A Study of Effectiveness of e-Learning and Blended ...I, Prabhas Ranjan, hereby declare that this thesis titled, “A Study of Eﬀec-tiveness of e-Learning and Blended Learning Among

A thesis submitted in fulfillment of the requirements

for the degree of Ph.D.

A Study of Effectiveness ofe-Learning and Blended Learning

Among B.Ed. Students

Doctoral Thesis

DEPARTMENT OF EDUCATION

Patna University

Researcher

Prabhas Ranjan

Supervisor

Dr. Lalit Kumar

Professor

Faculty of Education

Department or School Web Site URL Here (include http://)

http://www.university.com

http://www.glocaledu.net

nnn

Declaration by the Candidate

I, Prabhas Ranjan, hereby declare that this thesis titled, “A Study of Effec-

tiveness of e-Learning and Blended Learning Among B.Ed. Students”

has been prepared by me under the guidance of Dr. Lalit Kumar, Professor,

Faculty of Education, Patna University, Patna.

I also declare that this thesis is the result of my own efforts and has not been sub-

mitted to any other university or institution for the award of any degree, personal

favours whatsoever. All the details and analysis provided in the report hold true

to the best of my knowledge and belief. ...

...

...

...Signature of the Candidate

Date: Hea

Place: Hea

(Prabhas Ranjan)He.

. Reg. No. 1381/1994 . .

iii

Certificate

This is to certify that Mr. Prabhas Ranjan has worked satisfactorily for the

requisite number of terms under my supervision in the Department of Education,

Patna University, Patna and the thesis entitled “A Study of Effectiveness of

e-Learning and Blended Learning Among B.Ed. Students” embodies his

own work.

Date: Research Supervisor,Heeee

Date: Research Supervisor,He

Place: Prof (Dr.) Lalit Kumar H

Professor, Faculty of Education

Department of Educationnn

Patna University, Patnaiiiii

DEPARTMENT OF EDUCATION

PATNA UNIVERSITY

TO WHOM IT MAY CONCERN

This is to certify that the thesis submitted by Mr. Prabhas Ranjan in the

Faculty of Education, is a record of bonafide research work on the topic “A Study

of Effectiveness of e-Learning and Blended Learning Among B.Ed.

Students” based on synopsis approved by the Post Graduate Research Council

(P.G.R.C.) Patna University vide P.U. Letter No. Acad/1621 dated 19.09.14.

He got an extension of time for submission of Ph.D. thesis vide PU Letter No.

Acad/4655, dated 25.10.2018. He has successfully completed pre-Ph.D. Course

Work.

...

...Prof. Khagendra KumarHi

HeadHead, Headdd

Date: Department of Educationnnn

Place: Patna University, Patnannn

.

Department or School Web Site URL Here (include http://)

University Web Site URL Here (include http://)

AbstractA Study of Effectiveness of e-Learning and Blended Learning Among

B.Ed. Students

by Prabhas Ranjan

Blended learning and e-learning are two popular subjects of research and practice

in educational institutions today. As a judicious combination of online and face-to-

face learning, blended learning provides a better opportunity to design learning as

per the needs of the learners. This study was spread over two years and conducted

at the Department of Education, Patna Women’s College, Bihar, India, to compare

the effectiveness of blended learning mode (including the specific teaching-learning

strategies) and online learning mode. Randomly selected sample of students with

comparable level of intelligence quotient (IQ) were subjected to both control and

experimental treatment. The researcher found that the average achievement scores

of the blended learning mode was larger than the online learning mode. The effect

was consistent across different subjects and there was no correlation between IQ

and achievement scores of the students. The study also identified an effective

model for blended learning in the given learning conditions and identified the

challenges of designing and executing them.

Keywords: blended learning, online learning, e-learning, learner-centric teacher

education, Moodle, Patna

AcknowledgementsI thank Prof. Rash Bihari Pd. Singh, Vice-Chancellor, Patna University, Prof.Ashutosh Kumar, Dean, Faculty of Education, Patna University, Prof. KhagendraKumar, Head, Patna University for providing conditions supporting research andlearning in the Department. I thank Prof. Lalit Kumar for his supervision andsupport. I thank all the faculty members of the Department of Education, PatnaUniversity, Dr. Munnawar Jahan, Dr. Jessi George Modi, for their encouragingwords. I thank Dr. Sr M. Rashmi, Principal, Patna Women’s College, who pushedus to complete the Ph.D. work. I thank Prof. Yedla C. Simhadri, Ex-Vice Chan-cellor, Patna University, who appreciated the topic and took a particular interestin getting me admitted to the Ph.D. programme. I also thank Dr Ram Ranjan,Asst. Professor, Macquarie University, Sydney for supporting in setting up thewebsite glocaledu.org, this was critical for conceiving this research topic.

I thank Dr. Upasana Singh, Head and Dean, Faculty of Education, PWC for hervaluable suggestions at critical moments. I appreciate all my colleagues at theDepartment, Dr. Anju, Rashmi Sinha, Sr. M. Saroj AC, Dr. Madhumita, MadhuSmita, and Babli Roy for helping me in academic works, directly and indirectly,related to the experiment conducted under this research. I also thank my studentswho were very keen about my research, especially the students of 2015-17 batchwho helped in setting up the project on blended learning. I thank Deepti Shahi,B.Ed. Student (2015-17) for assisting me in pilot testing various research tools andin different jobs. I also appreciate the students of the Department of Education,PWC for their participation in the research, especially Fatima Anjum, Nisha, andSweta Vikram (2017-19 batch) who shared my interest in the topic and conductedresearch under CPE program of UGC under my supervision. My experience withthem was helpful. I thank the vibrant research community who, participating indifferent seminars and at the LinkedIn portal, appreciated and showed interest inmy work. Their comments and questions were helpful.

I thank Dr. Chandra Prabha for her support and Keshav Koushtubh for his curiousinquiries and support in printing.

Prabhas Ranjan

vii

Contents

Declaration by the Candidate iii

Certificate by Supervisor iv

Certificate by HoD v

Abstract vi

Acknowledgements vii

Contents ix

List of Figures xv

List of Tables xvii

Abbreviations xix

1 Introduction 11.1 Visualising the problem . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Expanding modes of education . . . . . . . . . . . . . . . . . . . . . 21.3 Uncritical trends of e-learning in India . . . . . . . . . . . . . . . . 31.4 Need for reforms in teaching-learning practices . . . . . . . . . . . . 61.5 Rising needs of inclusive education . . . . . . . . . . . . . . . . . . 71.6 Emerging trends of e-learning and blended learning . . . . . . . . . 8

1.6.1 What is e-learning? . . . . . . . . . . . . . . . . . . . . . . . 81.6.2 What is blended learning? . . . . . . . . . . . . . . . . . . . 81.6.3 Face-to-face learning . . . . . . . . . . . . . . . . . . . . . . 101.6.4 Defining e-learning and blended learning for the study . . . 10

1.7 Features of e-learning and blended learning . . . . . . . . . . . . . . 111.8 Can e-learning and blended learning support learner-centric educa-

tion? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

ix

Contents x

1.9 Can e-learning and blended learning address the practical needs ofteacher education? . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

1.10 Lack of comparative study on e-learning and blended learning . . . 141.11 Summarising the problems . . . . . . . . . . . . . . . . . . . . . . . 151.12 Significance of study . . . . . . . . . . . . . . . . . . . . . . . . . . 161.13 Objectives and hypotheses . . . . . . . . . . . . . . . . . . . . . . . 16

2 Review of Literature 192.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.2 Theoretical debate relating to the topic . . . . . . . . . . . . . . . . 20

2.2.1 Implications for the present study . . . . . . . . . . . . . . . 222.3 Debate relating to research paradigm . . . . . . . . . . . . . . . . . 23

2.3.1 Discussing scientific paradigm . . . . . . . . . . . . . . . . . 242.3.1.1 Debate relating to statistical significance testing . . 26

2.3.2 Concluding the paradigm debate . . . . . . . . . . . . . . . 282.3.3 Implication for the research . . . . . . . . . . . . . . . . . . 28

2.4 Discussions on confounding variables . . . . . . . . . . . . . . . . . 292.5 Implication for the present research . . . . . . . . . . . . . . . . . . 322.6 General findings in the distance mode . . . . . . . . . . . . . . . . . 322.7 Experimental research on e-learning and blended learning . . . . . . 33

2.7.1 Comparing modes of learning (Objective 3) . . . . . . . . . . 332.7.2 Comparing the subjects (Objective 4) . . . . . . . . . . . . . 372.7.3 Relation between IQ and achievement (Objective 5) . . . . . 372.7.4 Implications for the study (Objective 3 to 5) . . . . . . . . . 38

3 Method of Research 393.1 Scientific methodology . . . . . . . . . . . . . . . . . . . . . . . . . 39

3.1.1 Experimentation . . . . . . . . . . . . . . . . . . . . . . . . 403.1.2 Characteristics of scientific-realist methodology . . . . . . . 433.1.3 A note on positivist method . . . . . . . . . . . . . . . . . . 44

3.2 Alternative study designs for present research . . . . . . . . . . . . 453.2.1 Causal models and factor analysis . . . . . . . . . . . . . . . 453.2.2 Survey type study . . . . . . . . . . . . . . . . . . . . . . . . 463.2.3 Experimental study . . . . . . . . . . . . . . . . . . . . . . . 47

3.3 Method of study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473.3.1 Variables of the study . . . . . . . . . . . . . . . . . . . . . 473.3.2 Experimental design . . . . . . . . . . . . . . . . . . . . . . 48

3.3.2.1 Experimental control . . . . . . . . . . . . . . . . . 483.3.2.2 Controlling the variables . . . . . . . . . . . . . . . 503.3.2.3 Further control on extraneous variables . . . . . . . 533.3.2.4 Preparation of evaluation tool . . . . . . . . . . . . 543.3.2.5 Validity and reliability . . . . . . . . . . . . . . . . 55

Contents xi

3.3.2.6 Equating the scores of achievement test . . . . . . 583.3.2.7 Delimitation . . . . . . . . . . . . . . . . . . . . . 58

3.3.3 Preparation for the experiment . . . . . . . . . . . . . . . . 583.3.3.1 Development of the course . . . . . . . . . . . . . . 593.3.3.2 Content of the course . . . . . . . . . . . . . . . . 613.3.3.3 Time and place . . . . . . . . . . . . . . . . . . . . 613.3.3.4 Statistical tools . . . . . . . . . . . . . . . . . . . . 61

3.4 Description of the participants . . . . . . . . . . . . . . . . . . . . . 623.5 Ethical concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

4 E-learning and Blended Learning: Designing and Challenges 674.1 Models exclusive for blended learning . . . . . . . . . . . . . . . . . 67

4.1.1 Face-to-face driver model . . . . . . . . . . . . . . . . . . . . 684.1.2 Rotation model . . . . . . . . . . . . . . . . . . . . . . . . . 684.1.3 Flex model . . . . . . . . . . . . . . . . . . . . . . . . . . . 684.1.4 Online lab model . . . . . . . . . . . . . . . . . . . . . . . . 694.1.5 Online driver model . . . . . . . . . . . . . . . . . . . . . . . 69

4.2 Models for online and blended learning . . . . . . . . . . . . . . . . 704.2.1 Classroom type online learning . . . . . . . . . . . . . . . . 704.2.2 Massive Open Online Courses (MOOCs) . . . . . . . . . . . 724.2.3 The ADDIE model . . . . . . . . . . . . . . . . . . . . . . . 754.2.4 Online collaborative learning(OCL) . . . . . . . . . . . . . . 784.2.5 Community of inquiry(CoI) . . . . . . . . . . . . . . . . . . 80

4.2.5.1 Social presence . . . . . . . . . . . . . . . . . . . . 824.2.5.2 Cognitive presence . . . . . . . . . . . . . . . . . . 824.2.5.3 Teaching presence . . . . . . . . . . . . . . . . . . 834.2.5.4 Evaluation of learning . . . . . . . . . . . . . . . . 854.2.5.5 Strengths and weaknesses of OCL and CoI . . . . . 85

4.2.6 Competency-based learning . . . . . . . . . . . . . . . . . . 864.2.7 Community of practice . . . . . . . . . . . . . . . . . . . . . 884.2.8 Summary of findings . . . . . . . . . . . . . . . . . . . . . . 92

4.3 Designing online and blended courses . . . . . . . . . . . . . . . . . 924.3.1 Setting up objectives of the course . . . . . . . . . . . . . . 944.3.2 Activities/strategy available for designing courses . . . . . . 954.3.3 Defining mode of control and roles of players . . . . . . . . . 964.3.4 Using multimedia and design theories . . . . . . . . . . . . . 96

4.4 Design effectively used in the study . . . . . . . . . . . . . . . . . . 974.4.1 Planning lessons for blended learning . . . . . . . . . . . . . 98

4.4.1.1 Initiating . . . . . . . . . . . . . . . . . . . . . . . 984.4.1.2 Learning activity . . . . . . . . . . . . . . . . . . . 984.4.1.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . 98

Contents xii

4.4.1.4 Evaluation . . . . . . . . . . . . . . . . . . . . . . 994.5 Template for lesson planning . . . . . . . . . . . . . . . . . . . . . . 994.6 Challenges of designing and transaction . . . . . . . . . . . . . . . . 101

4.6.1 Challenges relating to technical requirements . . . . . . . . . 1014.6.2 Challenges relating to learners . . . . . . . . . . . . . . . . . 1034.6.3 Challenges relating the B.Ed. curriculum . . . . . . . . . . . 1044.6.4 Challenges for new teaching-learning practices . . . . . . . . 105

5 Data, Analysis and Interpretation 1095.1 Description of collected data . . . . . . . . . . . . . . . . . . . . . . 109

5.1.1 Data relating to third and fifth objective . . . . . . . . . . . 1095.1.2 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 1125.1.3 Data relating to fourth objective . . . . . . . . . . . . . . . 1145.1.4 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 116

5.2 Results of the third objective . . . . . . . . . . . . . . . . . . . . . 1165.2.1 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 118

5.3 Results of the fourth objective . . . . . . . . . . . . . . . . . . . . . 1195.3.1 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 120

5.4 Results of the fifth objective . . . . . . . . . . . . . . . . . . . . . . 1205.4.1 Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . 122

5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

6 Findings, Conclusion and Implication 1236.1 Findings and discussion . . . . . . . . . . . . . . . . . . . . . . . . 123

6.1.1 Effective design for e-learning/blended learning courses . . . 1236.1.2 Challenges in designing and transaction of e-learning and

blended learning . . . . . . . . . . . . . . . . . . . . . . . . 1246.1.3 Effectiveness of blended learning and e-learning . . . . . . . 125

6.1.3.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . 1266.1.4 Effectiveness of learning modes across subjects . . . . . . . . 127

6.1.4.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . 1286.1.5 Relation between IQ and achievement . . . . . . . . . . . . . 129

6.1.5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . 1296.2 Towards generalisation . . . . . . . . . . . . . . . . . . . . . . . . . 130

6.2.1 Limitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1336.3 Implications and suggestions for new learning modes . . . . . . . . 134

6.3.1 Suggestions for teachers . . . . . . . . . . . . . . . . . . . . 1356.3.2 Suggestions for students . . . . . . . . . . . . . . . . . . . . 1366.3.3 Suggestions for policymakers . . . . . . . . . . . . . . . . . . 137

6.4 Scope for further study . . . . . . . . . . . . . . . . . . . . . . . . . 137

References 139

Contents xiii

A Descriptions of Matching Tools 159A.1 Multidimensional Aptitude Battery-II . . . . . . . . . . . . . . . . 159

A.1.1 Verbal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159A.1.2 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

A.2 Computer Attitude Scale (CAS) . . . . . . . . . . . . . . . . . . . . 162A.3 Learning and Study Strategies Inventory . . . . . . . . . . . . . . . 164

A.3.1 The skill component of strategic learning . . . . . . . . . . . 165A.3.2 The will component of strategic learning . . . . . . . . . . . 165A.3.3 The self-regulation component of strategic learning . . . . . 166

B Evaluation Tools 167B.1 Contemporary India and Education (C-2) . . . . . . . . . . . . . . 167B.2 Learning and Teaching(C-3) . . . . . . . . . . . . . . . . . . . . . . 170B.3 Critical Understanding of ICT (EPC-3) . . . . . . . . . . . . . . . . 172B.4 Assessment for Learning (C-9) . . . . . . . . . . . . . . . . . . . . . 174

C Data Sheets 177

D Visuals of Modules 181

List of Figures

1.1 Continuum of mode of delivery before and after information age . . 3

2.1 Theoretical base of study . . . . . . . . . . . . . . . . . . . . . . . . 23

3.1 True experiment in education . . . . . . . . . . . . . . . . . . . . . 423.2 Verbal IQ scores across the groups . . . . . . . . . . . . . . . . . . . 623.3 Conceptual framework of research . . . . . . . . . . . . . . . . . . . 66

4.1 Three phases of online collaborative learning . . . . . . . . . . . . . 794.2 Community of Inquiry Framework . . . . . . . . . . . . . . . . . . . 814.3 The practical inquiry model . . . . . . . . . . . . . . . . . . . . . . 844.4 Life cycle of community of practice . . . . . . . . . . . . . . . . . . 91

5.1 Distribution of data . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135.2 Correlation matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

D.1 Moodle website http.glocaledu.org/elearning . . . . . . . . . . . . . 181D.2 Moodle website http.glocaledu.org/elearning . . . . . . . . . . . . . 181D.3 Moodle course writing interface . . . . . . . . . . . . . . . . . . . . 182D.4 Moodle course writing interface . . . . . . . . . . . . . . . . . . . . 182

xv

List of Tables

2.1 Scientific paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . 242.2 Online learning vs face-to-face learning . . . . . . . . . . . . . . . . 342.3 Blended learning vs face-to-face learning . . . . . . . . . . . . . . . 35

3.1 Variables of the experimental study . . . . . . . . . . . . . . . . . . 483.2 Experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . 513.3 Checklist for blended learning and e-learning . . . . . . . . . . . . . 513.4 Selection of participants . . . . . . . . . . . . . . . . . . . . . . . . 523.5 Structure and number of questions of written test . . . . . . . . . . 543.6 Alpha scores of MAB-II . . . . . . . . . . . . . . . . . . . . . . . . 563.7 Cronbach alpha results CAS . . . . . . . . . . . . . . . . . . . . . . 573.8 Alpha scores of LASSI . . . . . . . . . . . . . . . . . . . . . . . . . 573.9 Alpha scores of achievement tests . . . . . . . . . . . . . . . . . . . 573.10 Schematic layout of the samples . . . . . . . . . . . . . . . . . . . . 593.11 Raw score* ranges of student’s response in LASSI . . . . . . . . . . 633.12 Score* ranges of CAS . . . . . . . . . . . . . . . . . . . . . . . . . . 63

4.1 Evaluation of classroom type online learning . . . . . . . . . . . . . 714.2 Evaluation of MOOCs . . . . . . . . . . . . . . . . . . . . . . . . . 744.3 Evaluation of ADDIE . . . . . . . . . . . . . . . . . . . . . . . . . . 774.4 Evaluation of OCL . . . . . . . . . . . . . . . . . . . . . . . . . . . 804.5 Elements of COI . . . . . . . . . . . . . . . . . . . . . . . . . . . . 814.6 Evaluation of COI . . . . . . . . . . . . . . . . . . . . . . . . . . . 864.7 Evaluation of CbL . . . . . . . . . . . . . . . . . . . . . . . . . . . 884.8 Evaluation of COP . . . . . . . . . . . . . . . . . . . . . . . . . . . 914.9 Blended learning lesson planning . . . . . . . . . . . . . . . . . . . 1004.10 Online learning lesson planning . . . . . . . . . . . . . . . . . . . . 102

5.1 Summary of results . . . . . . . . . . . . . . . . . . . . . . . . . . . 1105.2 Summary of data first round . . . . . . . . . . . . . . . . . . . . . . 1115.3 Summary of data second round . . . . . . . . . . . . . . . . . . . . 1125.4 Blended learning mode scores across subjects . . . . . . . . . . . . . 1145.5 Elearning mode scores across subjects . . . . . . . . . . . . . . . . . 1155.6 Face-to-face mode score across subjects . . . . . . . . . . . . . . . . 115

xvii

List of Tables xviii

5.7 Summary of findings of of the third objective (*based on z-scores) . 1185.8 ANOVA result of subject-wise comparison . . . . . . . . . . . . . . 119

Abbreviations

ADDIE Analyse, Design, Develop, Implement, and Evaluate

B.Ed Bachelor of Education

DTH Direct To Home

DV Dependent Variable

F2F Face-to-face

ICT Information and Communication Technology

IGNOU Indira Gandhi National Open University

IQ Intelligence Quotient

IV Independent Variable

K-12 Kindergarten to 12th Class

LMS Learning Management System

MAB-II Multidimensional Aptitude Battery-II

MCQ Multiple Choice Questions

MOOCs Massive Open Online Cources

NCERT National Council for Educational Research and Training

NCF(SE) National Curriculum Framework (for School Education)

NCFTE National Curriculum Framework for Teacher Education

NCTE National Council for Teacher Education

NHST Null Hypothesis Significance Testing

NIOS National Institute of Open Schooling

NPTEL National Programme on Technology Enhanced Learning

NTA National Testing Agency

OCL Online Collaborative Learning

xix

Abbreviations xx

PIQ Performance Intelligence Quotient

SIQ Sum of Intelligence Quotient

SWAYAM Study Webs of Active–Learning for Young Aspiring Minds

UGC University Grant Commission

UTAUT Unified Theory of Acceptance and Use of Technology

VIQ Verbal Intelligence Quotient

Chapter 1

Introduction

1.1 Visualising the problem

By the second decade of the 21st century, the use of Information and Communi-

cation Technology (ICT) for education is many decades old. Introduction of new

technologies for supporting education consequently influences the technology of ed-

ucation. In other words, the technology that helps to impart education, influence

how it should be imparted. They raise new questions and create new problems.

But it is also important to see how are they addressing the long-standing ques-

tions and challenges of education. Low learning attainment by students in formal

education (in a classroom setting) is one such long-standing problem. Especially

in a populous country like India, formal education is highly challenged due to lack

of facilities, qualified teachers and quality education. Even in the best conditions,

formal education imparted in the traditional way is not efficient to fulfil the needs

of diverse learners. This problem, though identified long back, is yet elusive of

a direction toward a solution. We always expect new technologies to reflect on

these problems and elaborate on their potentials. The new medium of the Inter-

net is one such technology. We need to explore its potentials regarding solving our

long-standing problems.

1

Patna University

Chapter 1. Introduction 2

1.2 Expanding modes of education

Before the information age, the world of education was marked by two modes of

delivery of education. The first one was the face-to-face or regular mode, and

the other was distance mode. They were the two opposite ends of a continuum

of modes of education. These two modes differ in features like the degree of

resource intensiveness, size of learner group and commitment of the learners in

the context of time and place. The face-to-face mode demands from the students

a commitment to the institutional time table and attendance at a place. On the

other side, the distance mode demands no commitment to institutional time table

and place. The students are widely distributed over a large geographical area.

These two modes are sharply divided. The face-to-face mode is resource-intensive,

whereas the distance mode needs fewer resources.

This dichotomy of modes gets changed with the fusion of online and face-to-face

learning known as blended leading. In recent decades, blended learning is emerging

as an alternative mode that shares features of both of the previous modes. It sits

on the middle ground of the continuum that starts with the face-to-face mode or

regular mode and ends at distance mode. The online learning is mostly conducted

as asynchronous learning, where the teachers and students need not be together at

a given point of time. They may be dispersed over a wide geographical area, as in

the distance learning. But there is a possibility of monitoring the activity of each

of the students in real-time. The study materials also can be tailored according

to the needs of the learner.

In many of the institutions, the continuum is populated by different modes of

learning. For example, Some institutions use classroom aids, computer labs or

laptop instruction, web-enhanced learning, blended learning, and fully online in-

struction as alternatives to face-to-face learning. A number of experiments are

being done in this field and many fanciful terms like Hybrid Learning, Conversed

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Figure 1.1: Continuum of mode of delivery before and after information age

Learning, Conflex Learning, etc. are vying for claim a place on the continuum

(Table 1.1).

These new modes are resource-intensive. They need extra investment at the time

of their inception and also for training the teachers for their effective use, though

they are said to be resource effective in the long run. There is a dearth of studies

that identify and compare their strength and weaknesses in different socio-cultural

conditions.

1.3 Uncritical trends of e-learning in India

E-learning, specifically, online learning is a recently emerging trend in India. Indi-

ans are among the largest registrants in Massive Open Online Courses(MOOCs).

In an indigenous development, National Programme on Technology Enhanced

Learning (NPTEL) is jointly initiated by Indian Institute of Technologies (IIT)

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and Indian Institute of Sciences(IISc). They offer online courses for free and cer-

tification at a nominal cost in various topics. IITs have also developed MOOC

software MOOKIT for others to launch new courses with the motto that “creating

online courses should be as simple as taking them”. A MOOC on MOOCs course

has also been started to train teachers and other interested people to teach them

the functioning and pedagogical facets of MOOCs. Courses relating to Sciences,

Engineering, Humanities and Social Sciences have been developed. agMOOCs has

been developed especially for the students of agriculture. IIMs and Commonwealth

of Education are also involved in developing courses in India.

IIT Bombay in “Talk to a Teacher Programme” under National Mission on Educa-

tion through Information and Communication Technology (NME-ICT) has trained

thousands of teachers. There are other private initiatives like www.apnacourse.com

that support skill training and other courses for employs.

In the specific field of teacher education, there are Community initiatives like Teach

For India, which with the support of Central Square Foundation, developed an on-

line teacher training portal (www.firki.co). The aim is to empower the teachers,

enhance their pedagogical skills and encourage them to become reflective prac-

titioners. Firki aims to support high-quality in-service professional development

accessible to more teachers.

National Council for Educational Research and Training (NCERT) has started

MOODLE-based course ICT in Education for teachers and students for supporting

IT in school programmes.

SWAYAM (Study Webs of Active–Learning for Young Aspiring Minds) is another

programme initiated by Ministry of Human Resource Development, Government

of India to promote MOOCs in India. SWAYAM is conceived as an instrument of

self-actualising and life-long learning. The portal aims to provide all the courses

being taught in schools and universities. These are taught by the teachers of

eminent institutions of India and abroad. If a student is studying any course she

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in any college, she can transfer the credits earned on the portal to her academic

record. This portal provides opportunities for working or non-working as well as

the students studying in educational institutions a unique opportunity to expand

their skills and knowledge base.

Another programme with a similar name, SWAYAM Prabha is a subscription-

free Direct To Home(DTH) educational channels programme which telecasts high-

quality educational content using the GSAT-15 satellite transponders. At present,

there are 32 channels. These channels introduce four hours of new content daily,

which are repeated six times a day to facilitate the learners’ flexibility of time.

The contents for the channel are provided by NPTEL, IITs, UGC, CEC, IGNOU,

NCERT and NIOS. Thus the channels have contents for both higher education and

school education. All the disciplines like Natural sciences, commerce, performing

arts, social sciences and humanities, engineering, technology, law, medicine, agri-

culture, etc. are covered by them. The courses are related to certification vide the

SWAYAM platform. They have modules for teacher’s training, as well as teaching-

learning aids for students. They support preparation for competitive examinations

for admission in professional courses also. It also offers curriculum-based courses

for life-long learners from India and abroad.

All the instances above are aiming to teach a large mass of students mostly without

teacher’s monitoring. It is assumed that by putting learning material and labs on

the Internet and by making them available free of cost, the learner will start using

them for enhancing their knowledge. This is counter-intuitive, given the learning

habits of mugging up for success in examination acquired by a large number of

school-educated learners in India. The question that emerges here is about the

effectiveness of such endeavours without any institutional integration (in learner’s

educational institution). In other words, should these online learning be blended

with face-to-face learning at the learning institutions?

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1.4 Need for reforms in teaching-learning prac-

tices

A lot has been changing in teacher education recently, but they have little effect on

the teaching-learning practices at the institution level. The curriculum of an insti-

tution (there is little difference in syllabus and curriculum practically) is designed

and defined by autonomous universities and autonomous institutions. They are

provided with a syllabus framework by National Council for Teacher Education

(NCTE) to refer while constructing their curriculum. This National Curriculum

Framework for Teacher Education (NCFTE) . The NCFTE itself refers to con-

current National Curriculum Framework (NCF) for School Education for guiding

principles and objectives. Whereas this web is yet to function in an optimal way,

the policymakers keep on making new frameworks for school education and teacher

education on certain intervals to address the changing needs of society and learn-

ers. Despite this exercise, the present scenario of school education in India is

summarised by NCERT (2006, p.iv)in the best manner:

“... Indian School Education System ... is largely a monolithic sys-

tem perpetuating a kind of education which has resulted in a set of

practices adopted for development of curriculum, syllabus and text-

books that is guided by the patterns and requirements of the examina-

tion system, rather than by the needs determined by a mix of criteria

based on the child’s learning requirement, aims of education and the

socio-economic and cultural contexts of learners. A marked feature of

educational practices in school is a dull routine, bored teachers and

students and rote system of learning.”

An extensive intervention to change the focus of teaching-learning practices from

exam-centric education to learner-centric education is needed. We need to under-

stand the utility of blended learning in this regard.

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1.5 Rising needs of inclusive education

Besides, education is perceived as a tool for achieving equity in society by the

policymakers. The biggest challenge is to translate this aim into teaching-learning

practices. The NCERT (2006, p.iv) document identify the challenge as “conceptu-

alising flexibility or diversity” that is limited by the inherent rigidity of the system

and its “inability to define the role of the ‘curriculum’ and its transaction”. In

other words, the curriculum in its construct and transaction has failed to identify

the diversity of learners and learning styles and grooming their potentials. By its

monolithic structure and indiscriminate style of transaction, the education system

in India is recasting the social acceptance of inequality. It is with this view that

the present National Curriculum Framework 2005 and the National Curriculum

Framework of Teacher Education (2009) emphasise on the inclusion and learner-

centric education. The two terms despite different origins have a lot in common.

In the social context, for sustainable and holistic development, the concept of in-

clusion is mandatory. On the other hand, our understanding of the psychology of

learning has convinced us that learning is an individual endeavour, teacher and

any other outside agent has to facilitate it.

With the development of online technologies, a number of options have emerged

to assist the teachers for better support of the individual needs of learners. There

is a need to explore these options.

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1.6 Emerging trends of e-learning and blended

learning

1.6.1 What is e-learning?

In early writings, e-learning is often synonymous to online learning. But nowa-

days, it is perceived as any type of learning where digital technology is used as

a primal source of information and knowledge. This is a very broad definition

which includes all types of digital learning in its fold (for example, CAI, Videos,

PPT Presentations, etc.) besides the online learning. Often, the terms of digital

learning and online learning are used for specifying them separately.

Rosenberg (2001, p. 29) defined e-learning as the “use of the Internet technologies

to deliver a broad array of solutions that enhance knowledge and performance.”

e-learning can be described as a type of resource-based learning in which the

learners get learning content through learning materials rather than via teaching.

“The term ‘resource-based’ is often used as an ‘opposite’ to ‘taught”’ (Race, 2008,

p. 19). In this case, the resource can be accessed through the Internet. “The

learning that happens in resource-based learning usually opens up some freedom

of time and pace, if not always that of place.” In such type of resource-based

learning, the learners themselves have to be more responsible for their learning

than in traditional teaching-learning situations. (Race, 2008, p. 18)

1.6.2 What is blended learning?

The term blended or blending is in use in educational contexts for a long time.

It was used for using different learning environments to facilitate the learners’

construction of their own idea by interacting with different types of resources

and activities. It is an art that has been practised by inspirational teachers for

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centuries. In recent decades, the term ‘blend’ is being specifically used to refer to

the blending of e-learning with the traditional face-to-face mode of teaching.

In blended learning, also known as hybrid or mixed-mode learning, a portion of

the traditional face-to-face instruction is replaced by web-based online learning.

Yet, as McGee and Reis (2012, p.18) pointed out that there is consensus about

a number of aspects of blended learning, but he does not show any consensus

about the exact structure of a blended course. He asserts that “a snapshot system

that personifies those unique elements of a blended course can inform, model, and

clarify how blended course differs from other delivery designs.” Educational insti-

tutions generally used ‘blended’ to refer to a combination of face-to-face teaching

and online teaching. Graham et al. (2014) also found that in the research on

blended e-learning, most of the blended models adopted the combining of online

and face-to-face instruction. Blended learning is a widely researched phenomenon.

Drysdale et al. (2013, p. 98) reviewed over 200 masters’ theses and doctoral disser-

tations related to blended learning and have found that the graduate research on

blended learning was increasing. He also identified a growing perception among

researchers that blended learning was superior to predominantly or exclusively

e-learning methods and traditional method as well.

Blended learning is defined as a mixed-mode of learning in which both face-to-

face and online learning are used. Spiliotopoulos (2011) in Towards a Technology-

Enhanced University Education defines “blended learning as a learning model or

approach that mixes both web-based, mobile technologies, and classroom tech-

nologies for on-campus courses or programs (with or without a reduction in ‘seat

time’)”. According to the Sloan Consortium (Sloan-C), a leading professional or-

ganisation dedicated to promoting and supporting online education, “a blended

course is one in which 30 per cent to 70 per cent of the instruction is delivered

via technology. Sloan-C further defines this type of course as one “that blends on-

line and face-to-face delivery. A substantial proportion of the content is delivered

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online, typically uses online discussions, and typically has some face-to-face meet-

ings” (Sloan Consortium’s Definition),(Dziuban et al., 2011). Thus, e-learning and

blended learning can be identified separately with reference to the use and non-use

of face-to-face learning.

A blended learning course combines the best features of in-class teaching with the

best features of online learning to promote active, self-directed learning opportu-

nities for students with added flexibility (Garnham and Kaleta, 2002). Garrison

and Vaughan operationally define blended learning as “the organic integration of

thoughtfully selected and complementary face-to-face and online approaches and

technologies”. Face-to-face activities can support online activities or vice versa,

depending on the emphasis placed on the two options for engagement (Crichton

and Childs, 2008)

1.6.3 Face-to-face learning

Face-to-face learning is an institution-based instructor-mediated learning which

can be both teacher-centric (for example, lecture method, demonstration method,

etc.) and learner-centric (for example, project method, source method etc.). Face-

to-face learning is generally conducted at a classroom, which means any learning

space where learning can take place without interruption by outside distractions.

The greatest challenge in learner-centric methods in face-to-face mode is monitor-

ing and evaluation of learner’s participation and achievement.

1.6.4 Defining e-learning and blended learning for the study

In this work, we adopted the meaning of e-learning that specifically referred to

it as online learning. As such, e-learning is described as an electronically carried

out learning facilitated and supported by the use of computers, networking and

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multimedia. In this perception of e-learning, the use of networking (Internet or

intranet) is crucial.

For the purpose of this study, the blended course was one in which a part of the

instruction (30% to 70%) is delivered via online modules, and face-to-face activities

are designed to initiate, motivate and consolidate that learning by discussion.

In this study, face-to-face learning was the lecture-discussion method with chalk-

board and textbooks as teaching aids.

1.7 Features of e-learning and blended learning

The main feature of blended learning is effectively proportioning of e-learning

(online) and face-to-face learning on the basis of the needs of the learner, the

objectives of the instructor and the aims of the institution. The other features are

• E-learning is a type of resource-based learning in which the subject content

is provided to learners through materials rather than via classroom teaching.

The term ‘resource-based’ is often used as an ‘opposite’ to ‘taught’ (Race,

2008).

• The e-learning and the part of blended learning that is conducted through

resource-based learning provide some freedom of time, pace, and place for

the learner.

• In all varieties of resource-based learning, the learners themselves are more

responsible for their learning than in traditional teaching-learning conditions.

• In a blended learning course, the best aspects of classroom teaching is com-

bined with the best features of online learning. It promotes active, self-

directed and flexibility of learning for students. (Garnham and Kaleta, 2002).

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1.8 Can e-learning and blended learning support

learner-centric education?

Blended learning has many features of a learner-centric education. The learner-

centric education has emerged out of constructivism. In this approach to teaching-

learning, it is believed that the learners construct their knowledge themselves.

Each learner individually constructs meaning as he or she learns. E-learning com-

ponent of blended learning is oriented towards constructivism as it gives some

control over time and place of learning to the learner. The learners get a variety

of learning material in various formats and media. There are a number of gen-

eral principles of learning that are derived from constructivism, and that can be

supported through e-learning.

According to the proponents of constructivism:

• Learning is an active process in which the learner engages with ideas. By

providing online interactive resources for learning, e-learning gives an oppor-

tunity for learners to engage with the ideas.

• Reflection on learning is a key component of the learning experience. It

helps in both constructing meaning and constructing systems for organising

meaning. By providing the freedom to the learners to engage themselves

with the content presented in a variety of formats and allowing them to

engage with it, as many times as they want, e-learning provides a better

scope to reflect on their learning.

• Learning involves the use of language for self-expression and for consolida-

tion. The e-learning environment supports this function by providing op-

portunities for two way interaction with the teacher and among the learners

through online forums and chatting.

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• Learning is socially mediated. A student learns by intimately associating

with teachers, peers, family, relatives and other acquaintances. E-learning

provides a longer duration for association in the context of any particular

topic with teachers peers than the time-constrained classroom communica-

tion.

• Learning is contextual. A student learns in relationship to her previous

knowledge, belief, prejudices and fears. E-learning provides longer exposure

to the content. Thus, it provides better opportunities to reflect, express and

gather like-minded people.

• New learning builds upon previous learning. A learner absorbs new knowl-

edge on the basis of some structure developed from previous knowledge. It

is very difficult for a learner to keep pace with new learning if he lacks in

previous knowledge. Such conditions are difficult to be addressed in the

classroom. E-learning provides many opportunities like mindmaps and revi-

sion videos for quick recapitulation of the previous knowledge.

• Finally, learning is not instantaneous. For significant learning, one needs to

revisit the ideas, ponder them, try them out, play with them and use them.

Resource-based online learning provides the best opportunities for that.

1.9 Can e-learning and blended learning address

the practical needs of teacher education?

As found in many research, the blended learning courses are more popular among

the western institutions as they provide the benefits of both face-to-face and e-

learning (Olson as cited by Drysdale et al. (2013); Kaleta et al. (2005)). There are

several features of blended learning that are useful for teacher education.

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• Teacher education is practical and training oriented course, and at times

the theoretical component is not emphasised adequately. Blended learning

can be a part of a strategy to compensate the limited communication dur-

ing classroom transaction, and a part of the theoretical component can be

transferred online.

• Teacher education is a multidisciplinary subject. NCFTE suggests for deeper

integration with the general education faculties of the parent university. E-

learning can facilitate a better mode of faculty collaboration across disci-

plines through online support.

• Many parts of the curriculum developed on the framework provided by

NCTE are monotonous. Teachers can introduce new engaging activities

for motivating students.

• Many course components of teacher education programme need more drilling.

Those may be put online.

• Blended learning strategy should be designed to achieve the aims and ob-

jectives of National Curriculum Frameworks and to address the needs of

faculty and student simultaneously. With this, blended learning can become

a powerful force for transformation.

• Transaction of online course also generates data of students habits and per-

formance of students that can be used for self-analysis and for better evalu-

ation of the learning content and method.

1.10 Lack of comparative study on e-learning and

blended learning

Given the features of blended learning, it is widely adopted in the western educa-

tion system. Many studies have been conducted to test its effectiveness. But it is

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relatively rare in India. Its effectiveness needs to be verified empirically.

In a search result for ‘blended learning’ with ‘experimental’ as filter word, only

one result was found. The work by Scaria (2016) is about developing a blended

learning package. It is not experimental. There was no study comparing online

and blended learning as late as August 2019.

1.11 Summarising the problems

• Regular mode of education has a number of unanswered issues relating to

students’ learning attainment.

• Modes of education are expanding, but there is a dearth of study about their

effectiveness.

• The emerging trend of online learning in India is uncritical about its effec-

tiveness and about its integration in regular teaching-learning.

• Teacher-centric education has moved towards examination-centric education.

Learning is amiss in this approach.

• Help of technology is needed to address the diverse needs of inclusion.

• Potentials of e-learning and blended learning need to be explored in the

context of learner-centric education.

• There is a lack of study about the comparative effectiveness of e-learning

and blended learning.

It is in these contexts the present study has been taken up.

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1.12 Significance of study

The use of Online Learning and Blended Learning have become popular themes

among the researcher recently. This study is significant for the following reasons:

• This study compared the effectiveness of blended mode with that of online

mode of learning by comparing the learning achievements of students. These

modes are yet to be widely adopted in the Indian education system. This

study is a significant reference for future researchers.

• This study was set in one of the backward states of a developing nation.

This provided a perspective on the effectiveness of the blended and online

mode in that context.

• It can be used to make informed decisions pertaining to the selection of the

mode of education by the curriculum designers and policymakers.

• It highlights a system to organise learning for the modes of blended and

online learning.

• It also elaborates the challenges of conducting these modes.

• The study evaluates the possibilities of blended learning in achieving a great

degree of coverage of the learners and communicating messages in a con-

sistent fashion which results in all learners receiving equal opportunity to

learn.

1.13 Objectives and hypotheses

In light of the above discussion, the objectives identified for the study were:

[O1] To identify an effective way of designing e-learning and blended learning

courses

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[O2] To identify the challenges in designing and transaction of the e-learning and

blended learning courses

[O3] To compare the effectiveness of two different instructional modes of e-learning

and blended learning

[O4] To compare the effectiveness of the two different instructional modes of e-

learning and blended learning across the different subjects.

[O5] To find out the relation between IQ of the students of B.Ed. and their

achievement scores across different instructional modes.

For addressing the Objectives from O3 to O5, the following hypotheses were for-

mulated.

Hypotheses relating to O3 were

H01 There is no significant difference between the students’ achievement scores

while learning in blended mode and face-to-face mode.


while learning in e-learning mode and face-to-face mode.


while learning in e-learning mode and blended Learning mode.

Hypotheses relating to O4 were

H04 There is no significant difference among the achievement scores of the stu-

dents across different subjects taught in blended learning mode.


dents across different subjects taught in e-learning mode.

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dents across different subjects taught in face-to-face mode.

Hypothesis relating to O5 was

H07 There is no significant relation between IQ of the students of B.Ed. and their


Chapter 2

Review of Literature

2.1 Introduction

All research have umbilical connections with the works done by previous re-

searchers. Good research of today has to be well informed of earlier research

in its relevant field. Review of literature is the practice to take stock of what is

going on in the chosen field of study. Dziuban et al. (2016) describes the probable

purposes of the literature review as follows:

• Summarise and synthesise the scope and findings in a body of research

• Identify gaps in the existing research to guide future research

• Set the context and rationale for current research

• Critically examine methods and arguments used by researchers

• Assist in developing and evaluating theory and practices

• Understand the historical development of an idea or theory

19

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Chapter 2. Review of Literature 20

The literature review relates the conceptual, theoretical and empirical background

of the problem identified by the researcher and walks him through the contempo-

rary paradigms of research as practised by the researchers in the area relating to

the topic.

This study was an effort to put the blended learning and related terms in the

context of broader debates on teaching strategies and modalities. These following

aspects are covered in this chapter.

1. Theoretical background in the form of debates relating to the topic

2. Review of literature related to experimental study contrasting online or

blended learning

3. Debates relating to the research paradigm adopted for this study

2.2 Theoretical debate relating to the topic

There are two theoretical positions directly concerned with the topic of the study.

The first one relates to the method/strategy of teaching-learning. The movement

from face-to-face mode to the blended mode or e-learning mode can be perceived

as a movement from teacher-centric to learner-centric methods. It has already

been discussed in the First Chapter. The second inherent theory is the use of

media for teaching-learning.

McLuhan (1964) argued that “medium is the message (p.23)” and “media are

extensions of mind, body and being. (p.121)” As a critique of media, McLuhan

suggested being cautious about such extensions. He perceived them as not neces-

sarily benevolent and suggested that we should be careful while using them.

Thinking in the line of Mcluhan the e-learning is an extension of teacher’s mind

(when it serves as a portal for new learning) and eye (when it records student’s

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activity). The effectiveness of these extensions is debated in the Media Debate.

The Media Debate also known as Clark-Kozma Debate is related to the uniqueness

of medium or media as a factor of enhancement in learning.

Clark (1983) argued that media is just a vehicle of the message and has nothing to

do with the enhancement of learning just like a transporting vehicle used to deliver

goods to a store has no influence on the articles it carries(p.445). He also held

that the same learning goal could be achieved by using different media, and no

single media attribute can be related to a unique cognitive effect for some learning

task. Same learning results can be achieved by a different combination of media

(Clark, 1994). Hence the teacher or designer should choose a less expensive and

more effective way to represent and deliver instruction.

Kozma (1994) , on the other hand, believed that the specific media have specific

characteristics that make them more or less suitable for the accomplishment of

certain kind of learning tasks. He argued that the capabilities of a medium were

related to its three aspects. The first is the technology that determines a medium’s

function in terms of physical, mechanical or electronic capabilities. The second

aspect is the symbol system(s) that determines the symbols, specific rules and

conventions for symbolic expression, for example, printed texts, spoken language,

graphics, spoken language, musical scores. The third aspect is the abilities of the

medium to operate on symbol systems in specified ways. For example, displaying,

receiving, retrieving, displaying, transforming, evaluating.

Kozma (1994) further states that the right question to ask is not whether media

influence learning, but it is “how do media affect learning?” He suggests that we

should explore “the relationship between media and learning.” We should explore

the ways we can “use the capabilities of media to influence learning for particular

students, tasks, and situations.”

Both propositions of the debate have some research base in later findings. Means

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et al. (2010, p. 40) referred seven studies on the online environments where differ-

ent types of media (one way video) was used. The studies by Maag (2004); McK-

ethan et al. (2004); Schnitman (2007); Schroeder (2006); Schutt (2007); Schmeeckle

(2003); Zhang et al. (2006) had found no significant differences among different me-

dia combinations. These studies found no effect on learning from additional media

to online instruction. Tantrarungroj (2008) however had found that the blended

learners were significantly better on a “knowledge retention test held after four

weeks of intervention.”

2.2.1 Implications for the present study

Use of technology in teaching-learning is debated since ancient time. Even the

technology of writing was disapproved by Socrates, who believed that it would

diminish the student’s memory. The new media can claim a success story in a

short period. Since the beginning of the Media Debate in 1983, the new media has

proved its significance, and the debate seems to be more or less settled in favour

of using them for education.

This study was aimed to follow the Kozmza’s line of thinking while keeping the

perspective in mind that a badly managed online or blended course might confirm

the views expressed by Clark.

The theoretical structure of the study is summarised in the Figure 2.1. The study

was a comparison of learner’s achievements through their studies of the online

modules (resource-based learner-centric learning), face-to-face as well as online

modules (learner-centric learning, and face-to-face learning.

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Figure 2.1: Theoretical base of study

2.3 Debate relating to research paradigm

A paradigm represents the practices of a community of researchers. It defines a

model to be imitated and further extended. Future research try to fit themselves

to the established pattern. This notion of paradigm represents a wide range of

activities (Klee, 1997, p.134):

• the settling of the fundamental principles of the domain

• the subsequent possibility of extremely precise research

• a pedagogical tradition that trains succeeding generations in the

use of the paradigm

• a collection of institutions designed to promote the paradigm (pro-

fessional journals, professional associations)

• and a worldview with metaphysical consequences

The paradigms also suggest answers and put constraints on what will count as

successful solutions to a problem or puzzle. They give us not only the problems

to solve, but also guide us to identify when one can consider the problem to be

solved successfully from when it is not. Origin of a paradigm is in some kind of

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achievement, and it is often a stunningly successful solution to some problems.

That solution becomes the model for the later researchers under the paradigm to

emulate.(Klee, 1997, p.136)

2.3.1 Discussing scientific paradigm

Paradigm has five aspects. They are ontology, epistemology, theoretical perspec-

tive, methodology and method as described in Table 2.1. The last three objectives

of the research mentioned in Section 1.13 inherently had the assumption that a

single reality existed and that could be measured by reliable and valid tools. The

related theoretical perspective was positivism and post-positivism. The methodol-

ogy to explore these questions could either be survey-type research or experimental

research.

Ontology (What is reality) A single reality or truth existsEpistemology (How to know the reality) Measured by reliable and valid tools

Theoretical perspective (Approach to know) Positivism/Post-positivismMethodology (Ways to find them) Experimental or survey research

Method (Techniques to use) Sampling, Measurement andStatistical analysis

Table 2.1: Scientific paradigm

Research in psychology and education are related to three major philosophy of

science: empiricism, social constructionism, and scientific realism. Experiments

are related to scientific realism. Scientific realism is a development of and often

critical of positivism. Positivism was a popular movement in the theory of knowl-

edge (epistemology), mathematical logic, and philosophy of science. Klee (1997)

explained the position of positivists by elaborating their assumption that “logi-

cal relations between formal symbols could accurately represent external relations

between the objects, properties, or events to which the formal symbols referred.”

In other words, they believed that the natural phenomenon could be accurately

represented in mathematical formulations.

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Emerged to prominence during the Enlightenment Age, positivism emerged as an

approach to study in an organised way. Ontologically, this is related to realism.

Realism assumes that objects have an existence independent of the knower (Cohen

et al., 2011, p.7). The discoverable reality exists independent of the researcher. A

researcher uses language that designates a name to the phenomena, but the mean-

ing of the word is not just a discursive reality, the word owes to the discovered

phenomena itself for its meaning. Another feature of positivist epistemology is ob-

jectivism. The researcher approaches the questioned phenomena impartially. The

two are independent entities, and the meaning resides in the object/phenomena

under study, not in the mind of the observer. The observer has to obtain mean-

ing. The discovered knowledge is considered absolute (not relative) and value-free.

This knowledge is not situated in a political and historical context. The knowledge

is stated in factual and descriptive sentences.

In 20th Century, some of the assumptions of positivism were modified.

• Popper (1992, p. 425-90) held that the truth produced by scientific paradigm

is simply our belief in the current tested hypotheses.

• The principle of falsification argues that scientific theories can never be

proven true(Ernest, 1994, p.22). They can be tentatively accepted if all

attempts to refute them is exhausted. Popper (1992, p.280) suggests, “every

scientific statement must remain tentative forever”.

• For understanding some of the scientific theories, only the empirical data

may not be sufficient.

Post-positivist and scientific realist are not so assertive about this representation.

Identifying the common points among the versions of scientific realism, Haig (2013)

found two common doctrines as follows:

1. Existence of the world is independent of our perception, and it includes us.

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2. Scientific methods can give us knowledge about both observable and non-

observable feature of the world.

Besides, other doctrines held the truth as the primary objective of science. With

time, scientists produce better theories that represent truths in a better way.

However, many thinkers in behavioural sciences are cautious about making similar

claims. For example, Trout (1998) suggested a modest realism for psychology as

he perceived it less capable in creating “deeply informative theories like those of

physical sciences.”

2.3.1.1 Debate relating to statistical significance testing

Hubbard and Ryan (2000) have observed that statistical significance are the most

widely used methods for evaluating hypotheses in psychology. It is not one unified

theory of statistical significance but two different schools: Fisherian and Neyman-

Pearson. There are some points of difference between them, but they are used as

a unified theory. This has led to some confusion in the understanding of tests of

statistical significance.

The Fisherian school of significance testing seeks to test a hypothesis or theory of

interest against the null hypothesis that the expected effect is absent. According to

Fisher, the role of an experiment is limited to acquire the data to disprove the null

hypothesis. In this system, no alternative hypothesis is specified. There is no pro-

vision for Type II errors because the null hypothesis cannot be accepted. “Fisher

subscribed to an inductive conception of the scientific method and maintained that

significance tests are vehicles of inductive reasoning (Haig, 2013).” Moreover, it

holds p-values as measures of scientific evidence which was vehemently opposed

by many others.

Neyman and Pearson disagree with Fisher regarding a threshold p-value for re-

jecting the null hypothesis. They argue for the requirement of an alternative

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hypothesis and null hypothesis. In place of the p-value, they suggest the type-I

error rate α. They admit type II errors. To emphasise the difference, they call

their approach as hypothesis testing rather than significance testing.

Thus, “Neyman and Pearson take on measuring the reliability of errors in decision

making in the long run rather than with evidence for believing hypotheses in a

particular experiment. They do not measure the strength of evidence for different

hypotheses and thus do not tell us how confident we should be in our beliefs about

those hypotheses. (Haig, 2013).”

In many of the textbooks of research in behavioural sciences and education, a

hybrid of these two theories is presented in such a way that they look like one

single method. They are also misrepresented; for example, levels of statistical

significance are taken as measures of confidence in research hypotheses. Besides

these considerations, the textbooks’ approaches are criticised by philosophers of

science. They hold that the researcher is supposed to know that “given the data,

what is the probability that H0 is true?” However, what this method tells us that

“Given that H0 is true, what is the probability of these (or more extreme) data?

These are not the same.” In other words, the support for a hypothesis or theory

is claimed by rejecting the null hypothesis. Many scholars suggest that it is very

weak.

The use of the technique of Null Hypothesis Significance Testing (NHST) must

not end with reporting the p-value. It should accompany or be replaced by the

effect size. Effect size is a way of quantifying the difference between the two

groups. Moreover, a researcher may pursue other techniques like confirmatory

and exploratory factor analysis, meta-analysis, causal modelling etc. according to

her need. But, serious attention to the philosophy of research methods should be

given by the researchers to understand the contextual use of research methods.

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2.3.2 Concluding the paradigm debate

As a conclusion to the perception of truth in scientific paradigm, the two quotations

below underline the nature of truth claimed by it. The first one is from Klee (1997,

138-39):

. . . [N]ature is sloppy, complicated, and structurally obstinate, and

our powers of inventiveness and precision are finite and fallible. The

outcome of this is that no paradigm is perfect; no paradigm can give

a complete account of the domain over which it reigns. The intrinsic

incompleteness of paradigms means that there will always be a few

research results that do not fit the paradigm–that is, research results

that conflict with what practitioners using the paradigm would expect

to observe.

The other quotation is by Kuhn (1970, p.206). In the postscript to his famous

book The Structure of Scientific Revolutions, appended to the second edition of

the book in 1970, Kuhn wrote that

There is, I think, no theory-independent way to reconstruct phrases

like ‘really there’; the notion of a match between the ontology of a

theory and its ‘real’ counterpart in nature now seems to be elusive in

principle.

2.3.3 Implication for the research

The present research followed the scientific paradigm and believed that educational

practices and policies could be helped in a rational way by the scientific paradigm

of research. It could provide a theoretical structure which could help drawing

action plans for mass deployment of educational resources. The research also

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recognised the fact that all these endeavours are in the purview of theoretical

interpretation. Such interpretations are only ‘attempts’ to appropriate all known

features of phenomena.

The researcher also used effect size along with the Null Hypothesis Significance

Testing(NHST) for reporting the results.

2.4 Discussions on confounding variables

The term “Hawthorne effect” was coined by French (1953). It referred to a series of

brief experiments on managing factory workers carried out between 1924 to 1933 in

the Hawthorne Works of the Western Electric Company in Chicago. In this study

on the productivity of the factory workers, various conditions (pay, light levels, rest

breaks, etc.) were manipulated. The changes due to manipulation were increased

first and eventually return to the original conditions. The variables manipulated

by the researchers were of less importance. The important factor across these

experiments was the feeling of being part of an experiment or the feeling of being

observed. Mayo (1933) has suggested that it is due to sympathy and interest of

the observer. Even though this effect is debated by some observers, it is safe to

assume that in the research where human works are output or dependent variable,

they can’t be treated as material systems. The Hawthorne effect depends on the

mental states of the participants of the research: their knowledge, beliefs, etc.

Draper (y 16) has suggested a number of factors that may affect the experiment

as a Hawthorne effect. They are :

1. Material factors: for example as studied in original Hawthorne experiment,

i.e. illumination

2. Motivation or goals: Motivation of the workers, e.g. changes in actual re-

wards, piecework pay.

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3. Expectancies/expectation effects: Most of the time it is simply the individual

acquiring from others information about the work to get an idea what one

can expect of oneself; e.g. when one asks someone how long will it to climb

this hill, or prepare a recipe.

4. Learning effects: People get better at everything with practice. Counterbal-

ancing in experimental designs can control for this. However, as symmetric

learning effects can occur and undermine the counterbalancing.

5. Feedback: Students can’t learn new skills without good feedback. This can

often be a side effect of an experiment, and good ethical practice promotes

this further.

6. The attention of observers: For example, experimenters.

7. specific and known expectations of others: For example, experimenters, ob-

servers, supervisors, oneself.

He further elaborates that “in some cases there is a large effect that experimenters

did not anticipate, that is due to participants’ reactions to the experiment itself.”

He also quoted Adair (1984) who said that “the most important (though not the

only) aspect of this is how the participants interpret the situation. Interviewing

them (after the ’experiment’ part) would be the way to investigate this, and to

build in a precautionary check in every experiment (Draper, y 16).”

He considered it important because:

...[s]tudents and most experimental participants are doing things at

the request of the experimenter. What they do depends on what their

personal goals are, how they understand the task requested, whether

they want to please the experimenter or whether they see this task as

impinging on other interests and goals they hold, what they think the

experimenter really wants. Besides all those issues that determine their

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goals and intentions in the experiment, further aspects of how they un-

derstand the situation can be important by affecting what they believe

about the effects of their actions. Thus the experimenter effect is really

not one of interference, but of a possible difference in the meaning of

the situation for participants and experimenter. Since all voluntary ac-

tions (i.e. actions in most experiments) depends upon both the actors’

goals AND on their beliefs about the effects of their actions, differences

in understanding of the situation can have big effects(Draper, y 16).

Hawthorne effect is not alone in the research literature, which indicates uncertain-

ties of the experimental research on account of the perceptions of the participants.

There are several other observed phenomena which suggest similar effects. The

following list provided by Draper (y 16) tries to enumerate them at one place.

The John Henry Effect Suggested by Zdep and Irvine (1970); Saretsky (1972),

it is the opposite of the Hawthorne effect. This phenomenon occurs when a

supposed control group that gets no intervention compares themselves to the

experimental group and through extra effort gets the same effects or results.

Jastrow’s Effect In this effect, an explicit expectation about the performance

was transmitted and turned out to change the output. (Rosenthal, 1966;

Jastrow, 1900) In an experiment on factory worker it increased the effect

by a factor of three.

The Pygmalion Effect Also known as “expectancy advantage” it is a kind of

self-fulfilling prophecy. Teachers’ expectations of pupils can strongly affect

(by about a factor of two over a year) the amount of development they show.

Rosenthal (1966)

The Novelty Effect the participant performs differently at first because of the

novelty of the ’treatment’ which may change their expectations. Alterna-

tively, it can cause more alertness and make them perform differently. The

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experimenter is not important, but a materially unjustified belief any other

social media, may change perception operates through (say) attention rather

than through expectancies.

These discussions above had some important implication and prescriptions for this

research.

2.5 Implication for the present research

Studying the different effects during experimentation, the present researcher noted

some important directions (based on Section 2.4) for conducting this research:

• The experiment should not be one short term novel experience for the stu-

dents.

• Observations for the class selected for recording results for the experiment

should be well hidden among the regular practices.

• There should be many observations spread over time.

2.6 General findings in the distance mode

At one end of the continuum, we had distance education. There had been a

long history of distance education, and a number of the meta-analysis had been

conducted over the empirical reports in the field. The meta-analytical studies

of research literature on distance education by Bernard et al. (2004), Cavanaugh

(2001), and Moore (1994) had not found any significant difference between distance

education and face-to-face education. But a close study of Bernard et al. (2004)

reveals that behind this general conclusion, the variation in results is very high.

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The effect sizes vary from −1.31 to +1.41. The trend of negligible average but

a wide range of higher and lower values was a trend that continued through the

meta-analytical studies on online and blended learning.

There is a dearth of comparative experimental studies relating to distance edu-

cation in India. Besides the national level institution like IGNOU, there is less

number of high-quality distance education institutions. Many experts in India

would be apprehensive of a parallel statement (that distance education is equally

effective as face-to-face education) in the context of India. Yet, in western coun-

tries also, distance education is criticised for reducing education to some kind of

factory production process as it lacks the human dimension of group interaction

and alienates learners even from teachers. What was relevant for the purpose

of our study was the fact that this lack and interaction and alienation could be

avoided by online education.

2.7 Experimental research on e-learning and blended

learning

We found a number of research literature relating to the objectives three to five.

2.7.1 Comparing modes of learning (Objective 3)

The experimental research on online learning and face-to-face learning have shown

that the learning achievements for students in purely online and those who studied

in purely face-to-face were statistically equivalent. Means et al. (2010, p.xv) in a

meta-analysis found that in purely online and purely face-to-face conditions, the

research had an average effect size of +0.05, (Min −0.796 to Max +0.790) p =.46,

as depicted in Table 2.2

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Bernard and Lundgren-Cayrol (2001) studied online learning in the context of

the presence of the instructor as a moderator in online discussions. This study,

conducted in a teacher education course on educational technology, was about

the impact of moderation by the instructor. Students were randomly assigned

to different groups with high intervention and low intervention. The study did

not find a main effect for the moderator. In fact, the group for low moderator

performed significantly better than the other group. De Wever et al. (2008) also

found that the group with student moderators; rather, the instructor moderator

was significantly better. However, in the study by Zhang (2004), effectiveness

of instructor moderation of online asynchronous collaboration was significantly

higher. In this study, a group of students had an exclusive space for discussion,

whereas the other group’s discussion was moderated by the instructor.

Researchers Effect Size T-test(Z-Val) ParticipantsBeeckman et al. (2008) +0.294 3.03 426 participants

Bello et al. (2005) +0.278 1.05 56 participantsBenjamin et al. (2008) +0.046 0.14 Unknown

Beyea et al. (2008) +0.790 1.756 17–20 participantsCaldwell (2006) +0.132 0.43 60 students

Davis et al. (1999) -0.379 1.39 UnknownHairston (2007) +0.028 0.18 168 participants

Jang et al. (2005) -0.530 -2.69 105 studentsLowry (2007) -0.281 -0.84 53 students

Mentzer et al. (2007) -0.796 -2.35 36 participantsNguyen et al. (2008) +0.292 0.93 39 participants

Ocker and Yaverbaum (1999) -0.030 -0.14 43 participantsPadalino and Peres (2007) 0.115 0.41 49 participantsPeterson and Bond (2004) -0.100 -0.47 4 sections

Schmeeckle (2003) -0.106 -0.53 101 studentsSchoenfeld-Tacher et al. (2001) +0.800 1.74 Unknown

Sexton et al. (2002) -0.422 -1.10 26 studentsTurner et al. (2006) +0.242 0.66 30 students

Vandeweerd et al. (2007) +0.144 0.70 92 studentsWallace and Clariana (2000) +0.109 0.53 4 sections

Zhang (2000) +0.381 1.12 51 studentsZhang et al. (2006) +0.498 2.04 69 students

Table 2.2: Online learning vs face-to-face learning

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The review of literature on blended learning was concentrated on the replacement

model of blended learning. (Different models are discussed in chapter 4.) In this

model, some of the face-to-face lectures are substituted by the online material and

classes were reduced. Means et al. (2010, p.xv) reported that the combination

of purely face-to-face and online elements was more effective than face-to-face

instruction. The mean effect size was +0.35, p < .001.

At the same time, they cautioned that a larger effect size might be due to curricu-

lum materials and differences in aspects of the instructional approach, besides the

mode of instruction.

Researchers Effect Size T-test(Z-Val) ParticipantsAberson et al. (2003) +0.580 1.44 2 sections

Al-Jarf (2004) +0.740 3.82 113 studentsCaldwell (2006) +0.251 -0.99 60 students

Davis et al. (1999) -0.335 -0.99 2 courses/classDay et al. (1998) +1.113 3.85 2 sections

DeBord et al. (2004) +0.110 0.69 112 studentsEl-Deghaidy and Nouby (2008) +1.049 2.58 26 students

Frederickson et al. (2005) +0.138 0.40 2 sectionsMidmer et al. (2006) +0.332 1.56 88 studentsSchilling et al. (2006) +0.926 5.05 UnknownSpires et al. (2001) +0.571 1.60 31 students

Urban (2006) +0.264 1.37 110 studentsZacharia (2007) +0.570 2.64 88 students

Table 2.3: Blended learning vs face-to-face learning

In the meta-analysis done by U.S. Department of Education (Means et al., 2010,

p.38), ten studies comparing blended and online learning were compared. These

studies were levelled as “blended” or “purely online” on the basis of their inclusion

or exclusion of face-to-face learning, but the content and quality of instruction

across the two modes were also different.

The study referred Keefe (2003) who compared a blended class and an online

class who watched narrated PowerPoint slides shown online or by means of CD-

Rom. The blended class had a classroom lecture in addition to the online class.

Both groups could also use the e-mail, online chat rooms, and threaded discussion

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forums. Keefe found that the scores of the purely online group were around 8 per

cent lower than the blended group. This was the only study among the studies

selected for the meta-analysis that had a significant difference among the two

groups.

Poirier and Feldman (2004) used two groups for his study which were exposed

to predominantly face-to-face mode, but the face-to-face group was required to

participate in at least three online discussions during the course whereas the purely

online group had to participate in two online discussions with instructor each week.

Poirier and Feldman found a significant effect in favour of the purely online course

format for examination grades, but there was no effect on student’s performance

in writing assignments.

Campbell et al. (2008) studied a blended course which student got online instruc-

tion and attended face-to-face discussion along with a purely online course where

the students accessed instruction as well as participated in discussions online. Tu-

tors were present in both formats of discussions. Students had the freedom to

choose the format blended or online. In this case, the scores of the online discus-

sion group were significantly higher than the blended group.

Means et al. (2010, p.38-39) observed that the relative effectiveness of the blended

and purely online learning was dependent on the instructional element as in these

studies the instructional content was not controlled across the two modes.

Davis et al. (1999) , in their study, attempted to equate the instructional content

across three modes of delivery: blended, face-to-face and online. The students

were randomly assigned to the three sections. There was no significant difference

in posttest scores of the students(Means et al., 2010, p.39).

Means et al. (2010, p. 39) also reviewed six other studies (Beile and Boote, 2002;

Ruchti and Odell, 2002; Gaddis et al., 2000; Caldwell, 2006; Scoville and Buskirk,

2007; McNamara et al., 2008) where the purely online groups were contrasted with

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the blended group, but there was no significant difference. These studies also did

not attempt to equate the learning content across the modes.

Pereira et al. (2007) studied the impact of blended learning and traditional teach-

ing among the first-year students of Biology. They focused on their academic

performance and user satisfaction. They concluded that Blended learning was

more effective than traditional teaching for teaching human anatomy.

2.7.2 Comparing the subjects (Objective 4)

The comparative study across the subject is not done extensively in known liter-

ature. However the different studies are conducted on different subjects. Means

et al. (2010) have found that the common subject in many of the studies was

medicine or health care. Other subject used for study were computer science,

teacher education, mathematics, languages, science, social science, and business.

They further inform that there was no significant differences in effectiveness of

modes relating to the subjects of instruction(p. xvi).

Means et al. (2010) have studied the contrasts (16 studies) relating the medi-

cal/health care studies and found weighted effect size of 0.205 at the significance

level of 0.05 level. The lower and upper limits were 0.028 and 0.382. The studies

related to other subjects like teacher education, computer science, social science

and others (34 studies) reported weighted effect size of 0.199 at 0.01 level. The

lower and upper limits were 0.077 and 0.320.

2.7.3 Relation between IQ and achievement (Objective 5)

Jensen (1998) observed that even though the methodologies, data collection tech-

niques, and variables included in the studies have differences, they indicate that

intelligence and achievement are highly correlated. In a similar study,Kaya et al.

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(2015) have observed that several researchers demonstrated the relationship be-

tween intelligence and achievement with evidence that students with higher IQ

scores show significantly greater academic progress than those with lower IQ scores.

2.7.4 Implications for the study (Objective 3 to 5)

Regarding the studies relating to the modes of study, the possibilities of both

positive and negative results in cases of both e-learning and blended learning.

However, there were several precautions and implications for the study.

Means et al. (2010, p.49) cautioned that

“... the literature on alternative online learning practices has been

conducted for the most part by professors and other instructors who

are conducting research using their own courses. Moreover, the com-

binations of technology, content and activities used in different exper-

imental conditions have often been ad hoc rather than theory-based.

As a result, the field lacks a coherent body of linked studies that sys-

tematically test theory-based approaches in different contexts.”

Regarding the comparison across subjects, the studies shows that there is a low

possibility to get a significant difference. The conclusion is conducive to the logic

of the learner-centric approach where the content delivery is not important and

the learners are the agency of knowledge creation.

Regarding the correlation between IQ and achievement scores, a strong and posi-

tive relation is expected.

Chapter 3

Method of Research

The research methodology is an interdisciplinary field that gets informed by various

disciplines like statistics, philosophy of science, and cognitive science. In realist

or positivist methodology, the researcher has to specify three major tasks (Cohen

et al., 2011):

• Describe how the method functions.

• Evaluate method critically against their rivals.

• Suggest steps to use the method to achieve the research goals.

3.1 Scientific methodology

The goal of the scientific (positivist) methodology is to explain relationships. A

positivist researcher attempts to identify the causes that influence the outcome.

They aim at formulating laws, that can be used for prediction and generalisation.

They identify components of complex phenomena and try to find interrelation and

correlation among the components. They use random samples, selected variables

(independent and dependent variables), and empirical testing for getting verified

39

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Chapter 3. Method of Research 40

evidence. Their approach is characterised by procedure and methods which is

designed to discover general law and is replicable. They view their methodology

as value-neutral. Hence, the knowledge generated is also considered as value-

neutral. The post-positivists also follow a similar line except that they take the

perspective of the participants along with the observed data. Moreover, they do

not ’prove’ a hypothesis. They perceive the results as tentative and simply say

that the hypothesis was not rejected.

3.1.1 Experimentation

Experimenting is a legacy of natural science. The experimental research in ed-

ucation is generally related to social and educational psychology. It is almost a

hundred and a quarter of a hundred years old. One of the earliest experimenters

was Norman Triplett. In 1897-1898, he designed a simple laboratory experiment,

in which, he asked the participants to wind fishing reels in the presence or absence

of other participants. His intended to explain a phenomenon he had observed while

racing a bicycle. He has observed that racers performed better when competing

against others than when racing against the clock (Greenberg and Folger, 1988).

This was one of the earliest laboratory research. In social psychology studies, both

laboratory and field experiments are used.

There are three different types of laboratory experiments: First, impact experi-

ments; second, judgement experiments; and third, simulation. According to Aron-

son et al. (1985), in an impact experiment, the experimenter creates “conditions

that affect the subject, and those effects are measured.” In judgement experi-

ment, the participants are asked to “recognise, recall, classify, or evaluate stimulus

materials presented by the experimenter.” Fromkin and Streufert (1976) identified

simulation as another type of laboratory experiment. “A simulation is a laboratory

experiment that attempts to replicate, to varying degrees, features of real-world

environments or events.”

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In experimental research, an average causal effect (A) is found by the difference

observed in the experimental group, in contrast, to change in the control group.

Average causal effect (A) = (E1 − E2) − (C1 − C2),

where E1 is post-test for experimental group and E2 is pre-test for experimental

group; C1 is post-test for control group and C2 is pre-test for control group. A

schematic structure of a true research design is shown in Figure 3.1. Cohen et al.

(2011, p 315) mentioned three types of experimental research:

• The controlled experiment that is conducted in laboratory conditions. This

is called a true experiment

• The field or quasi-experiment is conducted in natural settings, but the vari-

ables are isolated, controlled and manipulated.

• The natural experiments are the experiments where it is not possible to

isolate and control variables.

In an educational experiment, field experiments are more common. Greenberg

and Folger (1988) observed that although both “laboratory and field experiments

are designed to test the cause-and-effect relationships between theoretically rel-

evant variables, field studies can be oriented either toward hypothesis testing or

exploration.” But, Kerlinger (1964) referred to the field study as “a scientific weak

cousin of laboratory and field experiments” (p. 390) (as quoted by Greenberg and

Folger (1988)). He attributed it as lacking in external validity. External validity

refers to the acceptability of the results of the research for generalisability to other

populations, settings, treatment variables, and measurement variables. Cook and

Campbell (1976) identified several factors which distinguished the field conditions

from the laboratory conditions. They are:

1. The difficulty of withholding treatments from no-treatment control groups,

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Matched onPre-test

Randomallocation to

group

ControlGroup

ControlGroup

Post-testIsolate, controlAnd manipulate

variables

ExperimentalGroupInterventionExperimental

Group

True Experiment in Education

Courtesy: Cohen et al (2011)

Figure 3.1: True experiment in education

2. The difficulty of being able to assign groups to conditions randomly,

3. A high degree of variability in sampling,

4. Subjects’ refusal to participate in treatment conditions,

5. High attrition rates caused by the treatment,

6. Heterogeneity in treatment implementation,

7. Feelings of resentment among no-treatment control subjects,

8. Treatment contamination resulting from social comparisons between sub-

jects, and

9. The dubious ethics of unobtrusive measurement.

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3.1.2 Characteristics of scientific-realist methodology

Scientific realism has a well-conceived methodology, which helps the researchers

in visualising the whole process beforehand. Haig (2013) has suggested a number

of characteristics of the scientific realist methodology that differentiate it from

others.

• The methodology describes how the method functions. It evaluates the

methods against their rival methods and recommends the way to use the

method to pursue the aims of the research.

• The realist methodology recommends valuable truth, explanatory under-

standing. and effective control as primary research goals and mutual adjust-

ment of method and research goals.

• It is naturalistic. It uses methods of various sciences to study. Proctor and

Capaldi (2001) advocated for empirical justification of methodological idea.

• Realist methodology is both generative and consequentialist. Generative, as

the term suggests, means creating new knowledge from observations. An ex-

ploratory factorial analysis is an example of a generative method that justify

the factorial hypotheses. A consequentialist method focuses on the testable

consequences of the reasoning from the acclaimed knowledge. An example

of consequentialist methodology is the hypothetico-deductive method. It

emphasises on predictive accuracy, which is used for justifying knowledge

claims.

• In the context of justification of knowledge claims, this methodology ac-

knowledges two different but complementary approaches. They are reliabil-

ism and coherentism. Reliabilism asserts that a belief is justified only to the

extent it is acquired by reliable processes. On the other hand, coherentism

suggests that the belief is justified as far as it is coherent to other beliefs.

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Thagard (1992) suggested a theory of explanatory coherence to illuminate

the coherentist perspective for comparative evaluation of scientific theories.

• The realist methodology holds science as a problem-oriented endeavour. In

this endeavour, correct identification of the problem is half the solution. Haig

(1987) even suggests that “problems are conceptualised as constraints of

their effective solution, and by including all the constraints in the problem’s

articulation, the problem enables the researcher to direct inquiry effectively

by pointing the way to its own solution.”

• Finally, it perceives the researcher as the “knowing subject.” The researcher

extensively uses heuristics to find her way towards a solution. For example,

the creation of hypotheses requires heuristic approach on the part of the

researcher.

These features indicate that the researcher should engage with the literature re-

lated to her problem for evaluating the variety of methods, strategies, and heuris-

tics that have been successfully used previously to produce valuable knowledge

about empirical phenomena and explanatory theories relating to his field.

3.1.3 A note on positivist method

Method of research represents the tools and techniques used for collecting, record-

ing, organising, and analysing the data. Good positivist research should be in-

ternally (Results are due to the manipulation of the independent variables only)

and externally valid (It can be transferred to other populations or situations).

They should be replicable (Different researchers can record data in the same way)

and reliable (Different researchers can arrive at the same conclusion). To achieve

this, the researcher needs to be objective, and her work should also be robust to

empirical refutation.

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With the aim of prediction and generalisation, the positivist researchers use tests,

questionnaires, observation schedules to generate quantitative data. Using descrip-

tive and inferential statistics, they analyse the data. The success of generalisation

depends upon the robustness of the process.

3.2 Alternative study designs for present research

In this section, three potential research designs have been discussed as rival meth-

ods for studying the problem undertaken by the present researcher. They are:

• Causal Model, for example, Unified Theory of Acceptance and Use of Tech-

nology (UTAUT) or Factor Analysis

• Non-experimental survey type study, for example, Community of Inquiry

(CoI) based evaluation of different modes

• Experimental design to compare the learning outcomes of the two methods

3.2.1 Causal models and factor analysis

Causal modelling and factor analysis were strong contenders for such studies.

There are some successful models for modelling the use of technology. For exam-

ple, Unified Theory of Acceptance and Use of Technology (UTAUT) by Venkatesh

et al. (2003). He suggested several models that could predict the success of tech-

nology adoption. These models are used for comparative studies on the adoption

of different technologies that can be validated by their actual use. The UTAUT

model is especially used for studying the acceptance of technology in institutional

conditions. It aims to explain user intentions to use an information system based

technology and subsequent behaviour regarding its usage.

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There were many contraventions which restricted the use of these methods for the

present study. Some of them are articulated as follows:

• Causal models and factor analysis needed a large number of participants.

The most liberal suggestion is a minimum of 200 samples for modelling and

100-plus for factor analysis. This was not practical for the conditions of the

present researcher.

• Causal models and factor analysis focus on the causes or factors. However,

the central question of the present study was relating to comparing the ef-

fects. Mere exploration of causes might have led to an indirect and tentative

explanation.

• Using these options for a comparative study of two educational modes would

be more viable had they been adopted by all the faculty members of the

institution. It would create a disposition among the students towards using

them. It can be observed in the four key components of UTAUT Model–

performance expectancy, effort expectancy, social influence, and facilitating

conditions–that they are suitable for technologies already introduced to and

experienced by the students.

3.2.2 Survey type study

A non-experimental method like survey type study was also a viable option, espe-

cially in the case of a normally occurring treatment. The Community of Inquiry

(COI) model-based study could be used for this study. The model had been dis-

cussed in detail in the relevant section of this report (See section 4.2.5).

The COI model theorises the whole field of teaching-learning in online and blended

learning systems. It defines them as consisting of three components. These com-

ponents are cognitive presence, teaching presence, and social presence. There is

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a tool developed for getting feedback from students regarding the specific com-

ponents of the model. The main reason for not using it for the study was that

there was no report of blended learning and online learning being used in regular

teaching-learning practice in the institutions of Bihar. The modes of education

under study were yet to be adopted by a large group.

3.2.3 Experimental study

This study required to answer the question which one of the two modes of teaching

could give better results. Since the study was concerned with cause and effect,

the experimental design was the first sought option. If efficiently designed and

executed, this design could give a definite answer to the question sought by the

study.

This study was seeking the effectiveness of the modes and did not explore the

causes of their effectiveness. Hence, it was designed to evaluate learning outcomes

in the form of knowledge, understanding, application and creativity. The steps of

the study are discussed next sections.

3.3 Method of study

The method of study section elaborates the systematic steps, tools and their va-

lidity and reliability.

3.3.1 Variables of the study

In quantitative research, a variable is a naturally found or conceived component

that has a varying quantity or a varying measurable quality. The dependent

variable (DV) is the variable of interest, whereas the independent variable/s (IV)

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is/are the variable/s that are manipulated to bring variance in dependent variable

thus establishing a causal/correlated connection between IV and DV. Confounding

variables (CV) are defined as interference caused by other variables unwanted and

sometimes unaccounted by the researcher. The variables of the study are depicted

in Table 3.1.

Independent Var.

Modes of Learning and respective strategies:Blended Learning: Teaching-leaning delivered througha combination of face-to-face and online delivery mode

e-learning/Online Learning: Teaching-learning deliveredthrough online delivery mode only

Face-to-face learning: Classroom teaching onlyDependent Var. Learning Outcome as measured by assessment tools

Confounding Var. IQ, Age, Attitude towards ICT

Table 3.1: Variables of the experimental study

3.3.2 Experimental design

The aim of designing experimental research is to standardise the actions relating

to the research. It ensures that the results are a consequence of the identified

factors.

3.3.2.1 Experimental control

The key steps to designing an experiment are to manipulate the independent

variables (IV) and control extraneous variables. The researchers control the IV by

determining which variables are to be studied and what values of the IV should be

used. They also decide the manner to manipulate the IV. Extraneous variables,

on the other hand, are the unwanted variables needed to be controlled as they

may influence the results by masking or confounding. The confounding variables

masks by hiding or obscuring the effects of IV on the dependent variable (DV). It

may be due to variability in data or environmental conditions, timing and other

things. These affect the reliability of the study. Confounding, on the other hand,

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is a systematic and inextricable mixing of the extraneous variable with IV that is

inseparable, hence causing errors. (Gould, 2001, p. 163-4).

The challenges for experimental control in the present research were:

• The students of B.Ed. were from diverse age group (from 20 to 39).

• The students were of different educational streams like arts, science, com-

merce and even professional disciplines like MBA, Computer Science. They

have different self-efficacy and exposure to different institutional cultures of

teaching-learning.

• The students had various degrees of expertise in using ICT tools.

• Given the huge difference in marks between highest and lowest scores of

students in the entrance test examination, they can be suspected of having a

wide variation in their intelligence quotient (IQ). Though a clear correlation

has not been established between the IQ and the learning achievement of

the students, yet they are confounding when the results of the experiment

are dependent on the understanding and ability to apply new learning.

• The course content of the papers of B.Ed. was completely new to the stu-

dents. Hence, they were at a beginner level. So, a pretest for evaluating

their previous knowledge was very difficult.

Besides the confounds mentioned above, there were some other threats that were

relevant to the experimental control of the study. To start with, all the prac-

tices and activities of online and blended teaching were a new experience for the

students. This, in itself, was a confounding factor. As discussed in Section 2.4

about the Novelty effect, the perception of students towards the new experience

was different. The students took the courses with different feelings of excitement,

apprehension, and passivity. Where, some students were excited about the ap-

plication of new technologies, some others were apprehensive about the number

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of tests during and after the course. Still, others took it as an endeavour more

suitable for the resourceful students. They believed that the process was advan-

tageous for the students with a computer/laptop, as they could revise the things

before the examination.

Besides these participant biases, there were other issues of concern for an experi-

mental study:

• Instrumentation–that were the changes that may occur over time in the mea-

surement of a dependent variable due to variation in mechanical or human

observer factors.

• Statistical Regression–that was the change perceived as a tendency of par-

ticipants who obtained very high or very low test scores, in the beginning,

to move toward the mean of the group when measured again.

• Experimenter Features– It was the researcher’s expectancy or bias about

the performance of the learning modes. His performance as a teacher across

different stages of research, his appearance, and personality might influence

students to create their ideas about the study.

3.3.2.2 Controlling the variables

Experimental research, in essence, is controlling of variance. The present study

was a comparison of e-learning and blended learning. It was done by comparison of

the achievement scores of students in these modes with their achievement scores in

face-to-face learning. The design adopted for the study was a hybrid design known

as the Switching Replication Design or Matched Group Design. In this design, the

randomised groups are subsequently subjected to similar treatments. In other

words, the control group becomes the experimental group and vice-versa. It is one

of the most robust research designs. Exposing each of the groups to the conditions

of the experiment and control can also address a paradox of experimental research.

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In experimental research, when a participant is exposed to one condition, we can

only say that she has been impacted by the treatment, but we do not know what

would have been the results if she had been given the other treatment.

The study was designed as a post-test, two experimental random groups and a

control group design, as illustrated in Table 3.2 and Table 3.10. In addition to

this, the participants were matched on some extraneous variables. This design was

aimed to maximise the research variables and minimise the extraneous variables.

Experimental1 R X1 O

Experimental2 R X2 O

Control R X0 OR*: Random selection and random assignment to groups

X1&X2*: TreatmentsX0*: Control

O*: Observation*Notations adopted from Gould (2001)

Table 3.2: Experimental design

Tools used in the study

In this study, for the first objective, a checklist was prepared for identifying the

features and skill requirements for using different models of blended learning and e-

learning. In this checklist, the researcher identified the cost-effectiveness, blending

possibility, individualised learning, increased peer and teacher interaction. It also

enlisted the required skills for teachers and students for using the different models

(Table 3.3).

CostBlend with Individua- Increased Increased Skills/Face-to-face lized Peer Teacher Tools

effective Mode Learning Interaction Interaction Required

Table 3.3: Checklist for blended learning and e-learning

For the selection of participants, three tools were used for creating relatively ho-

mogeneous groups. They were: MAB-II, LASSI, and Computer Attitude Scale.

All the details of these tools are given in Appendix A. For the selection of first-

round research groups, the tools were administered on the students of B.Ed at

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the beginning of the session in July. Due to the absenteeism of some students,

data of some regular students could not be recorded. A total number of 45 and

49 students from two sections participated in the first round. The students who

were fulfilling the criteria of the scales mentioned above were 32 and 29. Finally,

20 students from each section were selected randomly from the list of matched

groups. Similarly, in the second round, the number of participating students from

the two sections were 47 and 48. The number of selected students were 31 and

33. Finally, 20 students from each of the sections were selected. The details are

given in Table 3.4. Twenty students in each section were randomly assigned to

two groups in each section.

Criteria for using the different tools are given below:

• MAB-II: Students with IQ scores between 80 to 105 were selected to avoid

extremes in any group.

• LASSI: Since many of the students had extreme scores in some of the sub-

scales, we selected the students who did not have extreme scores in more

than 3 out of 10 sub-scales of LASSI.

• Computer Attitude Scale: A minimum cut off score of 30 was set.

Year/Round First Round Second RoundTotal Students Recorded in Section A 45 47Total Students Recorded in Section B 49 48Total Students Matched in Section A 32 31Total Students Matched in Section B 29 33Total Students Selected in Section A 20 20Total Students Selected in Section B 20 20

Table 3.4: Selection of participants

Besides the tools used for grouping students, the researcher used four achieve-

ment tests for assessing the learner’s learning attainments (described in subsection

3.3.2.4).

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3.3.2.3 Further control on extraneous variables

To address the threats of novelty and unfamiliarity, we selected a larger section

to teach in blended and online mode than the portion of the course to be used

for recording the data. A period of ’cooling time’ was given in each round to

the students to adjust to the new modes. Content taught during this period was

not used for preparing the achievement tests. This also gave an exposure to the

students regarding what and how of using online modules.

It was also declared that the whole thing was a kind of exploration in the new

ways of learning, and it was not for evaluation of their B.Ed. Degree. Though the

students were told about the experiment, they were not told about the purpose

of each of the steps of the experiment. The students perceive them as a regular

activity except for the tests, about which they were not happy as usual.

The tests were also administered on all students. Fairness of administration of the

tests was maintained. The test was conducted in one hall with three invigilators.

The activity was conducted for all the students of both of the sections rather than

for the selected 40 students in two sections.

Other teachers of the Department were informed about the topic. They were

requested not to give any instructions relating to the topic during the stipulated

period.

Despite careful planning, all the long term experiments have to suffer the problem

of missing values. This was due to absenting subjects (participants) that created

two missing values in two years. We substituted those missing values with the

average achievement scores of the group of students.

Another potential threat to internal validity was to maintain consistency in the

measurement of the outcomes. It was essential for comparing the results of the

evaluation of students during each set of modules among each other. For each

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step of evaluation from construction to evaluation, a standard procedure was elab-

orated.

In order to control the non-sampling errors during the evaluation process, a marks

entry form was created and given to the evaluators. They recorded marks achieved

in different sections and total marks. Entries made by one evaluator ware checked

by another evaluator. The entries were later typed in the spreadsheet program of

the computer for further analysis.

3.3.2.4 Preparation of evaluation tool

The first step for the preparation of the assessment tool was to create standards

by creating a blueprint. The blueprint standards for written examinations are

depicted here in Table 3.5.

Type Knowledge Understanding Application TotalObjective 5 3 2 10

Short Answer 1 2 2 5Long Answer 1 1or2 1or2 4

Total 7 6/7 5/6 19

Table 3.5: Structure and number of questions of written test

The achievement tests were developed in different phases. In the first phase,

the experimenter set the objectives of teaching the topic by dividing content into

different learning levels. The critical information and ideas, understanding and

application of the new ideas were identified. The following steps were taken for

developing the tool:

• A pool of probable questions was prepared and arranged according to the

level of learning.

• Items were sorted and filtered as per their relevance to the objectives set at

the beginning.

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• The learning objectives and the items based on them were reviewed by an

expert.

• As per the suggestions of the expert, a tentative achievement test was pre-

pared by the experimenter.

• The experimenter also prepared an answer key along with the evaluation

criteria (guidelines) for subjective questions.

• It was also decided that in order to objectify the evaluation process, the vari-

ation of expression, spelling errors and presentation would not be considered.

It will also help in optimising the results.

• The tool was administered on fifteen students of the previous batch for a

pilot study. The meaning and clarity of each question were discussed, along

with the answer.

• Some items, as well as the guidelines, were modified and re-written.

• The finalised tools, along with the evaluation criteria and guidelines, were

shown to two experts.

• Items were edited as per the unanimous decisions of the experts.

3.3.2.5 Validity and reliability

Intelligence Test: Multidimensional Aptitude Battery (MAB-II) developed by

Douglas N. Jackson and adapted for Indian condition by Narender K. Chadhdha

was used for sorting the students into different groups. This instrument is suitable

for the assessment of intellectual abilities of both adults and adolescents aged 16

and older. It consists of two parts, namely, verbal and performance.

The instrument provided norms for nine age groups starting from 16 and up to

74. We used 3 of the norms for the age groups 20-24, 25-34, 35-44 since B.Ed.

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Full Scale (Standard Alpha Score): 0.78INF COM ARI SIM VOC DS PC SPA PA OA0.77 0.74 0.78 0.73 0.74 0.77 0.74 0.77 0.78 0.78

Verbal : 0.81 Performance : 0.68INF COM ARI SIM VOC DS PC SPA PA OA0.79 0.73 0.83 0.73 0.75 0.68 0.55 0.62 0.65 0.61

INF=Information, COM=Comprehension, ARI=Arithmetic, SIM=Similarities,VOC=Vocabulary, DS=Digit Symbol, PC=Picture Completion, SPA=Spatial,

PA=Picture Arrangement, OA=Object Assembly

Table 3.6: Alpha scores of MAB-II

is a course open to all age groups. The technical manual of MAB-II reports

internal consistency reliability for different age groups from 0.94 to 0.97 for the

Verbal Scale, 0.95 to 0.98 for the Performance Scale, and 0.96 to 0.98 for the Full

Scale. Another method of reliability reported here was Separately Timed Halves.

These were 0.92, 0,94, 0.95 for verbal, performance and full scale. The test-retest

reliability for Verbal Scale, Performance Scale, and Full-Scale scores were 0.95,

0.96, and 0.97, respectively. In correlation to the Wechsler Adult Intelligence

Scale WAIS-R, the scores were lower for performance scale. It was 0.79, whereas

the scores for verbal scale was 0.91 and the full scale was 0.93.

We also calculated the internal consistency of the intelligence scores of our sample.

We used Cronbach Alpha test (Table No. 3.6). It is one of several estimates of

the internal consistency of a test. It is the mean of all possible split-half reliability

(corrected for test length). The results were as follows:

Thus, it can be observed that the tool could be reliable for our sample, especially,

the verbal tool had a high alpha score.

Computer Attitude Scale (CAS): The other tool used for checking attitude

towards using computers was the Computer Attitude Scale (CAS). A Self-reporting

questionnaire reporting details of the use and skills of digital technologies was

developed, and a computer attitude scale was adapted from the Computer Attitude

Scale (CASS) that was initially developed by Jones and Clarke (1994). We also

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incorporated the modifications suggested by Smalley et al. (2001) in the tool. The

tool had three parts consisting of affective, cognitive and behavioural attitudes.

We only used the affective part questions as the

Computer Attitude Scale (CAS) had 15 items, as listed in Appendix A.

Attitude Alpha Score0.84

Table 3.7: Cronbach alpha results CAS

Learning and Study Strategies Inventory (LASSI)

Item Type First Round Second RoundAnxiety (ANX) 0.76 0.73Attitude (ATT) 0.81 0.78

Concentration (CON) 0.67 0.71Information Processing (INP) 0.69 0.73

Motivation (MOT) 0.71 0.72Selecting Main Ideas (SMI) 0.74 0.76

Self Testing (SFT) 0.65 0.67Test Strategies (TST) 0.61 0.64

Time Management (TMT) 0.76 0.76Using Academic Resources (UAR) 0.66 0.66

Table 3.8: Alpha scores of LASSI

Achievement Test: As discussed in Section 3.3.2.4, the achievement test were

shown to the experts and piloted on fifteen students for validity and practicality.

For testing the reliability of the achievement tests, we conducted the Cronbach

Alpha Test. The scores were reasonably high. The items were reliable. The

results of the Alpha Test were as follows:

Item Type Test 1 Test 2 Test 3 Test 4Objective 0.76 0.75 0.77 0.76

Short Answer 0.73 0.72 0.72 0.73Long Answer 0.72 0.74 0.72 0.71Total Alpha 0.76 0.76 0.77 0.75

Table 3.9: Alpha scores of achievement tests

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3.3.2.6 Equating the scores of achievement test

We used four different achievement tests. Though they were made on the basis of

the same blueprint as depicted in Table no. 3.5 but, they had different conditions

of administration. The question papers were from different papers. We were

comparing across academic sessions also. In order to equate the scores across

conditions, we used z-scores of the marks obtained by the students.

3.3.2.7 Delimitation

The experiment was conducted on the students of the Department of Education,

Patna Women’s College only.

The study was limited to finding the effect of the blended and online modes and

had not attempted to establish the causes of these effects.

3.3.3 Preparation for the experiment

For the preparation of the experiment, the following activities were conducted:

• Assessment of intelligence quotient of all the students

• Assessment of attitude towards ICT.

• Assessment of Learning strategies by administering LASSI.

• Formation of groups for study

• Preparation of Assessment Tools

• Validation of tools

• preparation of lesson plans

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Subjects Subject-1(S1) Subject-2(S2)Topics Topic 1 Topic 2

Sections Section A Section B Section A Section BGroups GA(10) GB(10) GC(10) GD(10) GA(10) GB(10) GC(10) GD(10)

Lesson 1-3 X1(BL) X2(OL) X0(CL) X0(CL) X0(CL) X0(CL) X1(BL) X2(OL)Evaluation Test-1(O) Test-2(O)Subjects Subject-3(S3) Subject-4(S4)Topics Topic 1 Topic 2

Sections Section A Section B Section A Section BGroups GA(10) GB(10) GC(10) GD(10) GA(10) GB(10) GC(10) GD(10)

Lesson 1-3 X2(OL) X1(BL) X0(CL) X0(CL) X0(CL) X0(CL) X2(OL) X1(BL)Evaluation Test-3(O) Test-4(O)

X=Intervention; O=ObservationGA, GB, GC and GD = Groups of students

BL=Blended Learning; OL=Online Learning; CL=Classroom Learning

Table 3.10: Schematic layout of the samples

• Preparation of Online Modules

A schematic layout of the groups is shown in Table 3.10 for conducting the research.

3.3.3.1 Development of the course

For maintaining the objectivity, the learning modules were prepared with the

objectives set for preparing the evaluation tool. Three lesson plans were prepared

for each of the topics.

A website based on the Learning Management System (LMS) MOODLE was cre-

ated (www.glocaledu.org/elearning) and used to develop content relating to the

study.

MOODLE is an acronym for “Modular Object-Oriented Dynamic Learning En-

vironment.“ MOODLE is a free and open-source learning management system

(LMS). Developed on pedagogical principles, MOODLE is used for blended learn-

ing, distance education, flipped classroom and other e-learning projects in schools,

universities, workplaces and other sectors. It provides facilities to create lessons,

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manage users and courses, and communication with teachers and among the stu-

dents. Students can use MOODLE to review their courses, submit assignments,

take various quiz, and interact forum.

As a learning management systems, MOODLE supports learning environments

and automates many of the administrative tasks relating to teaching and assess-

ment. It facilitates the students’ mastery of learning content and allows instructors

to prepare and deliver different learning modules in various formats. The LMS rep-

resented the online-supported element of the learning environment. with the study

guidance directing them to several other resources including texts, CD-ROMs, and

Web links, some of which were prescribed and some optional for study purposes

Moodle helps thousands of educational institutions around the world to provide

an interface for e-learning. The teachers can create and manage online class-

rooms, where students can learn using videos, documents, and by taking tests.

Course forums and chat allow two-way communication among students and with

the teacher. The core features of MOODLE are as follows:

• Modern, easy to use interface for novices

• Personalised Dashboard for students, instructors

• Collaborative tools and activities (with the teacher, among the learners)

• All-in-one calendar to display the upcoming activities

• Convenient file uploading and downloading

• Simple and intuitive text editor for course writers

• Easy to send notifications to the students

• Track progress-Educators and learners can track their progress and comple-

tion of courses with various options available for tracking individual activi-

ties.

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3.3.3.2 Content of the course

In this study, the content for designing e-learning modules was taken from four

papers. They were: Critical Understanding of ICT, Contemporary India and

Education, Learning and Teaching, and Assessment for Learning.

3.3.3.3 Time and place

The experiment was conducted at the Department of Education, Patna Women’s

College, Patna. This Department operates in a separate building, segregated from

the main college building. The Department runs a B.Ed. Course for preparing

teachers for secondary and senior secondary high schools. It is equipped with

appropriate institutional and infrastructural facilities as prescribed by NCTE. It

has a computer lab with Intranet and high speed leased line Internet facility. The

classrooms are equipped with projectors and sound system. The main classroom

is air-conditioned. Other classrooms have adequate light and airing. Besides

classrooms, there are other places like the multimedia room, smartclass room,

computer lab, e-library, library, and lounge for extra activities. The noise level in

the rooms is generally non-intrusive. A faint sound of traffic honks can be heard

in the classrooms. Sometimes they get a disturbing level of noise, like when the

traffic police use sound system to give instructions. Occasionally, some cultural

programmes are conducted in the neighbouring building of Carmel High School,

Patna that raises the noise level.

3.3.3.4 Statistical tools

Z-score, Correlation Test, t-test, ANOVA, and Cronbach Alpha were used for

different purposes of the research. The analysis was conducted using RStudio that

is a free and open-source integrated development environment (IDE) for Software

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R, version 3.4.4 (2018-03-15), named as ’Someone to Lean On’. R is a programming

language for statistical computing and graphics.

3.4 Description of the participants

As described earlier, the participants were matched on the basis of their intelligence

quotient (IQ). Figure 3.2 shows the Verbal IQ scores of the participants.

Figure 3.2: Verbal IQ scores across the groups

Another criteria for controlling the extraneous variable the participants was to

check their performance in Learning and Study Strategy Inventory (LASSI). The

range of scores in LASSI subscales are presented in Table No. 3.11. The LASSI

scores were reasonably similar. The scores of Computer Attitude Scale (CAS) is

given in Table 3.12. The CAS scores shows that all of the participants have a

score above 30.

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Item Type A1 A2 B1 B2 C1 C2 D1 D2ANX 12-20 14-21 13-20 13-22 12-20 12-21 12-18 14-19ATT 18-25 20-25 20-24 21-26 21-24 20-26 21-27 22-25CON 15-25 12-25 11-20 10-20 13-23 12-19 14-26 16-24INP 10-20 11-20 11-19 12-20 11-20 11-21 13-20 11-23MOT 8-19 12-17 11-20 12-19 13-18 13-20 12-19 12-19SMI 14-24 15-24 14-25 14-25 14-25 15-24 14-26 13-24SFT 08-15 07-15 09-14 09-15 10-15 10-14 10-14 11-16TST 15-27 16-26 15-24 15-27 15-25 15-24 14-25 14-23TMT 12-16 14-20 15-20 15-22 14-22 14-21 15-23 14-19UAR 10-15 10-16 11-19 13-20 14-20 15-20 13-20 15-20

*Highest score can be 30.

Table 3.11: Raw score* ranges of student’s response in LASSI

A1 A2 B1 B2 C1 C2 D1 D235-42 32-34 33-38 36-41 34-39 32-37 36-38 34-39

*Highest score can be 60.

Table 3.12: Score* ranges of CAS

3.5 Ethical concerns

Several ethical practices need to be observed in experimental studies. The fol-

lowing set of rules were followed by the researcher and all others involved in the

process:

1. Primary evaluation of the students like IQ, LASSI scores were not shared

with other students or other faculty members. All students were informed

that it would be used for research purposes only.

2. Precautionary measures were taken to avoid any adverse effect on the cur-

riculum transaction. No student was deprived of information for the benefit

of the research.

3. After the topic evaluation test, the online modules were made available to

all the students. No student was denied the opportunity to be benefited by

new technology and from experience an innovative mode of learning.

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3.6 Conclusion

To summarise the method of study, the study was visualised as an experimental

research with four groups across two sections of B.Ed students created on the basis

of their verbal IQ scores. A conceptual framework of the whole study is depicted

in Figure 3.3. To summarise, the various aspects of the study are as follows:

Objective One (O1): To identify an effective way of designing e-learning

and blended learning courses

Method used: Document-based study

Tool used: Analysis and Checklist

Objective two (O2): To identify challenges in designing and transaction

of the e-learning and blended learning courses

Method used: Heuristic

Tool used: Self-reflection and dialogue

Objective three (O3): To compare the effectiveness of two different

instructional modes

Method used: Experimental method (Impact study)

Tool used: Achievement Tests

Variables: Blended Learning Mode (IV), e-learning/Online Learning Mode (IV),

Face-to-face learning Mode (IV), Learning outcome in the form of achieve-

ment score (DV)

Statistical tool: t-test, effect size

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Objective four (O4): To compare the effectiveness of the two different

instructional modes of e-learning and blended learning across the

different subjects.


Tool used: Achievement Tests

Variables: S1 – Critical Understanding of ICT (IV), S2 – Contemporary India

and Education (IV), S3 – Learning and Teaching (IV), S4 – Assessment for

Learning (IV), Learning outcome in the form of achievement score (DV)

Statistical tool: ANOVA, Effect size

Objective five (O5): Correlation between IQ of the students of B.Ed.

and their achievement scores across different instructional modes.


Tool used: Achievement Tests, Multiple Aptitude Battery-II

Statistical tool: Correlation

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Figure 3.3: Conceptual framework of research

Chapter 4

E-learning and Blended Learning:

Designing and Challenges

One of the objectives of the study was to identify an effective design of e-learning

and blended learning courses (O1). To achieve the objective, the researcher sur-

veyed popular models of online and blended learning, and templates for designing

a lesson for online and blended learning was prepared.

4.1 Models exclusive for blended learning

In the course of time, the educational institutions have developed a number of

models to conduct teaching-learning in blended learning mode. Some of the most

common models used by educational institutions are discussed here.

67

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Chapter 4. Designing and Challenges 68

4.1.1 Face-to-face driver model

As declared in the name itself, this model emphasises the face-to-face part. This

model is closest to the face-to-face mode. In this model, all students do not par-

ticipate in online mode. Only those students who have problems in keeping pace

with their peers in the classroom (due to social, lingual or neurological disadvan-

tages) are looped through the online mode. They can rejoin the mainstream if

they feel that they are ready. It is also applicable to the other group of students

who are on the right side of the normal curve. Those students who need more

challenging conditions can also loop through the online mode to complement what

they learn in their classroom. This model is also good for those students whose

only problem is with the mode of instruction. They are not native to the language

in which the instruction is imparted. This model also serves to mitigate the effects

of absenteeism.

4.1.2 Rotation model

Rotation Model or Station Rotation Model is a model in which the students iterate

between stations of face-to-face and online mode facilities in a preplanned and fixed

schedule. All of the students either study online or spend time with their teacher

in face-to-face mode. Generally, followed at primary level, this model complements

face-to-face learning with activity-based online learning. By including the elements

of games and fun, it excites and motivates the kid learners. It can also be used by

higher-level learners.

4.1.3 Flex model

Just opposed to the face-to-face drive mode, the Flex Model is closer to the online

mode. In this approach, the learning is primarily provided through the online ma-

terial. The students have to visit a site with digital facilities even though they can

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access the content from anywhere. At the learning site, there are qualified teachers

available to provide support as needed, but, the students’ learning is self-guided

mostly. Students learn and practice a new concept in an online environment.

Teachers provide support to individual needs and lead small group works. This

model is useful for addressing the needs of students with behavioural, academic

and socioeconomic disadvantages.

4.1.4 Online lab model

Online Lab Model is nearest to online learning. In this model, students learn

entirely online, but they visit a dedicated computer lab to complete their course-

work. There are people who supervise the lab, However they are not qualified

teachers. The learners learn at their own pace. This model is useful for addressing

various conditions such as when the institution is lacking teachers, government ed-

ucational institutions which are waiting for teacher appointment for a long time.

This model ensures that the learners, especially the young learners, are spending

time with the learning material. This can also be useful in a situation when there

are not many students for a particular subject and resources are limited. This

model is also useful to address the special needs students, as the teachers relieved

of the excessive burden of delivering content can attend individual needs.

4.1.5 Online driver model

In contrast to the Face-to-face Driver Model, we have Online Driver Model. In this

model, students work remotely from any place. The learning content is delivered

through a learning management system. The learners can opt for face-to-face

check-ins. They can chat with teachers online to address their specific needs. This

model is useful for students who need more freedom and flexibility due to other

commitments in their daily schedules.

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4.2 Models for online and blended learning

In the beginning, the designing of online teaching-learning had only two influences:

there were designs replicated from classroom teaching, and there were designs

adapted from print or multimedia distance education courses. In the course of

time, several new designs emerged which were capable of exploiting the potentials

of online learning, but the primary forms also survived.

Online learning is a changing learning environment. In this environment, the focus

is slowly shifting from teaching methods to designing learning models. There are

seven popular models to design an online course:

1. Classroom type online learning

2. Massive open online courses (MOOCs)

3. ADDIE Model

4. Online collaborative learning

5. Community of Inquiry

6. Competency-based learning

7. Communities of practice

4.2.1 Classroom type online learning

Automatically recorded classrooms and flipped classrooms are two main forms of

this design. They primarily focus on serving the needs of revision, absentees, and

for better use of classroom time. An example of this model is MIT classroom

lectures recorded and made available through MIT’s OpenCourseWare. In an

advanced format of this model, Learning Management systems (LMS) like MOO-

DLE and Blackboard present more controlled management of learning. They have

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weekly units and modules for study selected by one or more instructors. They

also provide facilities of online discussions among the learners and also with the

instructors. Assessments in this model are almost at the same patterns as of the

face-to-face classrooms. Yet, there is scope for flexibility in the design of LMS

that can set them apart from the traditional classroom model.

Massive Open Online Courses (MOOCs) can also be considered as an advanced

format of classroom type online learning. But it contains a number of adaptations

over simple classroom records. Due to the variations in the epistemological per-

spectives, the MOOCs deserves a separate treatment as online course design. But

if the collaborative and interactive features are negated, the MOOCs are almost

like recorded classrooms only.

The merit of the classroom type design is that it gets assimilated well with the

traditional teaching practices. But, due to this reason, many of the commentators

consider it inadequate to meet the challenges of the digital age. Especially, it

is considered incapable of supporting higher-level learning. At the same time,

a simple imitation of the classroom, in the form of recordings, is inferior to the

actual classrooms at least for the less motivated learners. It may simply increase

cost without contributing anything significant.

CostBlend with Individua- Increased Increased Skills/Face-to-face lised Peer Teacher Tools

effective Mode Learning Interaction Interaction RequiredHigh level Only when Only when Recording with

High cost technical Difficult used in used in high video-of recording skills to and an LMS an LMS audio quality,equipment earmark Costly environ- environ- Using editingand editing video ment like ment like software,work hours minutes MOODLE MOODLE Managing

LMS/YouTube

Table 4.1: Evaluation of classroom type online learning

As it can be observed in Table 4.1, the classroom type online learning model

requires high cost of production of contents and individulised learning is difficult

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in this system. It also requires high level of skills from the teacher. It is not

suitable for learner-centric education.

4.2.2 Massive Open Online Courses (MOOCs)

In its most popular form, Massive Open and Online Course is a behaviourist

oriented information transmission model. The mode of teaching is mainly through

online short lectures in the form of recorded videos. It is combined with automated

online testing, and sometimes the peer assessment is also used (Bates and Bates,

2015). This initial form is known as “xMOOCs”. “This term was coined by Downes

(2012) for courses developed by Coursera, Udacity and edX” (Bates and Bates,

2015). There are other variations like cMOOCs (Connectivist MOOCs). Chauhan

(2014) has identified many other variations:

• BOOCs (Big open online course) – a mixture of xMOOC and a cMOOC;

• DOCCs (Distributed open collaborative course): In the example cited by

Chauhan (2014), seventeen universities were sharing and adapting the same

basic MOOC;

• LOOC (Little open online course): Chauhan (2014) suggests it to be a small

group of 15-20 tuition-paying campus-based students, such courses also allow

a limited number of non-registered students to also take the course, but also

paying a fee;

• MOORs (Massive open online research): This is a mixture of video-based

lecturers and student research projects guided by the instructors;

• SPOCs (Small, private, online courses): An example is from Harvard Law

School, where pre-selected 500 students from over 4,000 applicants take the

same video-delivered lectures as on-campus students enrolled at Harvard;

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• SMOCs: (Synchronous massive open online courses): These are live lectures

offered to campus-based students that are also available synchronously to

non-enrolled students for a fee.

The designs of different MOOCs vary. In general, xMOOCs have specially designed

platform software with video lectures. The students are evaluated by computer-

marked assignment and/or peer assessment. Extra supporting materials and a

space for discussion (forum) are provided to the participants, where they can

discuss with very light discussion moderation. Normally, the participants can

choose between a certificate for a price or free audit of the course. This system

is improving with a large amount of ’big data’ input from the learners, as each

of their behaviours with the courseware is recorded and is used as analysing and

getting a better understanding of the requirements and choices of the learners.

cMOOCs (Connectivist MOOCs) on the other hand was developed by three in-

structors of the University of Manitoba in 2008. cMOOCs have a very different

educational philosophy than xMOOCs. They place emphasis on networking and

contribution from the participants themselves. There may not be a formal in-

structor or formal assessment. The role of experts is to initiate the course and

give input as guest instructors occasionally.

The key design feature of cMOOCs is identified by Downes (2014) as the autonomy

of the learners which means that the learners choose what content or skills they

want to learn and there may be no formal curriculum. The second of the feature is

diversity. Diversity means variations in terms of tools used, variety of participants,

their knowledge level, and variety of content. Another feature is interactivity which

is in forms of cooperative learning. It provides ample scope for communication

among participants, and this interaction is the base of emerging knowledge among

the students. Transparency is maintained regarding access to information, content,

activities and assessment.

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The structure of cMOOCs is not predetermined. They evolve through the process

of interaction and discourse. Most of the MOOCs are not institutionally based or

supported. They may use shared programmes or social media. This means that

there may be thousands of participants contributing to a variety of media, and

It is impossible for individual participants to keep track of all of them. Another

problem is that though all the conversations are open, the participants can only

contribute if they know that a certain communication exists. There is no formal

assessment. The participants can seek feedback from knowledgeable participants.

The cMOOCs are network-based learning supporting autonomous learners. Online

platforms like Qura.com is one example.

The design of MOOCs is still evolving. Hence, there is some confusion about

the definition and goals of MOOCs. The new designs of MOOCs are contributed

by individual instructors. There may be a lack of consistency in terms of the

educational philosophy of designing the educational content. There are other

issues like why should there be a differentiation in the certification of on-campus

MOOCs students and MOOCs only students when they are learning the same

material.


effective Mode Learning Interaction Interaction RequiredLess Only when Only when Recording with

High cost flexibility Difficult used in used in high video-of recording if only and an LMS an LMS audio quality,equipment recorded Costly environ- environ- Using editingand editing class are ment like ment like software,work hours used MOODLE MOODLE Managing

LMS/YouTube

Table 4.2: Evaluation of MOOCs

As it can be observed in Table 4.2, the MOOCs requires high cost of production

of contents, and individulised learning is difficult in this system. It also requires

high level of skills from the teacher. It is not suitable for learner-centric education.

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4.2.3 The ADDIE model

ADDIE stands for five steps modelling and implementing of learning design. AD-

DIE is Analyse, Design, Develop, Implement, and Evaluate. In some variations,

it can be six or more steps also, for example, PADDIE with Planning as an extra

component. In the analyse phase, the variables like learner characteristics, learn-

ers’ prior knowledge, resources available, etc. are considered. Content designers

conduct activities like developing learner profile, identifying learning spaces and

devices, researching learning resources, and determining delivery and assessment

strategies.

In the Design stage, the learning objectives for the course and creation and de-

signing of material is decided. Decisions about the content and their format of

presentation (video, audio, text, audio-visuals) are taken at this stage. The selec-

tion of technology, such as LMS, video, or social media, is also done at this stage.

In summary, a blueprint of the whole course is made. Some ingredients to decide

about the design process are contact information, course objectives, attendance

policy, late work policy, course schedule, grading scale or rubrics, orientation aids

for students, communication practices, technology policy and course design.

The development stage includes identification of activities to fulfil the course objec-

tives, analysis of the textbook, content module development and content chunking,

the creation of new content, the development of learning objects, development of

tools for student assessment and additional resources to support learning.

The Implementation stage starts with the announcement of the course. In the

beginning, the instructor tries to know the learners. Ice-breaking sessions are used

to introduce learners to each other. The instructor may introduce the syllabus

and gives guidelines about the successful completion of the course. It is also the

time to set the tone of excellence by stringent evaluation of early assignments.

For a successful implementation of the course, a learning community should be

nurtured. The instructor should provide ample scope for communications among

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the learners and for the learner-instructor communication. Teaching the learner as

an individual is one of the most desired aims of the course. This can support the

other desired goal of creating emotion and belongingness among the learners. The

instructor should also facilitate the development of good social behaviour among

students for online and offline behaviour. For group activities, the instructor

should try to develop appropriately sized groups.

The evaluation is the last stage of the cycle of the ADDIE model, but it is advised

to keep getting feedback on each of the stages as far as possible. The instructor

should develop and implement the best practices for design, requirements for in-

teraction, and should attempt to measure the overall quality of the course. She

should keep a journal to record the performance of the different course components.

They should solicit feedback on course content and instruction from the students.

Finally, the ultimate aim of the assessment is to give the learners feedback on their

performance in the programme.

Thus, the ADDIE model guides the path of course development by analyzing

the course objectives and audience; designing and developing the materials and

activities; implementing the course materials and encouraging learning, and finally,

evaluating the effectiveness of the course.

ADDIE model is a very successful model. Observers attribute its success to the fac-

tors like good quality design, clear learning objectives, carefully structured content,

controlled workloads for faculty and students, integrated media, relevant student

activities, and assessment strongly tied to desired learning outcomes. The model

applies these on a thorough basis.

There are certain limitations of the ADDIE model:

• It is very good for large and complicated courses, but it may be expensive

and redundant for a small or traditional class.

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• It focuses heavily on content design and development but does not pay as

much attention to the interaction between instructors and students during

course delivery.

• It gives a structure of five stages but does not provide any guidelines about

the appropriate selection of action/items within those stages.

• The extensive application of ADDIE model results in a strong division of

labour. It may involve faculty members, instructional designers, editors,

web designers. It becomes costly and expensive.

• Due to the huge infrastructural, human resource requirements, this model

may not respond to rapidly developing new content, new technologies or

apps being launched on a daily basis, and to a constantly changing student

base.

Thus, the ADDIE model provides a good foundation for designing teaching and

learning, but it is a pre-determined, linear and inflexible model that may fail to

handle more volatile learning contexts.


effective Mode Learning Interaction Interaction RequiredPossible by acc- Planning

Not cost ounting previ- and managementeffective ous knowledge Possible if skills,for small flexible of learners adopted in Possible Pedagogicpart of a and providing the design knowledge,

traditional different learn- Managingcourses ing paths Online LMS

Table 4.3: Evaluation of ADDIE

As it can be observed in Table 4.3, the ADDIE model is not cost effective for small

courses. Though individulised learning is possible in this system, it requires high

level and varieties of skills from the teacher.

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4.2.4 Online collaborative learning(OCL)

Constructivist approaches to learning and the growing uses of the Internet has led

to the development of computer-mediated communication (CMC), or networked

learning. In a developed form, it is now called the online collaborative learning

theory (OCL). Harasim (2012, p. 90) describes OCL as a model of learning which

encourages to support the students to create knowledge together. They are invited

to invent, to explore the ways to innovate. During the process of exploration, they

seek the conceptual knowledge that is needed to solve problems. They are not

supposed to recite the right answers. In this theory, teachers play a key role in

linking the students to the knowledge community, or to state of the art in the

discipline they are working. Learning in this context is defined as conceptual

change rather than behavioural change. Thus the conceptual change becomes the

key to building new knowledge. In this model, the learning activities are designed

with reference to the norms of the discipline. It also follows a discourse process in

which the conceptual learning and knowledge building are emphasised.

According to Harasim (2012) OCL is developed by “integrating the theories of

cognitive development that focus on conversational learning (Pask, 1975), condi-

tions for deep learning (Marton and Saljo, 1997) (Entwistle, mber), development of

academic knowledge (Laurillard, 2001), and knowledge construction (Scardamalia

and Bereiter, 2006).

Harasim discussed three key phases of knowledge construction through discourse

Figure:4.1:

• idea-generating (IG): Participants do brainstorming to collect the divergent

thinking on given topics;

• idea organising (IO): Participants discuss and argue about the ideas gener-

ated in the previous phase. They compare, analyse, and categorise the new

ideas.;

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(Figure source: https://opentextbc.ca/teachinginadigitalage/wp-content/uploads/sites/29/2014/11/ Harasim-Figure-6.3.jpg)

Figure 4.1: Three phases of online collaborative learning

• intellectual convergence (IC): In this phase, the participants reach a level

of intellectual synthesis, understanding and consensus (including agreeing

to disagree). It is usually achieved through the joint construction of some

artefact or piece of work, such as an essay or assignment.

The key design principle of OCL is to make the discussion as a core activity and

supplement it with textbooks, videos and other things, not the other way round.

The participation in the discussion activities should become an intrinsic desire

among learners, not just a compulsion to fulfil the grade requirements.

As it can be observed in Table 4.4, the OCL model is cost effective. Individulised

and learner-centric education is possible in this system. It requires highly moti-

vated learners to conduct intense and meaningful discussion.

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effective Mode Learning Interaction Interaction RequiredIT skills

Yes if the Fit for Peer Matchingfree tools higher Yes Yes Yes Guiding

like Google level inherently inherently possible skills, workingDrive leaning knowledge of

are used Onlinesoftware

Table 4.4: Evaluation of OCL

4.2.5 Community of inquiry(CoI)

The Community of Inquiry (CoI) framework developed by Garrison et al. (2000). It

provides a framework that helps in addressing the challenges of online and blended

learning environments. Its elements are depicted in figure 4.2 They are named as

social presence, cognitive presence, and teaching presence. This framework is in-

spired by John Dewey’s philosophy. His approach to teaching and learning is

known as Collaborative-Constructivist Approach. The framework holds that an

educational experience is embedded within a community of inquiry that is com-

posed of teachers and students. The community is considered as essential for

supporting collaborative learning and discourse, providing higher levels of learn-

ing. As Garrison and Vaughan (2008, p 9) elaborates, the CoI is based on the

two ideas that are essential to a higher level of education: ‘community’ and ‘in-

quiry’. ‘Community’ recognizes the social nature of education. It stresses the role

of interaction, collaboration, and discourse in constructing knowledge. ‘Inquiry’

is the process of constructing meaning by the students through personal respon-

sibility and choice. Thus, cohesiveness and interactive community of learners are

two ingredients of COI. The purpose of COI is to “critically analyse, construct,

and confirm new knowledge.” The framework of COI provides a means to integrate

these elements and facilitate the designing for deep and meaningful educational

experiences.

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Figure 4.2: Community of Inquiry Framework

ELEMENTS CATEGORIES INDICATORS(examples only)

Social Presence Open communication Risk-free expressionGroup cohesion Encourage collaboration

Affective expression EmotionsCognitive Presence Triggering event Sense of puzzlement

Exploration Information exchangeIntegration Connecting ideasResolution Apply new ideas

Teaching Presence Design & organisation Setting curriculum & methodsFacilitating discourse Sharing personal meaning

Direct instruction Focusing discussion

Table 4.5: Elements of COI

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4.2.5.1 Social presence

The role of social presence in educational settings has been studied the most ex-

tensively, in both online and face-to-face course settings (Garrison and Arbaugh,

2007). Social presence is about the environment of social interaction among stu-

dents and teachers. The categories of social presence are open communication,

group cohesion and affective expression (See Table 4.5). As Garrison and Vaughan

(2008, p. 19–20) elaborates that for involving in the community of inquiry, the stu-

dents must be provided with an open and risk-free environment. They should be

able to develop personal relationships with other students. They must be able

to develop a sense of community so that they can make themselves commit to

pursuing the intended academic goals. This, in essence, means the development of

effective or personal relationship among the learners based on open communication

and cohesive response. Cohesiveness is an essential part for it can help the stu-

dent community to begin their work collaboratively. Open communication starts

a community of inquiry, and social cohesion sustains it. Thus, social presence

provides the cohesiveness needed for participation and focus. The learners should

be respected as individuals, but at the same time, they should feel responsible and

committed to the community of inquiry.

Besides social presence, cognitive presence is required for higher levels of learning,

purposeful discourse to collaboratively construct, critically reflect, and confirm

understanding.

4.2.5.2 Cognitive presence

Cognitive presence, in essence, represents the inquiry process. In this process, the

reflective and interactive processes are integrated. The cognitive presence has a

cyclical inquiry pattern in which learning starts from experience moving through

reflection and conceptualization to action and again move on to further experi-

ence. This is illustrated by the Practical Inquiry Model (see Figure 4.3). This

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model has two dimensions and four phases. The vertical axis defines the delibera-

tion–action dimension. This dimension represents the repetitive nature of inquiry

as representing both constructive and collaborative activities. The horizontal axis

represents the perception–conception dimension. This process constructs meaning

from experience. Although the dimensions are abstracted processes, the phases

of inquiry resemble more closely the educational experience. The first phase is

the triggering event, whereby an issue or problem is identified and defined. The

second phase is the exploration of the problem and the gathering and refinement

of relevant information. In the third phase, participants begin to reconcile and

make sense of the information. Solutions will be hypothesized and debated. In the

final phase, the preferred solution is applied and tested directly or vicariously. It

may trigger another cycle of inquiry if the solution is not satisfactory. Cognitive

presence is a recursive process that encompasses states of puzzlement, information

exchange, the connection of ideas, creation of concepts, and the testing of the vi-

ability of solutions, but not necessarily in a linear order. (Garrison and Vaughan,

2008)

4.2.5.3 Teaching presence

Teaching presence is the presence of an experienced facilitator. It is essential for

creating and sustaining a community of inquiry. It provides the design, facilita-

tion, and direction for a worthwhile educational experience. It ensures that the

community of Inquiry is productive. Teaching presence establishes the curriculum,

approaches, and methods; it also moderates, guides, and focuses on discourse and

tasks. It is the means by which to bring together social and cognitive presence in

an effective and efficient manner. From an online teaching effectiveness perspec-

tive, Conrad (2005) reports in her research that students stated simply that “Good

instructors created community, poor instructors didn’t” (p. 12). She also states

that the opportunity for face-to-face experiences can enhance connectedness and

satisfaction. Similarly, Garrison and Cleveland-Innes (2005) found that students

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Figure 4.3: The practical inquiry model

place much value on the time they expend in studying and expect that it has

a structure and leadership presumably of the teacher. In his research, Arbaugh

(2007) also found students perceive teaching presence as essential for their per-

ceived learning and satisfaction with the delivery medium. Finally, Dixon et al.

(2006) found that leadership was linked to student success. Thus, students per-

ceive a strong connection between a successful learning experience and teaching

presence. The unifying force of teaching presence is essential to create and sus-

tain a community of inquiry in a blended environment when students are shifting

between direct and mediated communication.

Blended learning is about fully engaging students in the educational process. It

provides students with a highly interactive succession of learning experiences that

lead to the resolution of an issue or problem. The provision of teaching presence is

challenged to shape cognitive and metacognitive processes and learning. Student

awareness of the inquiry process is crucial to complete the inquiry cycle and to

prevent stalling in the early phases. Metacognitive awareness must be a goal of

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higher education for students to monitor and manage their learning. Metacogni-

tion is the regulation of cognition, which includes self-appraisal (assessing what

needs to be done) and self-management (successfully carrying out the learning

task). Engaging in a higher-order learning experience requires that students have

some metacognitive understanding of the inquiry process if students are to learn

how to learn.

4.2.5.4 Evaluation of learning

Garrison and Cleveland-Innes (2005) states that higher educational outcomes are

very difficult to define and measure. He says that outcomes change as stu-

dents engage in the educational process and activities are modified. Garrison

and Cleveland-Innes quotes Burbules (2004) as, “Outcomes are constituted and

reconstituted in active processes of inquiry, not taken as static endpoints” (p.

7). Unfortunately, an obsession with educational outcomes has created a focus

on assimilating measurable, although trivial, information. Unintended learning

outcomes can be most educational. True inquiry is exploratory and often unpre-

dictable. Burbules (2004) goes on to say that the “question of educational quality

should be sought. . . in the reflexively critical and liberating activities of the class-

room itself” (p. 9). For this reason, practical inquiry is very much process-oriented.

4.2.5.5 Strengths and weaknesses of OCL and CoI

The OCL and CoI use a constructivist approach in computer-assisted learning.

They use technology to increase and facilitate communication among learners and

teachers. Their approach to learning is based on knowledge construction through

social discourse.

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They can help in creating deep and transformative learning as achieved by class-

room discussions. They also assist in developing critical thinking, analytical think-

ing, synthesis, and evaluation. These high-level intellectual skills are considered

significant for learners in a digital age.

These models require highly knowledgeable and skilled instructors. Another limi-

tation, as discussed by Bates and Bates (2015), is about epistemological positions.

He states that these models are “more likely to accommodate to the epistemolog-

ical positions of faculty and instructors in humanities, social sciences, education

and some areas of business studies and health and conversely it is likely to be

less accommodating to the epistemological positions of faculty in science, com-

puter science and engineering. However, if combined with a problem-based or

inquiry-based approach, it might have acceptance even in some of these subject

domains.”


effective Mode Learning Interaction Interaction RequiredIT skills

Peer MatchingFit for Yes Yes Yes Guiding skills

Yes blended Possible possible inherently Leadershipleaning Online

software

Table 4.6: Evaluation of COI

As it can be observed in Table 4.6, the COI model is cost effective. Individulised

and learner-centric education is designed as a part of the model. It does not require

too many skills. It is fit for blended learning and online learning environment.

4.2.6 Competency-based learning

Competency-based learning is a model that is based on identifying relevant specific

competencies or skills and support the learners to master them at their own pace.

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Learners work individually rather than in a group. They can do it just for learning

sake or for some form of certification.

Competency-based learning is a four-step model. The first step is to define the

competencies. These competencies can be in forms of overt or covert behaviour. In

the latter case, the competencies are defined in specific and measurable terms. A

course based on competency-based learning is designed in such a way that the later

competencies are built upon the earlier one. In other words, they are progressive.

They are also coherent as they all constitute a specific job-related ability.

Learner support or mentoring is a key part of the model. Sometimes subject

mentors and course mentors are separated to support the learning in a better way.

Student mentors are the main contracts for the students during the course. They

support students in determining the pace of learning and support them whenever

there is a problem. Course mentors are more highly qualified and provide extra

support to the students. Students can contact any of the mentors without any

restriction. The mentors are supposed to address their need within one business

day.

The fourth step is assessment. The students may have to give written papers,

portfolios, projects, observed student performance and computer-marked assign-

ments. They take both formative (pre-assessment) and summative (proctored)

exams. If a student fails, they are provided with feedback where they need to

work on their competencies. They can resubmit if required.

There are a number of strengths in the competency-based learning model. It is

very effective and convenient for working students and those with family commit-

ments. It supports the learners to learn at their own pace. It recognizes the prior

learning of the learner and cut short the curriculum accordingly. Students also get

individual support from their mentors.

There are certain limitations to this model. It is more focused on job orientated

teaching. So non-job specific learning is not convenient in this model. It is not

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suitable for the subject areas where it is difficult to identify specific competencies.

It is not suitable for a constructivist approach. It also ignores social learning.

It is also less effective for developing the higher-level skills requiring creativity,

high-level problem-solving and critical thinking.


effective Mode Learning Interaction Interaction Required

Yes, but Flexible Yes Yes IT skillsIndividual but fit for possible Yes inherent Guidingmentoring job inherent in design skillsis costly oriented Leadership

Table 4.7: Evaluation of CbL

As it can be observed in Table 4.7, the OCL model is cost effective but individual

mentoring is costly. Individulised and learner-centric education is possible in this

system. It does not require too many skills, but it is oriented towards job oriented

training.

4.2.7 Community of practice

The community of practice (CoP) is a model in which experiential learning, so-

cial constructivism, and connectivism can be combined. Wenger (2013) defines

Communities of practice as “groups of people who share a concern or a passion

for something they do and learn how to do it better as they interact regularly.”

Wenger identified three characteristics of a community of practice:

• domain: a common interest that connects and holds together the whole

community

• community: a group of people bound by the shared activities they pursue

(for example, meetings, discussions) around their common domain

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• practice: members of a community of practice are practitioners. Whatever

they do in the context of the common interest informs their participation in

the community, and whatever they learn from the community affects what

they do

The CoP is a self-organising system. It does not have a formal design. But in

the course of time, the researchers have identified a number of actions that helps

in creating a CoP based program. Wenger et al. (2002) have identified seven key

design principles to support a community of practice. They are as follows:

• Design for evolution: The community must have the flexibility to accommo-

date the interests of participants without going too far from the issues of

common interests.

• Dialogue between inside and outside perspective: New perspectives from

outside the community should be introduced and discussed on a regular

basis.

• Encourage and accept different levels of participation: Different levels of par-

ticipation should be allowed. For example, some of the participants are core

members; some others who participate regularly but do not contribute much;

still others who do not participate regularly but contribute significantly at

times.

• Develop both public and private community spaces: The participants should

be allowed to work in small private groups or if they want they can choose

to be more public by initiating general discussion for example by writing on

blogs or social media sites.

• Focus on value: The core values of the community should be emphasised

through feedback and discussions.

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• Combine familiarity and excitement: Besides the discussion on common con-

cerns and perspectives, radical and challenging perspectives have to be in-

troduced at times.

• Create a rhythm for the community: The community should follow a regu-

lar schedule of activities while considering the participants time and other

constraints.

Researchers also talk about the life cycle of the CoP. They emerge, they grow,

and they have life spans. Figure 4.4 depicts these phases. Initially, in the inquiry

phase, audience, purpose and vision for the community are identified. In the

design phase, the activities, group processes, technologies, and roles to support

the community’s goals are defined. In the third phase of the prototype, the key

stakeholders are identified, and they become committed to the purpose. With

this success in hand, the fourth stage of launch opens the community for a wider

audience. Proactive engagements are planned for the community members by

creating and increasing the cycle of participation and contribution. This makes

the fifth phase of development. The whole activities and inclusion of new blood

have to the community have to be maintained for a longer time to sustain it till

it gets institutionalised. That is the sixth phase.

The merit of CoP is that it connects people who are otherwise dispersed and dis-

connected. It provides them with a shared context and enables dialogue among

them. It stimulates learning and diffuses existing knowledge to widespread peo-

ple. It also introduces collaborative processes and helps people organise around

purposeful goals. Overall it generates new knowledge for them.

By nature, CoP is outside formal educational organisations, as the participants

are not looking forward to getting any kind of degree. Yet, it can be used as

informal study groups in formal Settings. In their design, they can be compared

to connectivist and constructivist MOOCs. One of the merit as well as demerit of

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Figure redesigned fromhttps://library.educause.edu//media/files/library/2005/1/nli0531-pdf.pdf

Figure 4.4: Life cycle of community of practice

this model is that there is no single right design for it. The specific needs of the

community guide its structure and development.


effective Mode Learning Interaction Interaction RequiredSoft skills

Fit for Possible IT skillsnon Yes Yes but High

Yes academic/ inherently inherently generally Emotionalself- not Quotient

motivated required requiredlearning Leadership

Table 4.8: Evaluation of COP

As it can be observed in Table 4.8, the COP model is cost effective, but it is fit

for non-academic and self-motivated learning. Individulised and learner-centric

education is possible in this system. It requires good communication skills.

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4.2.8 Summary of findings

We examined the structure and merits of various models of online and blended

learning. Some of them can be blended with a regular mode teacher education

course. They are cost-effective and promote interaction among the learners. Com-

munities of Inquiry (COI) model is more suitable for a formal set-up. Though

Competency-based Learning can be used for enhancing the skills of teaching-

learning, COI is suitable for philosophical, psychological, and sociological aspects

of the teacher education curriculum. It is cost-effective. It also promotes peer and

teacher interaction. It is not too demanding regarding the skills. Another merit

of this model is that it can be used for both blended and fully online mode of

teaching. A template for designing a blended learning course on the basis of the

Communities of Inquiry (COI) will be developed. Another template for designing

a fully online course will also be developed.

4.3 Designing online and blended courses

As discussed above, there are several course designing models of online and blended

learning available for creating online courses. They are related to differences in

epistemological perspectives, technologies in use, teaching methods, and objectives

of learning. There are certain criteria for deciding the effective model for teaching

in the conditions of this research. At the same time, it should be kept in mind

that designing a new blended course is different from designing an existing course.

An existing course has a set of predefined activities, assignments for the students.

Adopting them in online mode may not work always. It is always necessary to do

an analysis of preparedness of students for using the new feature, availability of

instructors to supervise the online activities.

There is a whole set of e-learning applications that have evolved to address the

training needs of the learner and to design an effective and good blended learning

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course. For an effective module of blended learning, the defining characteristics

are:

• to identify clear learning outcomes in terms of the subject matter or skill to

be mastered.

• the instructional method involves achieving the learning outcomes in a hier-

archical ‘bottom-up’ analysis of the domain of learning.

• the role for technology usually involves a simulation of a process and the

automatic presentation of problems or routines that have been carefully ar-

ranged by their level of difficulty

• assessment may be automated: both for progress through the stages of the

required mastery, and for summative performance measures.

Macdonald surveyed the current practice in blended learning in America. He

has identified three teaching and learning contexts in which blended learning was

introduced. (Macdonald, 2012)

• Courses for campus-based students: Formal support to the group

is traditionally delivered through face-to-face synchronous contact

for both content delivery, discussion or the practising of skills,

whether through lectures, seminars, tutorials or lab sessions. In

order to accommodate variations in study patterns imposed by

students’ work-based or other commitments, or the pressure from

growing student numbers or other constraints, course designers

have adopted online media as part of a blended strategy.

• Courses exclusively for distance students: Such students rely tra-

ditionally on an asynchronous study environment in which con-

tent is delivered through self-study materials, and tutor-mediated

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support takes place through correspondence tuition supplemented

with occasional face-to-face tutorials or telephone conversations.

• Courses for campus-based as well as distance students: The third

and final context is where courses cater for both campus-based

and distance students at the same time. The introduction of on-

line media within a blended strategy allows for the use of common

teaching materials for both campus and distance students, and a

common web-based interface can be deployed to link distance stu-

dents with those who were able to attend face-to-face classes or

to provide opportunities for collaborative study which had previ-

ously not been possible. At the same time, some have found that

certain campus-based students prefer the flexibility of distance

learning if given a choice.

Blended learning courses are not guaranteed success by themselves. There are

several things that have to be considered to conduct a successful blended learning

course.

4.3.1 Setting up objectives of the course

Planning is the first step for a successful implementation of blended learning. It

starts by defining course objectives.McGee and Reis (2012) suggest that “There is

a clear consensus that the best strategies for design begin by clearly defining course

objectives before coming up with course activities, assignments and assessments.

Course objectives are particularly critical for blended courses because objectives

can inform content delivery mechanism (in class or online), pedagogy (bridging

between the classroom and online activities), and the requisite amount and loca-

tions for class meetings and interactions” (p.12). It also helps to keep the needs

of learners in mind:

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• Learning content for the first time (new learning)

• Learning more about the subject (advanced learning)

• Applying the content that has been learned (application learning)

• Knowing what to do when things go wrong (problem-solving)

Content and learning activities that provide for ample practice must be introduced

into the course, as many researchers have shown that the one-size-fits-all approach

of teaching is not as productive as tailoring the course as per learners’ need.

4.3.2 Activities/strategy available for designing courses

Carman (2005, p.2) suggested five elements that were key ‘ingredients’ for design-

ing courses:

• Live events: These are synchronous, instructor-led events. Tradi-

tional lectures, video conferences, and synchronous chat sessions

such as Blackboard Collaborate or Adobe Connect are examples.

• Self-Paced Learning. Experiences the learner completes individ-

ually on her own time, such as an internet or CD-ROM based

tutorial.

• Collaboration. Learners communicate and create with others. E-

mail, threaded discussions, and wikis are all examples.

• Assessment. Measurements of whether or to what extent learn-

ing has taken place. Assessment is not limited to, conventional

tests, quizzes, and grades. Narrative feedback, portfolio evalu-

ations and, importantly, a designer’s reflection about a blended

learning environment’s effectiveness or usefulness are all forms of

assessment.

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• Support Materials. These include reference material, both phys-

ical and virtual, FAQ forums, summaries and anything that aids

learning retention and transfer.

4.3.3 Defining mode of control and roles of players

At each stage, control needs to be maintained from the beginning of the planning

stage to ensure desired results. It is assumed that a course design process is being

pursued that starts with learning objectives, and that includes a general outline

used to guide the development of the course, its delivery and evaluation. It is

important to determine the role of a teacher in the learning process. Whether

it will be primarily directive or facilitative? The need for and importance of

interaction amongst the students should also be determined.

The responsibility of the instructor is to design quality, appropriate, effective online

learning modules that support efficient and sustainable e-learning activity. The

instructor also has to provide appropriate feedback to the learners and devise

student activities. They also create learning resources and manage online and

offline interactions. Thus a whole new set of roles emerge for the teacher as the

facilitator of blended learning.

Teaching is the interaction of teachers with learners. It is not just the transmission

of new knowledge. The teacher needs to be reflective, thoughtful and self-critical

to develop the e-learning and blended learning courses. It is necessary to do a

need analysis of the learners to prepare the e-modules for pre-defined learners.

4.3.4 Using multimedia and design theories

The use of multimedia as a tool to promote knowledge transfer is the strongest

component of online education. Clark (2002) as cited by Carman (2005) has

mentioned three principles:

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1. The Multimedia Principle: Adding graphics to text can im-

prove Learning Research has shown that graphics can improve

learning. The key is to ensure that graphics relates directly to

the instructional message, that is, they “educate, not decorate.”

2. The Contiguity Principle: Placing text near graphics improves

learning In five out of five studies, multimedia researcher Richard

Mayer (cited in Clark (2002)) found that learning from screens

that integrated words near the visuals yielded an average improve-

ment of 68%.

3. The Modality Principle: Explaining graphics with audio improves

learning. Audio should be used in situations where overload is

likely. For example, if you are watching an animated five or six-

step software demonstration, you need to focus on the visual–the

animation. If you have to read the text and at the same time

watch the animation, overload is more likely than when you can

hear the animation being read to you.

4.4 Design effectively used in the study

In this study, the courses were designed for regular students studying in a face-

to-face mode as classified by Macdonald (2012). Rotation model was used for

the blended learning course. In this model, students iterate from classroom to

computer labs. They were introduced to a new topic in the classroom then moved

to the computer lab for exploring the answers to the questions they created in

the first phase. Again in another session, they came back to the classroom for

discussing their answers.

For designing courses for both of the modes, (blended and online), the components

of Community of Inquiry(CoI) Model were considered as the base.

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4.4.1 Planning lessons for blended learning

Based on the discussion above, a template for designing online and blended learn-

ing courses can be specified.

4.4.1.1 Initiating

Parallel to the introduction, this stage will invite learners to inquire about the topic

introduced by the teacher. But the teacher will not raise questions and expect the

learners to answer on the basis of their previous knowledge. The teacher will

present a video or an image or a story or any other interesting activity and expect

them to raise questions on the basis of their previous knowledge. He will scaffold

them to create a list of questions to explore the learning material.

In blended mode, this step will be conducted in the classroom. In online mode, it

will be available on the website.

4.4.1.2 Learning activity

Learning content distributed over several pages, along with images and external

video links will be given on the website for exploration and divided into small

sections. At the end of each section, questions for self-evaluation will be given.

4.4.1.3 Discussion

The online group of students will discuss the answers to the questions identified

during the first step in the online forum.

The blended learning group will discuss the answers to the questions identified

during the first step in the classroom.

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4.4.1.4 Evaluation

There will be two parts of the evaluation process. The first part will be continuous

and cumulative evaluation. In this section, a minimum score will be set for the

duration of online activity by the students. Their self-evaluation scores, as well as

their attempts to give a correct answer, will also be observed. This will ensure that

the student has used the online content as per the requirements of their respective

modes.

The second part will consist of two types of evaluation. One will be a creative

assignment on the topic, and the other will be a summative evaluation based on

a tool created by the researcher. The results of these two will be used for the

statistical analysis.

4.5 Template for lesson planning

For this study, the COI model was considered as the main design for designing the

lessons. As discussed above, the three elements of COI are complementary to each

other, but they are not separate events. They overlap when the learning event is

executed. The second element is the mode that is being used for the execution of

the event. They can be face-to-face or online. There are two options for online

interaction: synchronous and asynchronous. For synchronous interaction, the stu-

dents and instructor have to be present for an online discussion on the stipulated

time. It can be conducted through online instant messaging. The asynchronous

strategies have no such compulsion. The next element is strategies for conducting

the activity. They can be classroom-based or online. Next two elements are the

nature of execution and expected result of the event. In Table 4.9, a template for

blended mode teaching is depicted.

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Day

No.

Element

Mode

StrategyN

atureofExecution

ExpectedR

esult

Day

1

Generaldiscussion

Creation

ofgeneralrelating

tothe

opinion.Identification

Cognitive

PresenceFace-to-face

Classroom

topic,Open

andofelem

entsfor

SocialPresenceD

iscussionfearless

expression,discussion

byW

ithouthesitation

theteacher

Day

2

Discussion

ofbroaderAw

arenessof

contextofthe

issuebroader

contextsTeacher


Classroom

bythe

teacherofthe

contentC

ognitivePresence

Discussion

(social,technical,ofstudy

philosophical)

Day

3to

5

Brow

singofcourse

pages;Monitoring

Mastering

Cognitive

PresenceO

nlineProgram

med

ofonlineover

asynchronousLearning

activityby

teacherC

ontent(in

LMS

environment)

Day

3to

5

Interactionin

forum:

askingA

nalysingSocialPresence

Online

Forumquestions,

theTeacher

Presenceasynchronous

Discussion

sharingcontent

observations

Day

6

Generaldoubt

SocialPresenceclearing,R

aisingC

onsolidationTeacher


Classroom

questionsby

ofC

ognitivePresence

Discussion

teacher,Generalisation

knowledge

byteacher

Day

7

Assignm

entElaboration

Assignm

entby

thestudents

ofnewC

ognitivePresence

relatingto

ona

selectedknow

ledgetopic

topic

Table

4.9:B

lendedlearning

lessonplanning

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The design for online teaching is not sharply different for online learning. The

main differences are regarding the mode and strategies of the design. In online

mode, we used the parallel strategies we use in face-to-face mode. For example,

classroom discussions are substituted by forum discussion. The description of the

online design is depicted in Table 4.10.

4.6 Challenges of designing and transaction

An objective of the study (O2) was to identify the challenges in designing and

transaction of the e-learning and blended learning courses.

4.6.1 Challenges relating to technical requirements

The technical skills of the researchers and the participants of the study were the

primary level of challenge for the study. For the present study, MOODLE solved

most of the requirements listed below. But these are subjective requirements that

can vary across different researchers and participants:

• Online execution of the course should not be resource-intensive.

• It should not demand too many programming skills.

• Easy to use software for creating and managing Learning Management Soft-

ware (LMS) should be available.

• Adding and revising course content, for example, new announcements, adding

course information, uploading course documents, linking content to external

resources such as digital learning objects etc., should not be complicated.

• User management, for example, enrolling, listing, and removing students

into the course site and group areas can be conducted easily.

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Day

No.

Element

Mode

StrategyN

atureofExecution

ExpectedR

esult

Day

1

Generaldiscussion

Creation

ofgeneralrelating

tothe

opinion.Identification

Cognitive

PresenceO

nlineForum

topic,Open

andofelem

entsfor

SocialPresenceasynchronous

Discussion

fearlessexpression,

discussionby

Without

hesitationthe

teacher

Day

2

Discussion

ofbroaderAw

arenessof

Online

contextofthe

issuebroader

contextsTeacher

PresenceO

nlineForum

bythe

teacherofthe

contentC

ognitivePresence

asynchronousD

iscussion(social,technical,

ofstudyphilosophical)

Day

3to

5

Brow

singofcourse

Online

pages;Monitoring

Mastering

Cognitive

PresenceO

nlineProgram

med

ofonlineover

asynchronousLearning

activityby

teacherC

ontent(in

LMS

environment)

Day

3to

5

Interactionin

Online

forum:

askingA

nalysingSocialPresence

Online

Forumquestions,

theTeacher

Presenceasynchronous

Discussion

sharingcontent

observations

Day

6

Generaldoubt

SocialPresenceO

nlineclearing,R

aisingC

onsolidationTeacher

PresenceO

nlineForum

questionsby

ofC

ognitivePresence

asynchronousD

iscussionteacher,G

eneralisationknow

ledgeby

teacher

Day

7

Assignm

entElaboration

Assignm

entby

thestudents

ofnewC

ognitivePresence

relatingto

ona

selectedknow

ledgetopic

topic

Table

4.10:O

nlinelearning

lessonplanning

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• Tools relating to the course management, for example, communication and

collaboration features, digital dropbox, course calendar assessment feature

online testing and survey tools, online grade book and course statistics, site

design and functionality, adding and editing navigational buttons should also

be easy.

• The troubleshooting relating to the LMS should not be too demanding.

• Login and password problems should be easily traceable.

• There should be a system for directing students to proper support personnel

and/or resource documentation for hardware (computer), software (applica-

tions and plug-ins), and connectivity (Internet service provider) issues.

• Designing a course the technology has to be used with the purpose of making

learning interactive, dynamic and fun rather than to show off the technolo-

gies.

• Students should have the skills to access and operate the Internet and Inter-

net browser.

4.6.2 Challenges relating to learners

Over the years of experience with online learning, the researchers have identified

a number of features that identifies a potential student who can be successful in

online and blended learning. They are as follows:

• Students who are highly self-motivated and responsible.

• Students who prefer learning material on their own and do not function

optimally in a traditional lecture environment.

• Students who are highly resourceful and make regular use of online or face-

to-face tutoring and supports.

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• Students who are committed to learning and genuinely curious about the

subject.

• Students who have personal or professional obligations that limit the amount

of time they can spend on campus.

• Students who carefully utilize the basic skills support courses as needed.

They have also identified the features that are common among the students who

are not successful.

• Students who believe that taking a hybrid course will be easier and require

less time than taking a traditional lecture course.

• Students who are not self-motivated and have a tendency to procrastinate

often.

• Students who greatly struggle with learning math and would benefit more

from the regular one-on-one interaction of a traditional lecture course or the

Emporium mode.

• Students who are averse to technology, email, online learning, or social media.

• Students whose personal and professional commitments outside of school

would prevent them from devoting sufficient time to the class.

• Students who have previously struggled with learning math in an online or

hybrid mode of the offering.

4.6.3 Challenges relating the B.Ed. curriculum

Right at the beginning of the research, one of the biggest changes in the teaching of

education as a subject took place. The curriculum of education was converted from

one year B.Ed. to a two year B.Ed course. The new 2-year curriculum adopted

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by the teacher education institutions was based on a schematic structure imposed

by the NCTE. This curriculum had a number of new contents in comparison to

the old one-year curriculum.

The main papers were Childhood and Growing Up, Contemporary India and Edu-

cation, Learning and Teaching, Language Across the Curriculum, Understanding

Disciplines and Subjects, and Gender, School and Society for the first year. In the

second year, Knowledge and Curriculum, Knowledge and Curriculum, Assessment

for Learning, and Creating an Inclusive School are the main paper.

Pedagogy of a School Subject is divided over two years. Practice-in-school teaching,

along with other field experience, is increased to a total of 5 months with hope to

professionalise the course. Another set of papers named as Enhancing Professional

Capability(EPC) is introduced which has the papers Reading And Reflecting On

Texts, Drama And Art in Education, Critical Understanding of ICT, and Under-

standing the Self. The 2-year course has a total of 1300 marks divided equally

over two annual examinations. The ratio of external and internal examination is

930:370. The four papers of EPCs are for internal evaluation. Besides these, the

department has included research at the graduate level in its curriculum. The

department also had two add-on courses.

The new curriculum was an apt opportunity to introduce new teaching mode and

methods, but it was not easy to come by.

4.6.4 Challenges for new teaching-learning practices

Patna has over a century-old legacy of the teacher training programme, as one of

the first training colleges was established in Patna. Established in 1908, Patna

Training College is one of the oldest training colleges of India. Along with the

post-graduate department, it is the alma mater for many of the teaching profes-

sionals and teacher educators in the state. Over the period, a set of perceptions

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evolved among the teachers and the students about the transaction of B.Ed. and

other education programmes. These perceptions define the academic practices and

culture of the B.Ed. Colleges and departments. Some of the common perceptions

are as follows:

• B.Ed. Degree is a short duration course. This is a colloquial reference to

the insignificance of practice-in-school teaching for many students and even

teachers.

• It is a “training programme.”

• In this course, the teacher educators have to teach methodology; supporting

student’s mastery on subject content is not their responsibility.

• The training of students is mostly for teaching lecture method. Other teach-

ing strategies are taught theoretically as a part of pedagogy paper.

• There is a lot of new content in B.Ed curriculum that the learners are un-

exposed, but these contents have to be taught in a short period of time.

Mostly, the lecture method is used in the transaction of the B.Ed. Course.

Other teaching strategies are rarely used.

• A hurried theoretical discourse is followed by another set of hurried practical

activities in a short duration of time.

These perceptions developed during the one year B.Ed. programme was mostly

unchallenged in the new two-year programme. Many teachers doubt the rationality

of a 2-year B.Ed. course. In a study on Professionalism of teacher educators in

Bihar, only 59% were of the view that one year is the insufficient duration for the

B.Ed. course (Madhumita and Ranjan, 2014).

Besides these negative view about the duration, there were a number of apprehen-

sions at the beginning of the new course. The teachers were apprehensive about

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the new curriculum contents, as there were a number of new topics which needed

extra preparation time. Hence, a change in teaching practices for all the teachers

was not appreciable for many of the teachers.

Chapter 5

Data, Analysis and Interpretation

5.1 Description of collected data

A summary of the data used for the objectives O3 to O5 are presented.

5.1.1 Data relating to third and fifth objective

Data for analysis of third objective O3 and fifth objective O5 are described in Table

5.1, Table 5.2 and Table 5.3. For analysis, the scores of students were converted

into z-scores. The tables depict both actual scores out of 50 and their z-scores.

As described in Table no. 5.1 the mean age of all participants was 23. The age

range was 20 to 30. The mean of their achievement in the blended learning mode

was 35.5 with standard deviation of 4.3. The minimum and maximum marks

were 25 and 45 respectively. In e-learning (online learning) modules their average

achievement score was 31.6 with standard deviation of 4. The minimum and

109

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Chapter 5. Results and Discussion 110

Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max

Age 80 23.075 2.243 20 21.8 24 30Blended L. 80 35.538 4.305 25 32 39 45Blendedzs 80 0.928 0.851 −1.298 0.394 1.479 2.761e-Learning 80 31.613 4.092 23 28 34 43e-Learningzs 80 0.115 0.820 −2.170 −0.362 0.752 2.170face2face L1 80 28.663 4.231 21 25 32 36face2faceL1zs 80 −0.467 0.775 −1.836 −1.045 0.217 1.175face2face L2 80 28.188 3.732 21 25.8 31 39face2face2L2z 80 −0.576 0.714 −2.016 −1.037 −0.102 1.217VIQ 80 93.225 6.205 80 89 98 104vioz 80 −0.000 0.994 −2.201 −0.664 0.818 1.656PIQ 80 77.412 6.982 63 72 82 99SIQ 80 84.875 5.742 68 81 88.2 98

Table 5.1: Summary of results

maximum marks were 23 and 43 respectively. In the face-to-face mode, they got

a mean score of 28.1 with 21 and 39 as the maximum and minimum scores. Their

respective z-scores are given along them.

The summary of Verbal Intelligence Test is also depicted here. The mean value of

80 students was 93.2 with the SD value of 6.2. The highest and lowest values were

80 and 104. But their Performance IQ was low (77.4) and overall IQ was 84.9.

The scores for the groups of first-round are separately presented in Table no. 5.2.

The mean age of all participants was 22. The age range was 20 to 27. The mean of

their achievement in the blended learning mode was 36.7 with standard deviation

of 4.6. The minimum and maximum marks were 25 and 45 respectively. In e-

learning (online learning) modules their average achievement score was 32.9 with

standard deviation of 4.2. The minimum and maximum marks were 23 and 43

respectively. In the face-to-face mode, they got a mean score 28.1 with 21 and 32

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Age 40 22.450 1.724 20 21 23 27Blended L. 40 36.725 4.668 25 34.2 39.2 45Blended Lz 40 0.854 0.928 −1.298 0.322 1.467 2.761e-learning 40 32.975 4.288 23 31 36 43e-learningz 40 0.132 0.874 −2.170 −0.222 0.781 2.170face2face1 40 29.950 4.272 22 26 34 36face2face1z 40 −0.416 0.772 −1.836 −1.022 0.217 0.678face2face2 40 29.300 3.722 21 26.8 32 39face2face2z 40 −0.570 0.708 −2.016 −1.014 −0.191 1.217VIQ 40 93.325 6.514 81 88.8 99 104vioz 40 −0.000 1.000 −1.892 −0.702 0.871 1.639PIQ 40 76.225 5.798 63 72 80 91SIQ 40 84.225 5.176 68 81 86.2 95

Table 5.2: Summary of data first round

as the maximum and minimum scores. Their respective z-scores are given along

them.


the scores of 40 students was 93.3 with the SD value 6.5. The highest and lowest

values were 81 and 104. But their Performance IQ was low (76.2) and overall IQ

was 84.2.

The scores for the groups of second-round are separately presented in Table no.

5.3. The mean age of all participants was 23.7. The age range was 20 to 30. The

mean of their achievement in the blended learning mode was 34.3 with standard

deviation of 3.5. The minimum and maximum marks were 28 and 41 respectively.

In e-learning (online learning) modules their average achievement score was 30.25

with standard deviation of 3.4. The minimum and maximum marks were 23 and

36 respectively. In the face-to-face mode, they got a mean score 27 with 21 and 29

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Age 40 23.700 2.534 20 22 25 30Blended L. 40 34.350 3.585 28 31.8 37 41Blended Lz 40 1.002 0.772 −0.271 0.394 1.578 2.492e-Learning 40 30.250 3.425 23 28 33 36e-Learningz 40 0.099 0.773 −1.520 −0.373 0.653 1.394face2face1 40 27.375 3.821 21 25 31 36face2face1z 40 −0.519 0.783 −1.743 −1.062 0.095 1.175face2face2 40 27.075 3.437 21 24.8 29 35face2face2z 40 −0.582 0.728 −1.966 −1.038 −0.064 0.955VIQ 40 93.125 5.962 80 90 97.2 103viqz 40 −0.000 1.000 −2.201 −0.524 0.692 1.656PIQ 40 78.600 7.890 70 71.5 86 99SIQ 40 85.525 6.255 75 81 89.2 98

Table 5.3: Summary of data second round

as the maximum and minimum scores. Their respective z-scores are given along

them.


the scores of 40 students was 93.1 with the SD value 6.0. The highest and lowest

values were 80 and 103. But their Performance IQ was low (78.6) and overall IQ

was 85.5.

All scores and z-scores are depicted as bar diagrams in Figure no. 5.1. It can be

observed that they are normally distributed. It can the observed that the z-score

data that are used in the study were normally distributed.

5.1.2 Interpretation

As can be observed in the Tables 5.1, 5.2 and 5.3, the mean value of scores in

blended mode is higher than the mean values of e-learning and face-to-face modes.

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Figure 5.1: Distribution of data

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This was consistent through the two rounds. It can also be seen that the verbal IQ

was higher than the performance IQ and it also confirms the normal distribution.

5.1.3 Data relating to fourth objective

Distribution of data relating to fourth objective O4 is depicted in Table no. 5.4.

to Table no. 5.6.


s1bl 20 35.750 3.567 29 33 37.2 43s2bl 20 35.650 4.557 25 32 39 41s3bl 20 34.350 5.224 27 30.8 39 45s4bl 20 36.400 3.733 29 34 39 43

Table 5.4: Blended learning mode scores across subjects

As depicted in Table no. 5.4, the mean of the achievement of students in Subject

One taught in blended learning mode was 35.7 with standard deviation of 3.6.

The minimum and maximum marks were 29 and 43 respectively. The mean of

the achievement of students in Subject two taught in blended learning mode was

35.65 with standard deviation of 4.6. The minimum and maximum marks were 25

and 41 respectively. The mean of the achievement of students in Subject Three

taught in blended learning mode was 35.3 with standard deviation of 5.2. The

minimum and maximum marks were 27 and 45 respectively. The mean of the

achievement of students in Subject Four taught in blended learning mode was


and 43 respectively.

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s1ol 20 31.650 5.029 23 27.8 34.2 43s2ol 20 32.550 2.781 27 31 34 38s3ol 20 30.700 4.181 23 28 34.2 39s4ol 20 31.550 4.161 25 28 34.2 39

Table 5.5: Elearning mode scores across subjects

As depicted in n Table no. 5.5, the mean of the achievement of students in

Subject One taught in e-learning mode was 31.6 with standard deviation of

5.6. The minimum and maximum marks were 29 and 43 respectively. The mean

of the achievement of students in Subject two taught in e-learning mode was


and 38 respectively. The mean of the achievement of students in Subject Three

taught in e-learning mode was 30.7 with standard deviation of 4.1. The minimum

and maximum marks were 23 and 39 respectively. The mean of the achievement

of students in Subject Four taught in e-learning mode was 31.5 with standard



sub1 40 30.125 3.797 22 27 33 36sub2 40 27.450 4.489 21 24 30.2 39sub3 40 29.200 3.844 22 26 32.2 36sub4 40 26.925 2.912 22 25 29 34

Table 5.6: Face-to-face mode score across subjects

As depicted in n Table no. 5.6 the mean of the achievement of students in Subject

One taught in face-to-face mode was 29.0 with standard deviation of 4.0. The

minimum and maximum marks were 22 and 36 respectively. The mean of the

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achievement of students in Subject two taught in face-to-face mode was 29.9

with standard deviation of 3.4. The minimum and maximum marks were 21 and

32 respectively. The mean of the achievement of students in Subject Three taught

in face-to-face mode was 27.7 with standard deviation of 3.7. The minimum and

maximum marks were 22 and 35 respectively. The mean of the achievement of

students in Subject Four taught in face-to-face mode was 26.2 with standard



Table no. 5.4, 5.5 and 5.6 the mean values are almost identical for all the subjects

taught under blended mode, e-learning mode and face-to-face mode. The variation

is also consistent.

5.2 Results of the third objective

For testing the hypothesis H01 a paired t-test was used.

The standardized achievement scores of students in blended mode (M = 0.93, SD

= 0.85) were higher than their achievement in face-to-face mode (M=−0.58, SD

= 0.71), t(72) = 16.69, p-value = 0. The effect size (Hedges’ g ) was 1.93.

The result was consistent through the two stages, the first round sample and the

second round sample as described below.

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The standardized achievement scores of students of first-round in blended mode

(M = 0.85, SD = 0.93) were higher than their achievement in face-to-face mode

(M=−0.57, SD = 0.71), t(36) = 12.01, p-value = 0. The effect size was 1.72.

The standardized achievement scores of students second-round sample in blended

mode (M = 1.0, SD = 0.77) were higher than their achievement in face-to-face

mode (M=−0.58, SD = 0.73), t(36) = 11.64, p-value = 0. The effect size was 2.12.


The standardized achievement scores of students in e-learning mode (M = 0.115,

SD = 0.82) were higher than their achievement in face-to-face mode (M=−0.58,

SD = 0.71), t(72) = 11.66, p-value = 0. The effect size was 0.91.

As can be observed, The result was consistent through the two stages.

The standardized achievement scores of students of first round in e-learning mode

(M = 0.13, SD = 0.87) were higher than their achievement in face-to-face mode

(M=−0.57, SD = 0.71), t(36) = 8.98 p-value = 0. The effect size was 0.88.

The standardized achievement scores of students in second round in e-learning

mode (M = 0.09, SD = 0.77) were higher than their achievement in face-to-face

mode (M=−0.58, SD = 0.77), t(36) = 7.55, p-value = 0. The effect size was 0.87.


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The standardized achievement scores of students in blended mode (M = 0.93, SD

= 0.85) were higher than their achievement in e-learning mode (M = 0.115, SD =

0.82), t(72) = 8.50, p-value = 0. The effect size was 0.98.

As can be observed, The result was consistent through the two stages.

The standardized achievement scores of students of first round in blended mode

(M = 0.85, SD = 0.93) were higher than their achievement in e-learning mode

(M= 0.13, SD = 0.87), t(36) = 5.52 p-value = 0. The effect size was 0.80.

The standardized achievement scores of students of second round in blended mode

(M = 1.0, SD = 0.77) were higher than their achievement in e-learning mode (M=

0.10, SD = 0.77), t(36) = 6.47, p-value = 0. The effect size was 1.17.

The results are summarised in the Table 5.7

Mean* S.D.* df t-value p-value Effect Size

Blended Mode 0.93 0.85 72 16.69 0 1.93Face-to-Face Mode −0.58 0.71

e-learning Mode 0.115 0.82 72 11.66 0 0.91Face-to-Face Mode −0.58 0.71

Blended Mode 0.93 0.85 72 8.5 0 0.98e-learning Mode 0.115 0.82

Table 5.7: Summary of findings of of the third objective (*based on z-scores)


As can be observed from Table 5.7, the mean of scores (z-scores) in blended learn-

ing mode was higher than the scores in face-to-face mode. The difference was very

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high and the t-value is 16.7. In terms of magnitude it was almost two standard de-

viation bigger. It clearly established the superiority of blended mode for the group.

Similarly, the mean of scores in e-learning mode was higher than face-to-face mode.

The t-value was high and the effect size was almost one standard deviation bigger

in magnitude. When directly comparing the blended and e-learning modes, the

mean of blended mode was bigger. T-value was high with a magnitude difference

of almost one standard deviation. Thus, the superiority of blended learning was

undoubtedly established.

5.3 Results of the fourth objective

A one-way ANOVA was conducted to compare the effectiveness of blended mode

across the four subjects. Normality checks and Levene’s test were carried out

and the assumptions met. There was no significant difference in mean scores of

students across the subjects [F(3,76)= 0, p = 1]. Hence, no further analysis was

carried out.

4 subjects Blended Mode E-learning Face-to-faceF-value 0 0 0.538p-value 1 1 0.62

df(between, within) (3, 76) (3, 76) (3, 156)Result Rejected Rejected Rejected

Table 5.8: ANOVA result of subject-wise comparison

A one-way ANOVA was conducted to compare the effectiveness of e-learning mode

across the four subjects. Normality checks and Levene’s test were carried out and

the assumptions met. There was no significant difference among mean scores of the

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students across the four subjects [F(3,76)= 0, p = 1]. Hence, no further analysis

was carried out.

A one-way ANOVA was conducted to compare the effectiveness of face-to-face

mode across the four subjects. Normality checks and Levene’s test were carried

out and the assumptions met. There was no significant difference among mean

scores of students across the four subjects [F(3,156)= 0, p = 0.62]. Hence, no

further analysis was carried out.


As can be observed in Table 5.8, F scores were too low and no difference could be

detected across subjects for scores in blended mode. For the e-learning mode and

face-to-face modes, the results were similar. It established the consistency of the

different modes across different subjects.

5.4 Results of the fifth objective

As per the objective O5, a correlation test was conducted. As depicted in Fig-

ure 5.2, there was a moderate correlation (0.36) between the student’s scores in

blended learning mode and their Verbal Intelligence Quotient (at 0.01 level). The

correlation was lower for Sum of Intelligence Quotients (including both verbal and

non-verbal). They were not significant for other pairs.

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Figure 5.2: Correlation matrix

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The verbal intelligence test of MAB-II consists of testing information about diverse

topics, comprehension of social situation to identify socially desirable behaviour,

arithmetic for reasoning and problem solving abilities, similarities for conceptu-

alising and rank likeness and differences, and vocabulary for verbal concepts and

individual’s openness towards new information. A significant correlation between

verbal intelligence and scores of blended learning mode may be an indication of

influencing these abilities.

5.5 Conclusion

In our study, we found that in general, there was a significant but low level cor-

relation between achievement scores and IQ. But in blended mode the correlation

coefficients were high. In this mode, the learners got more chance to reflect on their

own learning and were allowed to study at their own pace. This has positively in-

fluenced their achievement scores. Similarly, we found significant differences when

we compared the scores of blended group with the face-to-face group of students.

We found that the blended group over-performed over the face-to-face group of

students by approximately one standard deviation magnitude.

Chapter 6

Findings, Conclusion and

Implication

6.1 Findings and discussion

6.1.1 Effective design for e-learning/blended learning courses

The first objective (O1) of the study was to identify an effective design for e-

learning and blended learning courses.

In this study, the structure and merits of various models of online and blended

learning were examined. It was found that some of them can blend with a regular

mode teacher education course. They are cost-effective and promote interaction

among the learners.

We found that Communities of Inquiry (COI) model was more suitable for a formal

set-up. COI is ideal for teaching philosophical, psychological, and sociological

123

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Chapter 6. Conclusion, Limitation and Implication 124

aspects of the teacher education curriculum. It is cost-effective. It also promotes

among-peers and student-teacher interaction. It is not too demanding regarding

technological skills. Another merit of this model is that it can be used for both

blended and fully online mode of teaching. It also helped in creating a template

for lesson planning in e-learning and blended mode.

6.1.2 Challenges in designing and transaction of e-learning

and blended learning

An objective of the study (O2) was to identify the challenges in designing and

transaction of the e-learning and blended learning courses.

The technical skills of the researchers and the participants of the study were the

primary level of challenge for the study. The second significant challenge comes

from the motivational and attitudinal aspects of the learners towards an online

course. Some of them do not want to explore the full potential of online learning

as a support system.

Over time, the convenience of teaching in the traditional method has taken over

both teachers and students. It puts low demand for efforts on both learners and

teacher. The examination result rather than learning attainment is the only end

they need to work for.

The study also considers that designing a new blended course is different from

designing an existing course. An old course has a set of predefined activities,

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assignments for the students. Adopting them in online mode may not work always.

It is always necessary to do an analysis of preparedness of students for using the

new feature, availability of instructors to supervise the online activities.

There is a whole set of e-learning applications that have evolved to address the

training needs of the learner.

In this study, the courses were designed for regular students studying in the face-

to-face mode as classified by Macdonald (2012). Rotation model was used for

the blended learning course. In this model, students iterate from classroom to

computer labs. They were introduced to a new topic in the classroom then moved

to the computer lab for exploring the answers to the questions they created in

the first phase. Again in another session, they came back to the classroom for

discussing their answers.

6.1.3 Effectiveness of blended learning and e-learning

As discussed in Chapter 1 the hypotheses for the objective O3 were:


while learning in blended mode and face-to-face mode.


The standardized achievement scores of students in blended mode (M =

0.93, SD = 0.85) were higher than their achievement in face-to-face mode

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(M=−0.58, SD = 0.71), t(72) = 16.69, p-value = 0. The effect size (Hedges’

g ) was 1.93.


while learning in e-learning mode and face-to-face mode.


The standardized achievement scores of students in e-learning mode (M =

0.115, SD = 0.82) were higher than their achievement in face-to-face mode

(M=−0.58, SD = 0.71), t(72) = 11.66, p-value = 0. The effect size was 0.91.

H03 There is no significant difference between the student’s learning achievement

while learning in e-learning mode and blended Learning mode.


The standardized achievement scores of students in blended mode (M =

0.93, SD = 0.85) were higher than their achievement in e-learning mode (M

= 0.115, SD = 0.82), t(72) = 8.50, p-value = 0. The effect size was 0.98.

6.1.3.1 Discussion

As compared to Table no. 2.3, depicting the list of studies on online learning,

the most substantial effect was observed by Schoenfeld-Tacher et al. (2001) who

found an effect size of 0.8, Beyea et al. (2008) who found an effect size of 0.790,

Zhang et al. (2006) who found an effect size of 0.498, the effect size found in the

present study is large. Many others found a positive effect size varying between

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+0.028 and +0.381. If we look at the upper limit of the confidence interval of these

studies, they range from 0.209 to 1.756. These studies also showed a possibility

for a higher score. But the main reason for a lower score in the Indian context is

a poor learning habit of students learning under face-to-face mode.

In a study about the impact of blended learning and traditional teaching among

students in the first year of the Biology on academic performance and the degree

of user satisfaction, Pereira et al. (2007)also observed that blended learning was

more effective than traditional teaching for teaching human anatomy.

The findings in the context of blended learning were also similar. As depicted in

Table No. 2, Day et al. (1998) found an effect size of +1.113. El-Deghaidy and

Nouby (2008) found an effect size of +1.049; Schilling et al. (2006) found an effect

size of +0.926 against the face-to-face learning. Al-Jarf (2004) found an effect

size of +0.740; Aberson et al. (2003) found an effect size of +580. Others varied

between +0.110 and +0.571. The finding of the present study suggested an effect

size of around two sigma scores. The upper limit of the results mentioned in Table

No. 2 was varied between 0.468 and 1.845 on the positive side. Hence the findings

of the present study were consistent with the literature.

6.1.4 Effectiveness of learning modes across subjects

As discussed in Chapter 1, Hypotheses relating to O4 were:

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dents across different subjects taught in blended learning mode.


dents across different subjects taught in e-learning mode.


dents across different subjects taught in face-to-face mode.

The results of three one-way ANOVA test showed that there were no differences

in the effectiveness of any of the modes across the four subjects. It is similar to

the reported research by Means et al. (2010) who have not found a remarkable

difference in effect size when comparing different subjects. Their conclusion is

based on 50 studies.

6.1.4.1 Discussion

There is a dearth of comparative studies regarding the effectiveness of e-learning

for different subjects. There is a general understanding that any subject can be

taught in an effective way in online mode if properly designed. The teaching of

four different papers of teacher education in e-learning and blended learning modes

for the study show that they were equally effective.

There were some inconclusive references in the research literature about the differ-

ences in the effectiveness of blended and online learning across different subjects.

In this study, four subjects used for the experiment were Critical Understanding of

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ICT, Contemporary India and Education, Learning and Teaching, and Assessment

for Learning. The portions chosen for teaching were well-defined content.

The main purpose of our study was to check the consistency of modes across

different subjects. It was found that the modes were consistent across different

subjects.

6.1.5 Relation between IQ and achievement

H07 There is no significant relation between IQ of the students of B.Ed. and their


The first objective was to find out the relationship between the general mental

ability of the students defined by their IQ scores and their achievement scores in

different modes of learning. In our study, we found that there was a low-level

correlation between the IQ scores and achievement scores in general, but it got

enhanced when learners got chance to reflect on their learning and were allowed

to study on their own pace in blended mode.

6.1.5.1 Discussion

In the research literature, there had not been a strong correlation between the

IQ and achievement scores. It was found that a more robust relationship existed

between IQ and working memory. It is interesting that in this study, a correlation

was identified only for a blended learning mode. Nevertheless, we cannot read too

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much about this result. More data would be needed to make any assertion like

“blended learning helps better utilisation of IQ.”

The results were in consistence with various other research. As Jensen (1998)

observed that even though the methodologies, data collection techniques, and

variables included in the studies have differences, they indicate that intelligence

and achievement are highly correlated.

In a similar study, Kaya et al. (2015) have observed that several researchers demon-

strated the relationship between intelligence and achievement with evidence that

students with higher IQ scores show significantly greater academic progress than

those with lower IQ scores.

6.2 Towards generalisation

This study was grounded in two theoretical premises: Learner-centric approach

and the Media Debate. The somewhat success of blended learning observed in

this study owes its success to the learner’s freedom to inquire and explore. The

learner-centric approach has been successful in a lot of other contexts. The merit

of blended learning and online learning is in the fact that they grant some control

over time and place to the students to explore the learning content.

Regarding the Media Debate, this study, taking a cue from the literature about

using extra media, did not employ resource-intensive media like videos. The

main media used online were text, images and diagrams. These contents, coming

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through the Internet, were another form of media as they can be accessed through

different devices anytime, anywhere.

In the context of Clark-Kozma Debate, this study supports Kozma’s stand that

the relation between media and education should be explored. In the context of

education, the strength of the Internet as a medium is in its continuous availability

of the content and accessibility to a larger group (of peer and instructor) for

discussion. This social nature puts the Internet apart from other technologies.

These aspects help the students who need more time to learn as well as the students

who want to advance their learning.

With a post-positivist perspective of including the views of the participant, a

statement by one participant reflects on the merits of the blended learning and

e-learning:

“This system (blended and e-learning) keeps us on our toes all the time with so

many tests, (sic) it is not good. Earlier, we have to take notes only. In the old

system, we divide the syllabus portions among 3 to 4 girls and prepare notes to

share among ourselves. In this new system, everyone has to do all the things. Also,

there is no privacy, if I observe something new and write it in the forum or share

in the class, everyone else is listening and copying. How will I mark my difference

in the examination when everyone else is writing my things in the examination.”

The statement was an ethical commentary on blended and online learning systems.

It underlines both the merits of blended learning/e-learning and demerit of the

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examination system. It is more engaging than the face-to-face system, and at the

same time, there are problems if we try to fit it in the old system of evaluation.

It needs continuous or process-based assessment.

This study helps us to understand the potentials of blended learning and e-learning

to address a number of challenges that face-to-face mode, as well as distance ed-

ucation, were facing. The issues of inclusion and learner-centric education were

the most burning issues for the education system, which was predominantly con-

ducted in face-to-face mode. The distance learning mode also had severe problems

of the lack of means to monitor the learning activities and of lack of ways to create

opportunities for dialogues among the learners as well as with the instructor.

Learner-centric education and inclusion have been adopted as the guiding princi-

ples of modern Indian education (NCERT, 2005). It has put enormous pressure

on our educational system, which can be met out through the blended learning

mode of education. Blended learning lends itself to learner-centred, teacher-guided

(as opposed to teacher-directed), interactive, and student-collaborative learning.

There are some serious efforts by the top institutions of India to boost and exem-

plify the e-learning. More and more educational institutions are becoming ICT

enabled. But as it can be argued through this research that this is not sufficient to

equip the institutions with the IT equipment. The teachers have to be reoriented

for new strategies and roles. They also need to learn the art of blending.

This study noted the structure, functions and limitations of different online and

blended models. But these models are products of western academic cultures that

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have integrated ICT into their regular practices. In Indian conditions, the expan-

sion of ICT is yet to influence mainstream educational practices in a serious way.

The work culture of educational institutions is yet to consider digital technologies

as a reliable partner in transacting new knowledge. The students too are only

slowly turning to the ICT for addressing the gaps in their learning. The attempts

by governments have resulted in only Classroom type and MOOCs. They are far

from reaping the full potential the technologies. For a better result, the faculty

have to come forward and take the initiative to change the pattern of teaching-

learning practices. Content management systems like Wordpress and learning

management system like MOODLE are very user-friendly. They are intuitive, and

teaching faculty can use them without much effort.

6.2.1 Limitation

The study had some limitations that may constrict the scope of generalisation of

study. They are outlined below:

• In the study, the asynchronous online interaction (in the form of forum

discussion), was not as effectively implemented. It was meant to be a kind

of supplement parallel to teacher intervention in face-to-face mode. Rather

than the forum, many of them discussed it on their personal WhatsApp

platform.

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• The duration of using the online content was recorded by MOODLE and was

originally planned as a component for process evaluation but, it could not be

used as many students used screenshots or copy-paste content in the word

files. Each of the participants was not equally habituated to read from the

computer/mobile screen. A few of them claimed that they have problems

reading onscreen for long hours, though they can watch a movie on their

mobiles.

• For the purpose of optimising the differences, the face-to-face mode was lim-

ited to lecture and discussion only (as it was the control group for the study).

This is a limitation to consider the differences from face-to-face learning with

blended and online learning as independent and separate results.

6.3 Implications and suggestions for new learn-

ing modes

This study underlines the significance of Blended learning which plays an essential

role in improvising the effectiveness and efficiency of students’ learning process in

higher education institutions. India has recently arisen to the possibilities where

good teachers can share their skills across a vast number of learners. It is crucial

to understand how the new mode can fit in the regular teaching-learning practices.

There are many areas where the insights gained in the study can be applied.

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• The blended learning can address the problem of formal education related

to lack of individual support by extending the scope of teacher-student in-

teraction beyond the classroom.

• If properly designed, it can de-escalate the learner’s over-emphasised con-

cerns relating to examinations.

• With the push for universalisation of education at elementary, secondary and

tertiary levels, diversity of learners are increasing. The online and blended

learning can increase the support system for diverse need students with in-

creased exposure time and with the help of assistive technologies.

• The technologies supporting blended learning can be used for experimenting

with new education delivery modes.

There are some of the observations and experiences to share with different stake-

holders:

6.3.1 Suggestions for teachers

Teachers interested in running a blended course should consider the following

suggestions:

• Learning through a blended mode of learning can be made more effective only

when there is a rational combination of the online and face-to-face mode of

learning. The rational combination means that content has to be judged by

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their merit. One must have the answer to the question, how is it beneficial

if the particular part is put online.

• Teachers should learn to use different teaching strategies to make teaching-

learning more effective. They should take care that the strategies that give

students control over time, path, place and pace should be preferred.

• It is also important to understand that simply putting the slides, video etc.

online would not allow you the monitoring, which is important.

• The teacher should acquire the technical know-how of running an LMS as

much as possible.

6.3.2 Suggestions for students

The students should also be proactive for the success of the system. They should:

• not be shy and participate in discussion whole heartily.

• provide frequent feedback regarding whatever good experience they have and

also about the problems. They should take the initiative if the feedback is

not solicited.

• try to do activities and readings suggested in the content honestly.

• provide technical or otherwise support to their peers when needed.

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6.3.3 Suggestions for policymakers

India has recently started MOOCs through SWAYAM portal. UGC has decided

that the students will be allowed to substitute parts of their regular courses with

the MOOCs, which will be evaluated by the National Testing Agency (NTA). It

is advisable to train the teachers to blended these courses with their teaching

for better results. Only online learning and computerised summative testing will

promote the original problem of rote learning.

6.4 Scope for further study

The study can be extended in the following contexts:

• The study should be extended to other disciplines of higher education.

• The retention of learned content should also be included in the investigation

of effectiveness.

• The study of the effectiveness of the modes in the context of elementary and

secondary education context is also important.

• India is a country of a diverse population. Though it has a uniform educa-

tion system, cultural diversity does influence the way the components and

methods of teaching-learning are adopted. Hence, it is necessary to conduct

these experiences in diverse cultural conditions.

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Effective teaching and learning need an effective delivery system. Globalisation

and advancement in ICT changed the delivery style of teaching and learning.

Online education is replacing the conventional method of teaching. Further studies

in the field will emphasise that blended and online learning can play an important

role in improving the effectiveness and efficiency of students’ learning process in

higher education institutions.

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Appendix A

Descriptions of Matching Tools

A.1 Multidimensional Aptitude Battery-II

Like the scales from many other measures of intellectual abilities dating back tothe U.S. Army Alpha and Beta tests and before, the Multidimensional AptitudeBattery-II (MAB-II) consists of verbal and nonverbal groups of scales. Five “Ver-bal” sub-tests are contained in one booklet and five nonverbal, “Performance,”sub-tests are presented in a second booklet. Separate answer sheets, which may beeither hand or machine-scored, are provided for Verbal and Performance sections.It is thus possible to administer either Verbal or Performance sections separately,or the two together to obtain a comprehensive assessment of intellectual abilities.In addition to ten sub-scale scores, the MAB-II yields a Verbal IQ, a PerformanceIQ, and a Full-Scale IQ. Alternatively, standard scores may be used in place ofVerbal, Performance, and Full-Scale IQs. Descriptions of each scale are presentedat the beginning. The ten sub-scales of the MAB-II are presented below, listedunder the booklet in which they are contained.

A.1.1 Verbal

Information: The Information score reflects the degree to which an individual hasaccumulated a fund of knowledge about diverse topics. This fund of information

159

Appendix A. Matching Tools 160

is influenced by an individual’s level of curiosity, extensiveness of reading, andmotivation to learn new things. Long-term memory is required for a high score onthe Information test.

Comprehensive: Comprehension assesses the ability to evaluate social situationsto identify behaviour that is more socially desirable, and to give the reasons whycertain laws and social customs are practised. It requires not only general verbalability, but a degree of social acculturation, social intelligence, and knowledge ofconventional standards for moral and ethical judgment.

Arithmetic: This test, requiring the solution of numerical problems, reflectsreasoning and problem-solving abilities. High scorers have the capacity to abstractthose elements of a problem necessary for its solution and to arrive at a correctanswer quickly.

Similarities: Similarities requires an individual to conceptualize and rank like-nesses and differences as properties of an object and to compare these abstractlikenesses to those of another object, identifying the one that is most appropriate.Such a task requires flexibility and adjustment to novelty as well as an appre-ciation for and comprehension of properties of objects, long-term memory, andthe capacity for abstract thought. Unlike certain other verbal tests, Similaritiesrequires more than simply retrieving knowledge from long term memory; it is alsoa measure of how effectively one can use this knowledge.

Vocabulary: In its narrow interpretation, Vocabulary is an indication of thenumber of words or verbal concepts that have been learned and stored. But morebroadly, it indicates the individual’s openness to new information and conceptsand reflects the capacity to store, categorize, and retrieve this information appro-priately. Persons scoring high on Vocabulary can be expected not only to be ableto use words effectively but to demonstrate a higher level of subtlety and depth ofthought processes, and of conceptual and classificatory skills in the verbal domain.

A.1.2 Performance

Digit Symbols: Digit Symbol requires the learning of a new coding system andits use in a context in which visual-motor activity is important. Thus, like other


Performance sub-tests but unlike most of the Verbal Scale, it involves adaptation toa novel set of demands. The application of a novel combination of abilities—visualacuity, figural memory, motor skills, speed of information processing, and motiva-tion and persistence—is a further task requirement. It is markedly affected by ageand by impairment of visual-motor performance.

Picture Completion: The identification of important missing elements in apicture requires knowledge of a variety of common objects and the rules used forsimplified sketches. Other task requirements are the perceptual skills necessaryto interpret a percept meaningfully, the analytical skills required to distinguishimportant, critical details from unessential omissions, the ability to avoid thecompetition of irrelevant details in arriving at a solution, and the verbal ability toidentify quickly the first letter of the name of the missing detail.

Spatial: The Spatial sub-test requires the ability to visualize abstract objectsin different positions in two-dimensional space and to be sensitive to critical dif-ferences among alternatives. More generally, it requires reasoning in the figural-spatial domain combined with visual and imaginal processes, processes which forhigh scorers must be evoked quickly and automatically, for the task is timed. Anexcessive degree of checking responses as a result of cautiousness will impair thespeed of performance. Age also affects performance substantially, a fact that isincorporated into MAB-II (Indian Adaptation) norms.

Picture Arrangement: Picture Arrangement requires the respondent to identifya meaningful sequence from a random sequence, where the meaningful sequenceoften has a humorous interpretation. As such, it requires an ability to decodeperceptually a number of drawings, to abstract their intent and meaning, to inte-grate these separate perceptions into a meaningful temporal pattern, to locate theletter sequence corresponding to the correct sequence, and to follow these steps asquickly as possible in recognition of the timed nature of the task. Thus, the taskrequires both perceptual abilities and sufficient social intelligence to have insightinto others’ behaviour, permitting evaluation of alternative outcomes.

Object Assembly: Object Assembly requires that the respondent identify ameaningful object from a left-to-right sequence of disarranged segments. For sucha task, perceptual, analytical skills are required to visualize how the separate parts


might be reassembled, or, alternatively, first to identify elements of familiar objectsin the disarranged segments and to form a judgment about the integration of thesegments into a whole. Because the parts are printed, rather than in a manipulableform, visualization skills are also required to imagine the form of the figure whenparts are rearranged.

A.2 Computer Attitude Scale (CAS)

* Items of the affective domain was used in the study, as the reliability of the otherdomains (affective and behavioural) were very low. ** Items removed at the pilotstage.

The items were designed in Likert type scale, and they had options for ”DefinitelyTrue”, Maybe True”, ”Not Sure”, ”Maybe Untrue”, ”Definitely Untrue”.

1. Computers frighten me.*

2. Anything I can do on a computer, I can just do just as well without one.**

3. I learn new computer task by trial and error.

4. Working with a computer makes me feel tense and uncomfortable.*

5. Working with a computer is fun.

6. Other students ask me for help when using the computer.

7. I feel helpless when asked to perform a task on the computer.*

8. Computer work is boring.**

9. When I have a problem with the computer, I will usually solve it on my own.

10. I feel important when others ask me for information about computers.

11. Only Computer experts can understand both the technical aspects and howto use lots of software.**

12. Using the computer has increased my interaction with other students.


13. Computers bore me.*

14. I develop shortcuts and more efficient ways to use computers.

15. Working on computers makes me feel isolated from people.*

16. Anyone can use computing system.

17. I would like to spend more time using a computer.

18. I do not feel I have control over what I do when I use a computer.*

19. Computers should be available in every classroom.

20. If I can, I will take subjects that will teach me to use computers.

21. Computer sometimes scare me.*





26. Computers are tools that help me to achieve my goals.

27. I would like to learn more about computers.

28. I feel unhappy walking into a room filled with computers.*

29. Using the Internet is a waste of time.**

30. If I need computer skills for my career choice, I will develop them.

31. I am not good with computers.*

32. Computer jobs are exciting.

33. If my institution offered a computer course I would like to attend it.

34. Working with a computer makes me feel very nervous*.

35. Computer knowledge is important for everyone in society.


36. I feel threatened when others talk about computers.*

37. Computer skills are essential for my future.

38. Computers make me feel uncomfortable.

39. Computers help me to learn things.

40. I get a sinking feeling when I think of trying to use a computer.*

41. Computer frustrates me.*

A.3 Learning and Study Strategies Inventory

The Learning and Study Strategies Inventory (LASSI) is a 10-scale, 60-item as-sessment of students’ awareness about and use of learning and study strategiesrelated to skill, will and self-regulation components of strategic learning. The fo-cus is on covert and overt thoughts, behaviours, attitudes, motivations and beliefsthat relate to successful learning in postsecondary education and training settings.Furthermore, these thoughts, behaviours, attitudes, motivations and beliefs can bealtered through educational interventions. Research has repeatedly demonstratedthat these factors contribute significantly to success in college and that they can belearned or enhanced through educational interventions such as learning strategiesand self-regulated study courses and programs.

The LASSI is both diagnostic and prescriptive. The LASSI provides standardizedscores (percentile score equivalents) and national norms for ten different scales(there is no total score reported because this is a diagnostic instrument). It pro-vides students with a diagnosis of their strengths and weaknesses, compared toother college students, in the areas covered by the ten scales; it is prescriptive inthat it provides feedback about areas where students may be weak and need toimprove their knowledge, skills, attitudes, motivations and beliefs.

There are six items on each of the ten scales of the LASSI, 3rd Edition. Thesescales are Anxiety, Attitude, Concentration, Information Processing, Motivation,Selecting Main Ideas, Self Testing, Test Strategies, Time Management, and UsingAcademic Resources.


Each of these scales is primarily related to one of three of the components ofstrategic learning: skill, will and self-regulation. The conceptual framework ofstrategic learning underlies each of these components, so there are some overlapand interaction among and within the components and individual scales. However,strategic learners need to know about each of these categories and about how touse information and skills in each of these categories. They also need to knowhow to pick and choose among the various elements in each category to help themreach specific learning goals and objectives.

A.3.1 The skill component of strategic learning

The LASSI Scales related to the skill component of strategic learning are: Infor-mation Processing, Selecting Main Ideas, and Test Strategies.

The Information Processing Scale assesses how well students’ can use imagery,verbal elaboration, organization strategies, and reasoning skills as learning strate-gies to help learn new information and skills. These strategies are also used tobuild bridges between what students already know or believe and what they aretrying to learn and remember.

The Selecting Main Ideas Scale assesses students’ thinking skills for identify-ing important information for further study from less important information andsupporting details.

The Test Strategies Scale assesses students’ use of both test preparation andtest-taking strategies.

A.3.2 The will component of strategic learning

The LASSI Scales related to the will component of strategic learning are Anxiety,Attitude, and Motivation.

The Anxiety Scale assesses the degree to which students worry about school andtheir academic performance.


The Attitude Scale assesses students’ attitudes and interests in college andachieving academic success.

The Motivation Scale assesses students’ diligence, self-discipline, and willingnessto exert the effort necessary to complete academic requirements successfully.

A.3.3 The self-regulation component of strategic learning

The LASSI Scales related to the self-regulation component of strategic learning areConcentration, Self Testing, Time Management, and Using Academic Resources.

The Concentration Scale assesses students’ ability to direct and maintain theirattention on academic tasks.

The Self Testing Scale assesses students’ use of comprehension monitoring tech-niques, such as reviewing or paraphrasing, to determine their level of understand-ing of the information or skill to be learned.

The Time Management Scale assesses students’ use of time management prin-ciples and practices for academic tasks.

The Using Academic Resources Scale assesses students’ willingness to usedifferent academic resources such as writing centres, tutoring centres and learningor academic support centres when they encounter problems with their courseworkor performance.

Appendix B

Evaluation Tools

B.1 Contemporary India and Education (C-2)

Normative Visions of Indian Education

Total Marks : 50 Time: 2 hours

All the questions are compulsory.

Group A

1. ............. was the first Indian writer who suggested mass scale orientation ofcommon people for the benefit of the state in Ancient India.

2. ............. was the first Indian emperor who established a formal system ofadministrative officials to provide value orientation to the common mass.

3. The first Indian civilisation that is understood to have some kind of citizen-ship values was ................

4. Prasthanatrayi (three sources or axioms) refers to the three canonical textsof Hindu philosophy, especially of the Vedanta school. It consists of .......

5. The four noble truths of Buddhism are: .........................

167

Appendix B. Evaluation Tools 168

6. Which of components of Eight Fold path of Buddhism can be perceived asdirectly promoting moral virtues?

a) Right Speech b) Right Action

c) Right Livelihood d) Right Resolve

7. Which of the following is a part of the three jewels of Jainism.

a) Right Knowledge b) Non-violence

c) Right Livelihood d) Truthfulness

8. The word .................. represents the spirit of common brotherhood in theIndian Constitution.

a) equality b) unity

c) fraternity d) socialism

9. The term secularism mentioned in the Indian Constitution means

a) separation of state and religion

b) developing scientific temperament

c) freedom to profess, preach and practise any religion

d) equality of religious sects

10. The social institution that plays an important role in developing responsiblecitizenship with democratic values is

a) education b) democratic participation

c) political party d) family

Group B (40 words) All the questions are compulsory.

11. The power of religious fundamentalism is not vested in religious text orcanons but in modern democratic politics to seek mass followers. Elaborate.

12. Saptabhangivad or Syadvad is a Jain theory that supports the diversity andrelativity of views. However, it is different from the diversity of individualviewpoints, Explain.


13. Why should a school teacher be inclusive not just tolerant of different reli-gious faiths?

14. Islam promotes democratic ethos, but the democracy itself is inconsistent inmany of the Muslim countries, why?

15. Describe the early history of Christianity in India.

Group C (100 words)

16. Hinduism contains a plethora of sects. These sects promote both toleranceand strife. Explain.

17. Does Indian secularism differs from western secularism? How?

18. What do you mean by federalism? Discuss the federal features of the IndianConstitution.

19. Define and differentiate between the concepts of equity and equality.

20. What steps will you take to promote democratic values among your students?


B.2 Learning and Teaching(C-3)

Planning for Teaching


Group A


1. Visualising the learners means finding out different psycho-constructs like................. and .............. background of the learners.

2. Besides classroom teaching, the unit plan can include ...........

3. ................. attitude is the type of attitude that is invisible to us and func-tions from our subconscious level.

4. Level of high academic .............. can lower academic achievement with re-spect to her potential.

5. The genius children need a modified curriculum which provides opportunitiesfor ............... in their interest area of interest and .................... in otherareas.

6. Which of the following is not a part of the minor system for a child?

a) Family b) Curriculum Planner

c) Classroom d) Neighbourhood

7. Which of the following is a part of the major system for the child

a) School b) Culture

c) Family friends and relatives d) workplace of the parents

8. ................. is NOT an example of the instrumental value.

a) Cleanliness b) Self control

c) Love d) Family security


9. Which of the following principle is NOT involved in unit planning

a) Interest b) Development

c) Dynamism d) Persistence

10. Which one of the following can NOT be used for visualising the learners

a) hearsay about child’s community b) Self reporting

c) Group and Individual Testing d) Health Report

Group B (40 words)


11. What is a terminal value? Give some examples.

12. What are the differences between attitude and aptitude?

13. Describe Thorndike’s theory of Readiness.

14. Finding the interest area of a learner is critical for an effective teaching-learning.

15. How the evaluation of learning achievement of a unit is different from theevaluation of learning achievement of a lesson?

Group C (100 words)

16. Visualising the learner is the base for understanding their differences. Clarifythe meaning of the statement and describe the significance of visualising.

17. What is learning readiness? Identify the factors affecting it.

18. Describe the steps for planning for a unit relating to your teaching method.

19. The identification of the objectives of assessment is a stratified process. Clar-ify.

20. Discuss the process of analysing content matter of teaching subject.


B.3 Critical Understanding of ICT (EPC-3)



Group A

1. Records are ................. forms of information.

2. An organism or system can receive information as ............... input.

3. The name of word processor installed by default in Ubuntu Operating Systemis ...............

4. For installing a new app in Ubuntu, one needs to go to ..........

5. The expansion of the acronym FLOSS is ..........................

6. Which of the following is an educational software:

a) Kile b) Stellarium

c) Impress d) Firefox

7. What is/are the different format/s in which one can save a word processingdocument?

a) .odt b) .doc

c) .docx d) All of above

8. Which of the following is NOT among the free and open-source operatingsystem

a) Fedora b) Debian

c) Mac d) Ubuntu

9. .............. is NOT an input device

a) pendrive b) keyboard

c) joystick d) touch screen monitor


10. Malware does NOT include

a) spyware b) spyware

c) virus d) hacking

Group B (40 words)


11. How the Open Source software is more supporting to teaching-learning?

12. Enlist the apps relating to LibreOffice with a brief description of its function.

13. What is the difference between the operating system and Application soft-ware?

14. Describe the ways we can classify the operating systems?

15. Copying from your textbook to your assignment can be an example of pla-giarism? Why or Why not?

Group C (100 words)

16. What is Free and Open Source Software? Discuss its philosophy and advan-tages.

17. What is telecommunication? Discuss its types and implications for educa-tion.

18. How can you use a browser for secured and smart Internet-surfing?

19. Discuss the process of designing E-content. Enlist some popular authoringtools.

20. Briefly describe the types of networking.


B.4 Assessment for Learning (C-9)

Introduction to Assessment & Evaluation



Group A

1. Being trained under a Music maestro without a formal degree is an exam-ple of ............. learning. The evaluation here is an example of .................evaluation.

2. In the context of institutions assessment is a/an ................... process.

3. Social Constructivism emphasises on ................. of learning.

4. Constructivism perceives learning as an active process of .......... of the en-vironment.

5. The terms summative evaluation and formative evaluation was first coinedby ................... in 1967

6. Which one of the following is a psychological group is a psychological theoryrelating to the British Empiricism of Hume:

a) Behaviourism b) Rationalism

c) Constructivism d) Social Constructivism

7. Which one of the following is NOT an objective of summative evaluation

a) promoting b) Feedback for learning

c) Categorising d) Giving degree

8. The word .................. represents the spirit of universal brotherhood in theIndian Constitution.

a) equality b) unity

c) fraternity d) socialism


9. Which of the following is NOT a purpose of formative assessment

a) providing feedback to the teachers to modify her teaching strategies

b) making students focus on their learning progression

c) taking a decision like retaining a student in a particular class

d) improving the self-efficacy of learners

10. Which of the following is NOT an example of direct assessment

a) project b) case study

c) survey d) portfolios

Group B (40 words)

11. Criterion-referenced assessment can be critical in some conditions. Elabo-rate.

12. Why do we use diagnostic tests?

13. What is the meaning of placement in the academic context?

14. In what condition you can use performance assessment in your class?

15. What challenges can you perceive in using norm-referenced tools for highstakes evaluation?

Group C (100 words)

16. Discuss the meaning and scope of terms like test, examination, appraisal,evaluation in the context of assessment.

17. Discuss the main features of the forms of assessment based on nature andscope of assessment.

18. What are the differences between formative and summative evaluation? Howwill you use formative evaluation during your classroom teaching?

19. Can teacher made tests be standardised? How?

20. What is a prognostic test? Discuss its use for programme evaluation.

Appendix C

Data Sheets

177

Sheet1

Page 1

Age s1bl s1ol s1cl s2bl s2ol s2cl s3bl s3ol s3cl s4bl s4ol s4cl VIQ PIQ SIQ

27 36 32 31 30 81 87 82

22 32 31 35 29 86 70 76

23 33 25 23 27 90 76 83

25 35 25 28 22 90 89 89

24 33 23 29 25 92 85 88

22 38 21 28 22 94 70 81

22 34 26 29 28 97 74 85

22 41 32 36 30 97 86 92

24 37 26 29 28 99 86 93

23 35 22 28 24 103 70 86


29 32 26 32 26 83 89 85

26 28 24 29 26 89 81 84

22 31 27 31 28 90 86 87

21 33 25 30 24 91 70 79

22 27 24 31 23 92 70 76

24 26 21 30 24 93 73 82

23 24 22 31 26 96 77 86

22 29 27 41 27 99 86 93

21 33 29 39 27 100 78 89

25 36 30 41 29 103 92 98


30 25 32 27 28 80 73 75

23 29 36 32 34 86 75 80

23 32 37 28 28 88 74 98

23 23 30 22 25 90 73 81

22 36 28 34 35 93 74 83

21 33 40 31 34 94 70 81

28 25 32 26 29 95 70 75

26 32 32 28 32 96 99 98

21 31 33 28 27 98 75 86

22 32 39 25 27 102 70 95


21 35 36 34 38 84 84 83

29 31 33 35 37 88 76 81

21 29 32 25 34 90 70 78

24 27 34 26 31 92 88 90

23 27 32 25 33 93 83 87

28 33 33 29 34 94 87 90

24 27 27 25 34 95 88 92

26 27 32 26 39 98 78 88

24 24 28 25 35 101 72 86

20 22 29 24 31 103 70 80


21 32 28 31 27 81 63 6824 42 35 32 31 86 78 8126 38 33 36 32 88 84 85

27 36 32 39 30 91 82 85

Sheet1

Page 2

22 35 30 34 28 92 72 8121 29 23 25 25 93 73 8322 32 22 26 25 96 77 86

23 43 36 36 33 98 85 9122 37 26 30 26 101 75 88

21 37 24 29 25 101 90 95


25 25 22 31 23 82 74 7723 43 39 45 25 87 82 84

21 23 21 27 26 89 73 80

22 36 27 30 24 91 79 8423 34 29 39 25 93 70 81

26 37 32 40 26 93 71 8223 35 30 32 27 97 74 8522 34 30 39 34 99 70 85

21 34 30 31 30 101 80 9121 33 31 38 30 102 78 90

Age s1bl s1ol s1cl s2bl s2ol s2cl s3bl s3ol s3cl s4bl s4ol s4cl VIQ PIQ SIQ22 34 41 35 37 81 78 78

21 34 37 36 39 85 72 7822 25 25 26 30 88 81 8422 34 39 31 34 92 77 84

21 36 41 32 38 93 69 8022 36 40 33 36 94 91 9222 27 36 29 31 98 75 86

22 35 39 28 32 101 72 8624 33 38 24 27 102 72 87

22 31 38 25 28 104 81 93


21 26 32 28 37 82 74 7726 29 31 28 39 87 82 8425 32 34 30 38 89 73 80

22 30 35 35 40 91 79 8421 33 31 34 42 93 70 81

23 28 31 30 29 93 71 82

20 29 32 35 43 97 74 8523 29 37 32 39 99 70 85

21 32 38 33 39 101 80 9120 32 34 29 36 102 78 90

Appendix D

Visuals of Modules

Figure D.1: Moodle website http.glocaledu.org/elearning

Figure D.2: Moodle website http.glocaledu.org/elearning

181

Appendix D. Visuals of Modules 182

Figure D.3: Moodle course writing interface

Figure D.4: Moodle course writing interface

Words Index

ADDIE, 75

Blended Learning, 8Blended Learning features, 11

Clark-Kozma Debate, 21, 131Classroom Type Online Learning

Model, 70Cognitive Presence, 82Cohen, Louis, 25Community of Inquiry, 80, 97Community of Practice, 88Competency-based Learning, 86Constructivism, 12Continuum of Mode of Education, 2

e-learning, 8expectancy advantage, 31

Face-to-Face Driver Model, 68Face-to-face learning, 10Fisherian school of significance

testing, 26Flex Model, 68

Hawthorne effect, 29

Jastrow’s Effect, 31

Learner-centric approach, 12, 130

learner-centric education, 7

Media Debate, 21, 130MOOCs, 3, 72

NCF, 6NCF 2005, 7NCFTE, 6NPTEL, 3Null Hypothesis Significance Testing

(NHST), 27

Online Collaborative Learning, 78Online Driver Model, 69Online Lab Model, 69

positivism, 24post-positivist, 25

Research paradigm, 23Rotation Model, 68

scientific paradigm, 24scientific realism, 24Sloan Consortium, Sloan-C, 9Social Presence, 82SWAYAM, 4SWAYAM Prabha, 5

Teaching Presence, 83

183

Index 184

The John Henry Effect, 31The Novelty Effect, 31The Pygmalion Effect, 31

Types of MOOCs, 72

UTAUT, 45

Names Index

Adair, G., 30

Bates, A. W. T. and Bates, A. W, 72Beile, P. M, 37Bernard, R. M, 34Boote, D. N, 37Buskirk, T. D., 37

Caldwell, E. R., 37Campbell, M., 36Carman, J.M., 96Chauhan. A., 72Clark, R. E., 21, 96, 97Crichton, S, 10

Davis, J. D., 34, 36Downes, S., 72, 73Draper, Stephen W., 29–31Drysdale, J.S, 9Dziuban, C, 10Dziuban, C. D., 19

Feldman, R. S., 36French, J.R.P., 29

Gaddis, B, 37Garnham, C, 10Garrison, D. R., 10Gould Jay E., 49

Gould, Jay E., 51Graham, C.R., 9

Haig, B. D., 25Haig, Brian D., 26, 27Hubbard, R., 26

Jacobson,L., 31Jastrow, 31

Keefe, T. J., 35Klee, Robert, 23, 24, 28Kozma, R. B., 21Kuhn, Thomas S., 28

Maag, M., 22Mayo, E., 29McGee, P., 9McKethan, R. N,., 22Mcluhan, M., 20McNamara, J. M., 37Means, Barbara, 33, 35, 36, 38

Neyman, 27

Odell, M. R., 37

Poirier, C. R., 36Popper, K., 25

Reis, A., 9

185

Index 186

Rosenberg, M., 8Rosenthal,R., 31Ruchti, W. P., 37

Saretsky, G., 31Schmeeckle, J. M., 22Schnitman, I., 22Schroeder, B. A., 22Schutt, M., 22Scoville, S. A., 37

Spiliotopoulos, Valia, 9

Tantrarungroj, P., 22Trout, J. D., 26

Vaughan, Norman D., 10Venkatesh, V, 45

Zdep,S.M., 31Zhang, D., 22Zhang, K., 34

Documents

A Study of Effectiveness of e-Learning and Blended ...I, Prabhas Ranjan, hereby declare that this thesis titled, “A Study of Eﬀec-tiveness of e-Learning and Blended Learning Among