Collaborative Learning in Social Networking Sites: A Case Study on the

use of Mahara

Gregory S. Ching

Lunghwa University of Science and Technology, Taoyuan, Taiwan, ROC

gregory_ching@yahoo.com

Keywords: social networking sites, collaborative learning, task-based learning, constructivist internet-based learning environment, learning style

Abstract. Information technology and education have been working hand in hand. Advancement in

computer technology has altogether opened up limitless educational innovation. With the rise of

popularity of social networking sites (SNS) such as Facebook, educators have been eager to test the

usefulness and effectiveness of SNS in the teaching and learning process. This paper summarizes the

findings of a case study with the use of a social networking software; Mahara. Participants are 46

students of a technical vocational university in Taiwan. Students are grouped together and assigned a

certain task to accomplish with the use of Mahara. Enabling the collaborative functions of SNS to

accomplish the task, students are later surveyed with regards to their learning styles, perceived

collaborative learning and constructivist internet-based learning environment (CILES) preferences.

Result shows that the participants’ collaboration is highly significant to their CILES preferences.

While, there seems to be no significant effects of learning style towards the participants’ CILES

preferences. Recommendations are given to further the improvement of SNS use in education.

Introduction

For the past two decades, the rise of globalization and the advancement of technology have continued

to change the way we conduct our daily lives [1-3]. Moreover, the phenomenon of globalization has

jumpstarted a series of trends and concepts that have continued to change the teaching and learning

pedagogy. Furthermore, technological advancement has also ushered the era of evolving concepts of

literacies and the transformation on the definition of text [4]. Literacies are now said to include not

only the traditional alphabetical texts, but multimodal versions of texts including images, symbols,

pictures, sounds or any combination of these elements.

Social networking sites (SNS) or a more common term people are aware; Facebook has changed

the way people perceived online communities [5-6]. In Taiwan, data from the August 2011 survey

mentioned that on average an individual spends around 27.8 hours a month online. Results also show

that Facebook accounts for 27% of the time, while YouTube accounts for around 4% of the time. Data

also suggests that there is an overall increase of around 24% as compared to last year’s average. In

sum, the numbers and times spent of online users is increasing with the further advancement of

technology. Hence, it is hypothesized that an instructional design based on SNS should provide

positive learning outcomes.

SNS Platform. This study shall mainly use an open source program called Mahara; a Personalized

Learning Environment. Mahara is able to address three relevant learning concept of the current age,

namely: Personalized learning, Reflective learning, and Collaborative learning. Mahara actually

concerns itself with the personalization of the learning process. Some characteristics includes: 1)

Personalized self-presentation, wherein users can design their own web pages, thereby, organizing

and presenting their own learning data in precisely the way they would like to present it; 2) Privacy –

within Mahara, users are able to upload personal files such as documents, videos, audio clips, images

and so on (limited to the amount of allowable disk space) in a secured location in cyberspace (a

concept of cloud application); 3) Accessible – users are able to access uploaded data wherever and

Advanced Materials Research Vol. 717 (2013) pp 778-783Online available since 2013/Jul/15 at www.scientific.net© (2013) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/AMR.717.778

All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP,www.ttp.net. (ID: 130.194.20.173, Monash University Library, Clayton, Australia-26/11/14,14:18:21)

whenever as long as an internet connection is available; and 4) Access control, wherein users can

actually control who gets to see what. In addition, Mahara allow users to form groups and institutions,

which further limit the accessibility of information placed within Mahara.

Social Modalities in Learning. With the coming of the Web 2.0 technologies such as blogs,

podcasts, wikis, and SNSs, widespread adoption of these technologies have been seen all throughout

the academe [7-8]. The most common Web 2.0 technologies used in the educational context are Blog.

Blogs are genres of texts defined not so much by their form or content as by the kinds of uses to which

they are put, and the ways these users construct social identities and communities [9]. In a study

regarding a blog integrated intelligent tutoring system, wherein learners can better regulate and

enhance their own learning. Study have shown that through the use of an experimental course,

learners are able to make use of the blog-based learning aid in a very positive way and eventually pass

the specified evaluation thresholds [10].

Social networks are actually defined as the social structure of nodes that represent individuals (or

organizations) and the relationships between them within a certain domain. Therefore, social

networks are usually built based on the strength of relationships and trust between the members

(nodes) [11]. Recently many have been using the concept of SNS in the educational settings. In a

study on high school students’ online community discussion forum, wherein students provide

comments or expressed their thoughts and opinions on blogs. Results show that such social talks are

able to help solved collaborative issues in a subtle and indirect manner, hence, makes learning more

effective [12].

In a study on a Taiwanese network learning society EduCities, findings suggest a structured

network learning society helps participants to coordinate and manage interaction processes [13]. In a

way, a SNS learning environment provides various opportunities for students and teachers alike to

interact and learn from each other. In a recent study on 25 British teenagers’ language and literacy

practices on Facebook, results have shown that Facebook do function as a new medium of self

presenting and making friends [14]. In sum, SNS learning communities can effectively function as a

learning tool. However, educators must guide their students and model effective knowledge

construction and collaboration by establishing trusting relationships with students through

appropriate feedback and adequate supervision [15].

Collaborative learning. Collaborative learning is defined as any instructional method in which

students work together in small groups toward a common goal [16]. As the notion of working with

others often increases involvement in learning, similarly, sharing one’s own ideas and responding to

others’ reactions sharpens thinking and deepens understanding. In a study involving the quality of

student involvement in a group of college educational psychology students, findings suggest that

overall quality of experience was greater during collaborative learning. Benefits occurred specifically

for thinking on task, student engagement, perceptions of task importance, and optimal levels of

challenge and skill [17].

Collaborative learning in a SNS environment has also shown some significant effects [18-19].

Furthermore, research shows that accounting learning styles in grouping and collaborative learning

process is able to improve the overall outcome of the group [20]. In a collaborative engineering

college students’ learning activity, results have confirm the effectiveness of using wiki as a

collaborative authoring tool [21]. In another spectrum, the use of SNS is not without its problems.

Many are concern on SNS’s privacy and integrity; research shows that 80% user reported the lack of

integrity of student submissions, while over 70% say privacy concerns are very important barriers [22].

Ultimately, SNS does facilitate information sharing, knowledge management, and in fostering

collaboration within and between organizations. However, careful monitoring is needed [23].

Methodology

This research is designed as a case study, wherein the primary objective is to investigate a

contemporary phenomenon within its real-life context; when the boundaries between phenomenon

and context are not clearly evident; and in which multiple sources of evidence are used [24]. To

Advanced Materials Research Vol. 717 779

understand the effectiveness of SNS usage in education, this case study shall summarizes the findings

of a course subject in Marketing. Using the SNS software Mahara, a total of 46 third year students of

a technical vocational university in Taiwan participated in the study. Students are grouped together

and assigned a certain task to accomplish with the use of Mahara. The task is to create a website for a

hypothetical product with the use of Mahara as a platform for the website. The students shall enable

the use of the collaborative functions of Mahara to accomplish the task. At the end of the semester,

students are surveyed with regards to their learning styles, perceived collaborative learning and

constructivist internet-based learning environment (CILES) preferences.

Survey Instruments. The survey used in this study is comprised of three parts, the constructivist

internet-based learning environment or CILES, the statements for collaboration, and the learning style

survey. The CILES is composed of the following scales: 1. Ease of use scale, which involves

measuring perceptions of the extent to which students discern that the Internet-based learning

environments are easy-to-use. 2. Relevance scale, which involves measuring perceptions of the extent

to which students discern that the Internet-based learning environments are authentic and represent

real life situations. 3. Challenge scale, which involves measuring perceptions of the extent to which

students discern that the Internet-based learning environments are challenging but helpful in problem

solving. 4. Inquiry learning scale, which involves measuring perceptions of the extent to which

students have the opportunities to be engaged in inquiry learning in the Internet-based learning

environments. 5. Reflective thinking scale, which involves measuring perceptions of the extent to

which students have the opportunities to produce critical self-reflective thinking in the Internet-based

learning environments [25].

CILES is quite a reliable tool. Validity of the CILES ranges from 0.93 to 0.85, which is considered

highly reliable [25]. CILES is derived from Maor’s Constructivist Multimedia Learning Environment

Survey, which had been originally designed to evaluate interactive multimedia programs [26]. This

was later revised into the CILES, which is specifically meant for examining the relationships between

the duration spent on internet and preferences towards internet-based learning environments [25]. In

their original study, it was found that students having moderate internet experiences seemed to be

more critical to the preferences of the internet-based learning environments.

As for the collaboration survey, items are derived from the statements for collaboration used in a

study by Lee and Tsai with an overall reliability of 0.84[27]. For each of the statements throughout the

survey, a five point Likert scale is used. Scales are marked as 5 for strongly agrees to 1 as strongly

disagrees with the items describing the participants. For the learning styles, the study uses the highly

referred inventory originally developed by Dunn [28] to describe the three basic styles, such as visual,

auditory, and tactile learner.

Data Analysis. After the survey is collected and encoded, the Statistical Package for Social

Scientist (SPSS) software is used to compute for the mean, correlations, T-tests, and Analysis of

Variance (ANOVA). For the validity of the survey, besides for the learning style with a reliability of

0.52, the rest of the factors are quite reliable with Cronbach alpha values ranging from 0.81 to 0.86

(please see table 2).

Participants. As mentioned earlier, the study involves 46 students enrolled in a Marketing course

at a technical vocational university in Taiwan. Table 1 shows the background demography of the

participants. Among the participants, female students consist of 74%, while the male students

comprises of the remaining 26%. Average age is 22 years old. As for the internet accessibility, 87% or

40 students mentioned that they have smart-phones with internet capability. While, 96% or 44 of the

students stated that they have internet connection at their homes. For the duration of internet usage,

39% of the participants mentioned that they spent more than 24 hours a week. While the rest are less

than 24 hours (please see table 1 for more details).

780 Key Engineering Materials and Computer Science II

Table 1. Descriptive statistics (N=46)

Items n % Min. Max. Mean SD

Gender

20 38 22 3.36

Female 34 74 20 38 22 3.60

Male 12 26 20 29 21 2.67

Internet capable mobile phone

Yes 40 87

No 6 13

Internet connection at home

Yes 44 96

No 2 4

Internet usage

Less than 6 hours a week 6 13

Between 6 to 12 hours a week 14 31

Between 12 to 24 hours a week 8 17

More than 24 hours a week 18 39

Table 2. Results on the various factors and items of the survey (N=46)

Factors/Items (Cronbach Alpha Reliability) n Min. Max. Mean SD

Ease of use (α= 0.82)

3.34 0.98

Have interesting screen designs 44 1 5 2.95 1.03

Are easy to navigate 44 2 5 3.80 0.82

Are fun to use 44 2 5 3.59 0.82

Are easy to use 44 2 5 3.61 0.84

Take only a short time to learn how to use 44 2 5 3.55 0.85

Relevance (α= 0.80)

3.49 0.97

Show how complex real-life environments are 44 2 5 3.48 0.90

Present data in meaningful ways 44 2 5 3.89 0.72

Present information that is relevant to me 44 2 5 3.68 0.74

Present realistic tasks 44 1 5 3.59 0.84

Have a wide range of information 44 2 5 3.95 0.96

Challenge (α= 0.81)

3.92 1.35

Make me think 46 1 5 3.91 0.92

Are complex but clear 46 1 5 3.11 0.99

Are challenging to use 46 2 5 3.39 0.80

Help me to generate new ideas 46 2 5 3.67 0.73

Help me to generate new questions 46 1 5 3.72 0.89

Inquiry learning (α= 0.85)

3.72 0.62

I can find out answers to questions by investigation 46 2 5 4.09 0.73

I can carry out investigations to test my own ideas 46 1 5 3.85 0.87

I can conduct follow-up investigations to answer my new questions 46 1 5 3.72 0.91

I can design my own ways of investigating problems 46 2 5 3.70 0.87

I can approach a problem from more than one perspective 46 2 5 3.65 0.95

Reflective thinking (α= 0.86)

3.83 0.71

I can think deeply about how I learn 46 2 5 3.67 0.82

I can think deeply about my own ideas 46 2 5 3.65 0.90

I can think deeply about new ideas 46 2 5 3.63 0.88

I can think deeply how to become a better learner 45 2 5 3.56 0.92

I can think deeply about my own understanding 45 2 5 3.73 0.81

Collaborative learning (α= 0.85)

3.47 0.67

Discuss problems encountered in learning with peers 46 3 5 3.74 0.68

Share class notes or learning materials with peers 46 2 5 3.70 0.79

Share my learning experiences with peers 46 2 5 3.83 0.85

Make good use of learning information provided by my peers 46 2 5 3.61 0.77

Review learning materials with peers prior to exams 46 2 5 3.65 0.82

Learning styles (α= 0.52)

Visual learner

10.54 6.82

Auditory learner

10.63 6.86

Tactile learner

11.48 7.96

Advanced Materials Research Vol. 717 781

Results and Discussions

The primary objective of this study is to determine the effectiveness of a SNS used in an actual course

subject. Table 2 shows the various mean scores of the CILES, statement for collaboration, and

learning styles. The highest among the items are the item I can find out answers to questions by

investigation for the factor Inquiry Learning with a mean of 4.09. This result signifies that the students

in a sense are quite interested in learning the subject Marketing. Furthermore, among the factors, the

highest is Challenge with an overall mean of 3.92. Such results indicate that students felt challenge

with the use of the SNS. Since the SNS software is new to them, students although at first felt hesitant

in using the system. However, they later immersion with their assigned tasks, students becomes more

attached and used to the system.

As for the effects of gender, T-test results show that there are no significant differences among the

participants. Similarly, there are also no significant differences among the students’ learning styles.

Such results indicate that the collaborative SNS learning environment is effective regardless of the

students’ gender and learning styles. In addition, ANOVA results show that there seems to be no

significant difference among the various time spent online with the CILES and collaboration. For the

correlations among the various factors, results show that collaboration is highly significant to the

CILES (please see table 3 for more details).

Table 3. Correlations among the factors

Factors (1) (2) (3) (4) (5) (6) (7)

Internet usage (1) 1

Ease of use (2) -0.022 1

Relevance (3) 0.045 0.806** 1

Challenge (4) -0.107 0.449** 0.325* 1

Inquiry learning (5) 0.057 0.435** 0.469** 0.262 1

Reflective thinking (6) 0.025 0.480** 0.297* 0.345* 0.689** 1

Statements for collaboration (7) 0.001 0.579** 0.507** 0.369* 0.624** 0.490** 1 Note. * Significance at 0.05. ** Significance at 0.01.

Conclusion

Result shows that the participants’ collaboration is highly significant to their CILES preferences.

While, there seems to be no significant effects of learning style towards the participants’ CILES

preferences. Furthermore, collaboration is seen as a highly correlated factor for the constructivist

learning environment. In essence, as SNS learning environment becomes more and more common,

educators should be careful in designing the tasks involve. It is hoped that this study will shed light to

and in essence determine how SNS affects learning.

Acknowledgements

This work is supported in part by the Taiwan National Science Council under grant numbers NSC

101-2410-H-262-011, NSC 100-2511-S-262-004, and NSC 99-2632-S-262-001-MY3.

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