Does Technology = More Knowledgeable Other? An .../67531/metadc... · disc. The students weren’t allowed to use the one computer in the classroom—it was for the teacher’s use

APPROVED: Carol D. Wickstrom, Major Professor James D. Laney, Committee Member Endia Lindo, Committee Member Janelle B. Mathis, Committee Member James D. Laney, Chair, Department of Teacher

Education and Administration Jerry R. Thomas, Dean, College of Education Mark Wardell, Dean of the Toulouse Graduate

School

DOES TECHNOLOGY = MORE KNOWLEDGEABLE OTHER? AN INVESTIGATION OF THE EFFECTS

OF AN INTEGRATED LEARNING SYSTEM ON THE LITERACY LEARNING

OF EMERGENT READERS

Rebecca S. Putman, B.S., M.Ed.

Dissertation Prepared for the Degree of

DOCTOR OF PHILOSOPHY

UNIVERSITY OF NORTH TEXAS

August 2014

Putman, Rebecca S. Does Technology = More Knowledgeable Other? An Investigation

of the Effects of an Integrated Learning System on the Literacy Learning of Emergent Readers.

Doctor of Philosophy (Curriculum and Instruction – Language and Literacy Studies), August

2014, 139 pp., 13 tables, 7 illustrations, reference list, 227 titles.

Professionals in education continue to explore technology as a way to instruct young

students, and there is an accompanying belief that this technology can make an educational

and academic difference. Despite the high percentage of young students in classrooms using

technology, the impact of this technology on the early literacy skills of young children remains

largely unknown. Guided by Vygotsky’s social learning theory, this study reports a 24-week

investigation on whether regular use of Istation®, an integrated learning system used by

approximately 3,000,000 students in the United States, had an effect on the early literacy

achievement of children in twelve kindergarten classrooms. A mixed-method, quasi-

experimental design was constructed using propensity scores. Also investigated were the

effects of the level of teacher literacy support on early literacy achievement and the interaction

between Istation® use and the level of teacher literacy support. A descriptive discriminant

analysis was performed to determine the main effect of Istation®. The level of teacher support

and the interaction effect was then tested using a multivariate between-subject analysis.

Results indicated that Istation® did have a statistically significant effect on the early literacy

skills of the 72 kindergarten students studied and was able to explain 17.7% of the variance in

group differences. Hearing and recording sounds and letter sound knowledge were the main

contributors to group differences. Teacher literacy support and the interaction between

teacher support and Istation were not significant. This study considers the relationship between

technology and early literacy and concludes that Istation® can serve as a more knowledgeable

other as students develop some early literacy skills; however, teachers are still needed to

provide complete literacy instruction for young students.

ii

Copyright 2014

by

Rebecca S. Putman

iii

ACKNOWLEDGEMENTS

Nietzsche was right: That which does not kill us makes us stronger. After this

dissertation, I am as strong as ever. When I didn’t think I had the strength to collect one more

piece of data or write one more word, I relied on the strength of others. I would like to thank

my committee members (Dr. Jim Laney, Dr. Endia Lindo, and Dr. Janelle Mathis) for their

guidance and wisdom along the way. Dr. Carol Wickstrom, my committee chair, was always

there to support, to encourage, and to offer wise words of advice.

Throughout this process, I always had the support of my fellow doc students, Kathy

Dixon and Lois Knezek. Kathy and Lois were always willing to discuss, edit, revise, and vent with

me. Their friendship during this process has been invaluable, and I will be forever grateful for

their never-ending support and encouragement.

I couldn’t have done this without my incredible parents, Lori and Tim Smith. They’ve

been my teachers for over 40 years now, and they have always encouraged me to follow my

dreams. I am grateful for their immeasurable support and encouragement during this process.

Last, but certainly not least, I would like to thank my family. My husband, Robert, has

been my biggest supporter and cheerleader along the way, never once complaining about the

long hours and sacrifices that our family had to make for me to get this degree. I couldn’t have

done it without his love and encouragement. I started this degree when my kids were young.

They grew up with mommy in school. It’s all they know. And they love me no matter what.

DISSERTATION became a bad word in our house, and they will probably cheer the loudest

because it is done. No, this dissertation didn’t kill me. It made me stronger--thanks to the love,

support, guidance, and encouragement of those around me. I am blessed.

iv

TABLE OF CONTENTS Page

ACKNOWLEDGEMENTS ................................................................................................................... iii LIST OF TABLES ................................................................................................................................. v LIST OF FIGURES .............................................................................................................................. vi INTRODUCTION AND OVERVIEW .................................................................................................... 1 DOES TECHNOLOGY = MORE KNOWLEDGEABLE OTHER? AN INVESTIGATION OF THE EFFECTS OF AN INTEGRATED LEARNING SYSTEM ON THE LITERACY LEARNING OF EMERGENT READERS .... 11

Introduction ...................................................................................................................... 11

Methods ............................................................................................................................ 22

Results ............................................................................................................................... 35

Discussion.......................................................................................................................... 41 APPENDIX A OBSERVATION CODING MATRIX FOR LEVEL OF TEACHER LITERACY SUPPORT ....... 55 APPENDIX B TEACHER SURVEY OF LITERACY PRACTICES ............................................................. 60 APPENDIX C PROFILE OF INTEGRATED LEARNING SYSTEM IN STUDY .......................................... 62 APPENDIX D EXTENDED LITERATURE REVIEW .............................................................................. 71 APPENDIX E ADDITIONAL METHODOLOGY................................................................................... 97 APPENDIX F ADDITIONAL RESULTS ............................................................................................. 117 COMPREHENSIVE REFERENCES ................................................................................................... 123

v

LIST OF TABLES

Page

1. Number of Articles on Emergent Literacy in the Top Educational Technology Journals ... 7

2. Demographics of Six Schools Within District A and District B .......................................... 26

3. Demographics of Twelve Teachers by Group ................................................................... 26

4. Demographics of Study Participants by Group ................................................................. 27

5. Teacher Profiles Matrix for Low, Medium, and High Levels of Literacy Support ............. 31

6. Means and Standard Deviations on the Six Literacy Concepts for ® vs. Control ............. 37

7. Wilks’ Lambda and Canonical Correlation for Two Groups on Box-Cox Transformed Data ........................................................................................................................................... 38

8. Standardized Discriminant Function and Structure Coefficients for Transformed Data . 39

9. Means and Standard Deviations for Nonsignificant Teacher Support Main Effect.......... 40

D.1. Definitions of Technology, CAI, and ILS ............................................................................ 93

F.1. Skewness of Data Before and After Box-Cox Transformation Procedures (xnew = (xλ-1)/λ) ......................................................................................................................................... 118

F.2. Mean Differences on Literacy Skills as Measured by Level of Teacher Support ............ 118

F.3. Group Means According to Istation® Use and Level of Teacher Support ...................... 120

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LIST OF FIGURES

Page

D.1. Technology as a deliverer of literacy ................................................................................ 83

D.2. Technology as a site for interaction around texts ............................................................ 87

D.3. Technology as a medium for meaning-making ................................................................. 89

E.1. Diagram of the research design ........................................................................................ 99

E.2. Diagram of the variables and outcomes for Research Question 1 ................................. 100

E.3. Diagram of the variables and outcomes for Research Question .................................... 101

E.4. Example of observation worksheet ................................................................................ 108

1

INTRODUCTION AND OVERVIEW

It is reasonable to consider how new technologies intersect with traditional instruction and whether those technologies add anything beyond what might be accomplished more efficiently and cost effectively using conventional [instruction].

Labbo and Reinking

Not too many years ago, kindergarten classrooms were filled with free play centers,

puppets, finger paints, and puzzles. Today, these same classrooms are often filled with word

walls, worksheets, assessments, and various kinds of technology. There is an increased

emphasis on academic skill-building, particularly literacy, in kindergarten. In a study on the

changing landscape of kindergarten classrooms, Bassok and Rorem (2014) reported that the

average time spent on literacy in kindergarten classrooms rose 25% from 1998 to 2006 while

time spent on all other subjects decreased. With increasing time spent on literacy in

kindergarten, a logical follow up is to investigate the strategies and approaches teachers are

using to instruct students in early literacy.

A large body of research has documented the significance of early literacy instruction

and its effects on short- and long-term academic success (e.g., Adams, 1990; Anderson, Hiebert,

Scott, & Wilkinson, 1985; Bus & vanIJzendoorn, 1999; Bus, vanIJzendoorn, & Pellegrini, 1995;

International Reading Association and National Association for the Education of Young Children,

1998; Juel, 2006; National Early Literacy Panel [NELP], 2008; National Institute of Child Health &

Human Development, 2000; Snow, Burns, & Griffin, 1989; Sulzby & Teale, 1991). Furthermore,

research has shown that children who do not make sufficient progress during these early years

remain at risk throughout their schooling (Barnett, 1995; Campbell, Ramey, Pungello, Sparling,

2

& Miller-Johnson, 2002; Cunningham & Stanovich, 1997; Hanson & Farrell, 1995; Juel, 1991;

Shaywitz, 2004; Stanovich, 1986).

While most agree that kindergarten is an important element in creating literate and

successful students, there is considerable variation in the strategies and environments that are

used to encourage early literacy success in kindergarten classrooms. Many school districts are

increasingly turning to technology as a way to instruct their young students; however, there is

very little research to support its use as an effective tool in kindergarten classrooms.

Personal Connection to the Research

As a researcher, it is important to examine my personal connection to the research and

consider how my own story affects the way that I approach and view literacy and technology.

For the first five years of my teaching career, I taught in classrooms with deaf preschoolers and

second graders. These kids often came to school with little to no language. Not surprisingly,

these students struggled with language and literacy skills. I was always searching for ways to

encourage their language development so that they could eventually learn to read and write

proficiently. Beyond hearing aids and assistive listening devices, very little technology was

incorporated into our curriculum. It was a banner day when we got one of the first digital

cameras ever made. The camera was huge, and it stored the photographs on a large floppy

disc. The students weren’t allowed to use the one computer in the classroom—it was for the

teacher’s use only. In 2000, I started teaching hearing kindergarteners. We had two computers

in the classroom. The children were allowed to play game-like educational programs on CD-

ROMs provided by the district. We would also visit the computer lab once a week and use art-

based programs to create images related to our studies or visit new websites, such as

3

PBSKids.org to play games. In general, technology was not integrated into the curriculum;

instead, it supplemented the curriculum and was often used as a reward or something to be

used once work was done.

Once my own children started school, several years later, I noticed many changes in how

technology was being used in the classroom. There were interactive white boards in every

classroom. Students visited the computer lab often and had access to various kinds of

technology in the classroom. My own kids were asked to use technology during assignments,

and technology was being integrated into the curriculum regularly. Last year, I heard about a

new computer program, Istation®, being used in the schools on the news. A few months later,

my own kids came home talking about using Istation® at school. When I met with their

teachers, they showed me fancy graphs from Istation® with lines indicating that my kids were

making progress over time. The teachers were excited that the program was aligned with the

state learning standards, and that they could generate reports of student progress at any time

that would inform their instruction. I started researching Istation®, trying to find out more

about this new program. Surprisingly, I couldn’t find much beyond the company website. I

searched the academic journals--there was no published research on Istation®. I emailed

Istation® to find out how many students were using their program, but the company refused to

provide information on the number of users or the cost of their product. Anecdotal evidence

suggested that schools all over the United States are using Istation®, and there have been

statewide implementations of Istation® in both Texas and South Carolina. Using inductive

reasoning, I estimated that close to 3,000,000 students are currently using Istation®. I was

surprised that states and districts (including my own) would invest considerable time and

4

money in a program with no research to support its effectiveness. Furthermore, I was curious if

Istation® really could add anything beyond what might be accomplished more cost effectively

using traditional instruction.

The reality of educational technology is that it is ubiquitous, and it is a likely a

permanent component of the early literacy curriculum. Because of this new reality, the goal for

me and other researchers is to investigate how to effectively incorporate and integrate this

ever-changing and dynamic technology into the curriculum.

Problem Statement

[The] early childhood dimension is even more radically under-researched than other age ranges with respect to new technologies and literacy development.

Lankshear and Knobel

Despite the high percentage of young students in classrooms using technology, the

impact of technology on the early literacy skills of young children remains largely unknown

(Hisrich & Blanchard, 2009). In fact, there is a large amount of controversy and disagreement

over how to effectively integrate technology into the early literacy curriculum in a meaningful

way (Burnett, 2010; Paterson, Henry, O’Quin, Ceprano, & Blue, 2003; Tracey & Young, 2007).

This controversy is caused, in part, by the scarcity of research investigating the relationship

between technology and the development of early literacy skills (Kamil & Lane, 1998; Labbo &

Reinking, 1999; Lankshear & Knobel, 2003; Tracey & Young, 2007). In 2000, the National

Reading Panel report reviewed the research on computer-assisted instruction [CAI] (National

Institute of Child Health and Human Development [NICHHD], 2000). The report concluded that

despite the high interest and use of technology in the classroom, there is very little systematic

research on technology’s effect on literacy. Other researchers have also acknowledged the

5

lack of research, with Labbo and Reinking (1999) noting, “the research pertaining to the use of

new digital technologies in literacy instruction is by any measure broad and shallow rather than

focused and deep” (p. 480).

There have been several studies that have investigated the number of articles on

technology in the major literacy journals, and their findings support the claim that there is a

dearth of empirical research on the relationship between technology and literacy (Andrews,

2004; Burnett, 2009; Kamil & Lane, 1998; Lankshear & Knobel, 2003; Tracey & Young, 2007). In

their investigation of articles published within four major literacy journals (Reading Research

Quarterly, Journal of Literacy Research, Research in the Teaching of English, and Written

Communication) between 1991 and 1995, Kamil and Lane (1998) found only 2.7% of the articles

focused on the relationship between technology and literacy. Tracey and Young’s (2007)

replication of Kamil and Lane’s search found only 4.9% of the articles related to technology and

literacy during the period from 2002 to 2007. Also worth noting is the fact that most of the

articles located in these searches did not report empirical research; instead, the articles were

often theoretical in nature. This gap in the research is even more marked with respect to early

literacy. After a similar review of the research on new technologies in early childhood journals,

Lankshear and Knobel (2003) suggested that the “early childhood dimension is even more

radically under-researched than other age ranges with respect to new technologies and literacy

development” (p. 59).

My own investigation of the top five educational technology journals revealed a similar

pattern. To begin my review, I used the Journal Citation Reports® Social Sciences Edition to

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locate the five educational technology journals with the highest impact factors. Initially, I

identified the following educational technology journals:

1. Computers and Education (impact factor = 2.775);

2. Journal of Computer Assisted Learning (impact factor = 1.632);

3. Educational Technology Research and Development (impact factor = 1.522);

4. Australian Journal of Educational Technology (impact factor = 1.363); and

5. British Journal of Educational Technology (impact factor = 1.313).

After further investigation, I discovered that the Australian Journal of Educational Technology

recently shifted its focus to higher education technology only. In its place, I added Educational

Technology and Society (impact factor = 1.171) to my review.

To begin my electronic review, I went to the home pages of the five journals. I searched

the home pages for articles in the journals for a period of five years (2008-2013), using the key

words, “emergent literacy” and “early literacy.” I did not include any search terms related to

technology because I assumed that technology would already be the focus in journals devoted

to educational technology. After an initial search, I noticed that many researchers use the term

“early reading” rather than “early literacy.” Based on this observation, I added “early reading”

as a key word for my search. This added search term helped to locate a couple additional

articles related to early literacy. I read the abstracts of all articles located with the key words

and considered any article that investigated or reviewed educational technology, of any kind,

with a preschool, kindergarten, or first grade population. Using the Academic Search Complete

database, I confirmed the results using the journal titles and identical key words.

7

As shown in Table 1, my results further support Lankshear and Knobel’s (2003) earlier finding

that emergent literacy and technology is significantly under-researched. In fact, my review

found that less that .5% of the articles in the top five educational technology journals addressed

the topic of emergent literacy.

Table 1

Number of Articles on Emergent Literacy in the Top Educational Technology Journals

Journal Number of Articles on Early/Emergent Literacy

(2008-2013) Computers and Education 10 out f 1240 Journal of Computer Assisted Learning 0 out of 228 Educational Technology Research and Development

1 out of 222

British Journal of Educational Technology 2 out of 541 Educational Technology and Society 0 out of 496 Total 13 out of 2727 (.47%)

This lack of research on technology and early literacy belies the continued increases in use of

technology in early education and makes it difficult for school districts and educators to make

informed decisions about integrating technology effectively into the early literacy curriculum.

While the focus on the role of technology in early literacy instruction is important, there

is another equally important aspect to consider—the money spent on this technology. A study

by an independent research company predicts that annual spending on educational technology

in the United States will increase to $4.9 billion in 2013 and top $6.8 billion in 2015 (NeXt Up

Research, 2011). These amounts are staggering and reflect the escalating use of technology in

education. Increasing numbers of school districts, wooed by big software developers, are

purchasing expensive new technologies, anticipating significant gains and progress in literacy

skills. In addition, legislative mandates, such as the No Child Left Behind Act, often focus on

8

early reading skills in an attempt to address perceived problems in reading achievement

(Paterson, et al., 2003). These mandates put pressure on districts to find quick solutions that

are considered “teacher-proof”. Educational technology is often their solution. As Cuban

(2001) notes,

To educators, dependent on voters and taxpayers for funds and political legitimacy, it often matters little whether the new technology is costly and fully tested to do what vendors and promoters say it can do. Pressed by parents, business leaders, public officials, and computer vendors, few school boards and administrators can resist the tidal wave of opinion in favor of electronic solutions to education’s age-old problems. (p. 192)

Despite the lack of thought that often goes into purchasing these costly technologies, additional

independent research on the relationship between technology and literacy is needed in order

to justify (or discourage) districts’ large expenditures and inform their decisions about how to

integrate technology into the instructional curriculum (Tracey & Young, 2007).

Research Questions

Reviews of the literature have shown that there is a large gap in the research on

determining the effects of technology on young learners’ literacy achievement, particularly

from a sociocultural perspective (Paterson et al., 2003; Tracey & Young, 2007). Given the

relevance of this topic to the educational system and the lack of research, the purpose of this

research study was to investigate the complex relationship among technology, teachers, and

early literacy instruction in twelve kindergarten classrooms from an emergent literacy

perspective. Another purpose of this study was to investigate whether technology was an

adequate substitute for the “more knowledgeable other” in the classroom. As part of this line

of inquiry, this study explored whether technology can serve as a digitally-mediated cognitive

and language tool for students as they develop emergent literacy skills. To accomplish this

9

purpose, kindergarten classrooms from one school district using Istation® were matched with

kindergarten classrooms in another school district, which were not using literacy software as

part of their kindergarten literacy curriculum. The following questions guided the study:

1. What effects does the Istation® reading program have on the literacy learning of kindergarten students in six different classrooms? Is this learning significantly different than that of comparable children in classrooms without the Istation® program?

2. What effects does the level of literacy support provided by teachers in the classroom have on the literacy learning of the kindergarten students?

3. Is there an interaction between use of Istation® technology and the level of teacher literacy support in the classroom?

Research Methods

Most studies that attempt to assess the benefits of [technology] to supplement reading instruction do not include adequate controls for teacher and classroom variables, and these variables may have a significant impact on the academic performance of young children.

Macaruso and Walker

Based on the nature of the research questions, this investigation was done using an

embedded mixed methods approach (Teddlie & Tashakkori, 2009). In embedded mixed

designs, the researcher embeds qualitative data within a quantitative investigation. The first

quantitative stage measured the gains made in literacy achievement by students using

technology and students not using technology. A second qualitative stage, embedded within

the first stage, collected observational and interview data on the teachers and classrooms

within these twelve classrooms. By examining teacher and classroom variables through

interview and observation, I was able investigate factors other than Istation® that had an effect

on participants’ literacy learning. I also attempted to control for significant variables using

propensity score matching during the data analysis phase.

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Organization

This introduction provides an overview of my study, explains the relevance of the topic

and method, and offers my personal connection to the research. My research article, with

more detailed descriptions and results from the study, follows the introduction and offers

discussion around the topic of technology and the “more knowledgeable other.”

In order to provide a more complete understanding of the research, I provide additional

information in the appendices that are not included in the article. A coding framework and

teacher survey from the qualitative portion of the study are included in Appendices A and B

while detailed information about Istation® is provided in Appendix C. Appendix D offers a more

detailed and thorough review of the literature related to education and technology. I provide

additional details about the methods used in the study in Appendix E. Finally, I present

additional results in Appendix F.

11

DOES TECHNOLOGY = MORE KNOWLEDGEABLE OTHER? AN INVESTIGATION OF THE EFFECTS OF

AN INTEGRATED LEARNING SYSTEM ON THE LITERACY LEARNING OF EMERGENT READERS

Introduction

There are few areas of universal agreement among educators and the general public;

however, most would agree with the idea that creating literate and successful students is a

fundamental goal of education. This goal of creating literate students begins early. An

extensive body of research has documented the significance of early literacy instruction and its

effects on later academic success (e.g., Adams, 1990; National Early Literacy Panel [NELP], 2008;

National Institute of Child Health & Human Development [NICHHD], 2000; Snow, Burns, &

Griffin, 1989; Sulzby & Teale, 1991).

Because of the importance of developing early literacy skills, researchers have focused

their efforts on identifying variables that support and facilitate early literacy success (Adams,

1990; Clay, 1991; NELP, 2008; Snow, Burns, & Griffin, 1989). Overall, the strategies and

environments utilized in early literacy classrooms are diverse; however, one tool that is used in

most early literacy classrooms is technology. Recent research indicates that 98% of elementary

school classrooms have computers in the classroom, with 75% of the teachers reporting that

they use the technology regularly (National Center for Educational Statistics, 2010).

Educational Technology

“Technology” is a broad and somewhat vague term in education. Technology can refer

to anything from computers to electronic games to interactive smart boards to hand-held

electronic devices. Likewise, research on educational technology is wide-ranging and focuses

on various applications, populations, and purposes. Because of the diverse focus of the

12

research, it is often difficult to generalize findings and draw definitive conclusions about the

role and effectiveness of technology. Furthermore, making informed decisions about

educational technology is virtually impossible because few published articles on technology are

research studies that evaluate the effectiveness of specific applications of technology; instead,

most articles are theoretical in nature or are descriptions of how technology is used in the

classroom (Cassady & Smith, 2005; Lankshear & Knobel, 2003). In describing previous research

on the effects of technology on literacy learning, Cassady & Smith (2005) noted, “the primary

theme has been that there is limited empirical research demonstrating the effects of

technology, with the bulk of research in areas such as multimedia and hypermedia for children

providing theoretical arguments rather than research-based outcomes” (p. 363).

Integrated Learning Systems (ILS)

History. The specific technological focus of this study is integrated learning systems (ILS).

ILS are adaptive sequence systems that adjust instruction based on individual differences in

students’ learning (Lee & Park, 2007). These systems are fully integrated with the curriculum

and are based on the concept of mastery learning. If a student masters a skill, the student

progresses to the next skill. If the student fails to master a skill, the computer adapts and

presents remedial information, reassessing until the student achieves mastery of the skill.

Integrated learning systems (ILS) were first noted in schools in the 1970s and 1980s.

These initial ILS were teacher-independent systems that covered a comprehensive curriculum

and provided assessment data on the students (Paterson et al., 2003). ILS gained favor because

of issues with educational technology during this time (Becker, 1992). For example, most

computer software was poorly designed and difficult to use (Paterson et al., 2003). Further,

13

most teachers were uncomfortable with technology as a classroom tool (Paterson et al., 2003).

ILS were thought to overcome these obstacles because they were “research-supported reading

programs to enhance reading achievement and technological interventions that promise quick

improvement with their ‘teacher-proof’ programs” (Paterson et al., 2003, p. 175). Early ILS were

based on behavioral theories about learning and used reinforcement, feedback, shaping,

fading, and programed instruction (Maddux & Willis, 1992). As Clements (1985) noted, many of

the early ILS emphasized “content rather than process and the mechanical rather than the

meaningful” (as cited in Paterson et al., 2003, p. 175).

In the 1980s, ILS lost favor as the cognitive revolution, computer science, and the social

sciences had an increasing influence on education and teaching (Maddux & Willis, 1992).

Educators moved towards more constructivist theories and the principles of Vygotsky’s social

constructivism (Maddux & Willis, 1992). Because of this shift in thinking (and a loss of profits),

software developers started examining how computers might assist students in the

construction of meaning around literacy. The ILS regained favor in the 1990s in reaction to a

perceived literary crisis (Paterson et al., 2003). In a review of the advantages of the newer ILS,

Becker (1992) noted that the newer systems offered individualized instruction and flexible time

and data management systems; however, his review did not provide an endorsement of ILS,

with Becker emphasizing that there was not enough credible research to say that ILS was better

than teacher instruction.

In the late 1990s and 2000s, ILS vendors started marketing their products specifically to

very young children, in part because innovations in graphics, animation, and sound made the

systems more engaging (Becker, 1992; Paterson et al., 2003). The companies marketed these

14

new and improved ILS as “highly effective, systematic approaches to literacy instruction that

will help emergent readers acquire and practice skills in basic print concepts, the alphabetic

principle, phonological awareness, word identification, and other reading subskills” (Paterson et

al., 2003, p. 176). Since the introduction of ILS to young children, very few researchers have

investigated the software developers’ claims that ILS help develop early literacy skills.

Research. Several researchers have noted the lack of high-quality research on the

effectiveness of ILS on literacy achievement (Cassady & Smith, 2004; Paterson et al., 2003;

Tracey & Young, 2007). Many of the studies on ILS and literacy skills have produced somewhat

mixed results, and it is difficult to draw definitive conclusions. In addition, conclusive

recommendations for integrating technology into an early literacy curriculum are hard to make

because early literacy skills are defined and assessed very differently across studies. The

available research suggests that ILS generally have a positive effect on early literacy skills. For

example, Bauserman, Cassady, Smith, and Stroud (2005) investigated the efficacy of PLATO’s

Beginning Reading for the Real World on kindergarteners’ emergent reading skills. Their study

found large effect sizes for phonological awareness and concepts about print (Bauserman et al.,

2005). Both Tracey and Young (2007) and Cassady and Smith (2004, 2005) investigated the

effectiveness of another popular ILS, the Waterford Early Reading Program. The results from

these three studies indicated that the Waterford Early Reading Program had a statistically

significant impact on young students’ early literacy skills, particularly their phonological

awareness skills. In addition, Cassady and Smith’s (2005) study found the ILS to be particularly

effective for students with the lowest initial reading skills. Conversely, Paterson et al. (2003)

15

studied the same ILS and found no benefits; instead, the researchers found that literacy

facilitation by the teacher and time were more important to early literacy success.

Despite the mixed results, there are generalizations that can be made from the

research. First, ILS should not supplant teacher-led instruction; instead, ILS appear to be most

effective when integrated into the existing classroom curriculum (Cassady & Smith, 2004). In

addition, Cassady and Smith (2004) noted two additional generalizations about technology and

literacy in their review of ILS: “(a) Gains in research on computer-based tools are typically short-

lived due to the limitations in scope and content in most computer packages, and (b)

methodological design issues have hindered the examination of the impact of ILS in realistic

instructional settings” (p. 950).

Overall, studies on the impact of ILS on early literacy skills have generally found positive

effects; however, these studies often focus narrowly on one population or one aspect of

literacy while ignoring the broader context of technology use in early literacy classrooms.

Many researchers assert that there just is not enough evidence to endorse the widespread use

of ILS in classrooms (Blok et al., 2002; Cassady & Smith, 2005; Paterson et al., 2003).

Istation® Treatment

The ILS that is the focus of the current study is Istation®. An accurate count of Istation®

users is unavailable; however, a description of Istation® on the EdSurge website reports that

over 900,000 students in over 407 districts use Istation® (EdSurge, n.d., Who Is Using It section).

This number appears to grossly underestimate the number of users since both Texas and South

Carolina have recently implemented and funded the use of Istation®, state-wide. Through a

program called Texas SUCCESS, all Texas public school students in Grades 3-8 have free access

16

to Istation® Reading at school and at home. According to the most updated enrollment reports

from the 2011-2012 school year, there are 2,231,934 students in Grades 3-8 in Texas (Texas

Education Agency, 2012, p. 15). Similarly, the South Carolina Success Program recently

provided funding for free access to Istation® Reading for all students in Grades pre-K through 8

in public schools. For the 2011-2012 school year, South Carolina had an average daily

attendance of almost 500,000 for Grades K-8 (South Carolina State Department of Education,

2011-2012). Based on these numbers alone, the actual number of Istation® users is probably

much higher than the 900,000 reported by the EdSurge website. Despite the high number of

users, the statewide implementations, and the associated costs of Istation® Reading, there are

no published reports on Istation®.

Theory. The content of Istation® Early Reading is organized around five domains of

reading: phonemic awareness, alphabetic knowledge, vocabulary, comprehension and fluency

(Mathes, Torgesen, & Herron, 2012). These domains are based on the five pillars of reading

presented in the National Reading Panel’s (2000) The Report of the National Reading Panel:

Teaching Children to Read (NICCHD, 2000).

How Istation® works. The Istation® program was developed around four main

components: assessment, instruction, reporting, and teacher tools. These four components are

aligned and integrated into the state curriculums and are part of what makes Istation® an ILS.

In fact, Istation® has aligned each of its lessons with the common core objectives and with the

learning objectives of 42 states plus the District of Columbia and the US Virgin Islands (Istation,

n.d., Instructions: Correlations section).

Istation® begins by having students log in and take an assessment that lasts 40 minutes

17

or less (Mathes, Torgensen, & Herron, 2012). These assessments attempt to determine

students’ abilities in the five critical reading areas and are mainly multiple-choice, with a few

fill-in-the-blank questions. Using item response theory and computer adaptive testing

algorithms, the program adapts, varying the difficulty and number of questions depending on

how the student responds (Mathes, Torgesen, & Herron, 2012). Based on the assessment

results, Istation® places the student within the reading curriculum.

After students are assessed, they receive systematic and explicit direct instruction and

practice on their individual levels. The instruction follows a typical lesson plan format, including

an introduction, modeling, guided practice, independent practice, and an application within a

book or passage. Interactive activities, games, and animated characters such as Detective Dan

and the Digraphs are integrated into the lessons. If a student is successful during the lesson,

the program adapts and moves on to the next lesson in the Istation® curriculum. If a student

struggles during a lesson, the program will automatically adapt and reteach the skill in another

format.

Research on Technology and Literacy

Despite the high percentage of young students in classrooms using technology, including

Istation®, the impact on the early literacy skills of young children remains largely unknown

(Hisrich & Blanchard, 2009). In fact, disagreement exists with regard to the role of technology

in early literacy environments and to the manner in which technology is integrated into the

early literacy framework in a meaningful and effective way (Burnett, 2010; Paterson, Henry,

O’Quin, Ceprano, & Blue, 2003; Tracey & Young, 2007). Researchers have suggested that this

controversy is caused, in part, by the scarcity of research investigating the relationship between

18

technology and the development of early literacy skills (Kamil & Lane, 1998; Labbo & Reinking,

1999; Lankshear & Knobel, 2003; Tracey & Young, 2007).

Several studies investigated the number of articles on technology in the major literacy

and early childhood journals. Findings from these studies support the claim that there is a

dearth of empirical research on the relationship between technology and literacy (Andrews,

2004; Burnett, 2009; Kamil & Lane, 1998; Lankshear & Knobel, 2003; Tracey & Young, 2007).

Overall, these investigations have found very little empirical research on technology and

literacy, with less than 5% of the articles reporting findings on technology and literacy. This gap

in the research is even more marked with respect to early literacy.

These findings are particularly troublesome considering the enormous amount of

money that is spent on educational technology. A 2011 report on Unleashing the Potential of

Educational Technology by the White House notes that annual spending on technology in K-12

educational settings in the United States was around $2.9 billion in 2010 (White House Council

of Economic Advisors, 2011). A study by an independent research company predicts that

annual spending on educational technology in the United States will increase to $4.9 billion in

2013 and top $6.8 billion in 2015 (NeXt Up Research, 2011).

Finally, most of studies that have examined technology and early literacy have done so

from a cognitive processing theoretical perspective, which as Lankshear and Knobel (2003)

note, “marginalizes the interest many early childhood educators and researchers have

in…research that looks at social and cultural aspects of literacy acquisition in relation to new

technologies” (p. 63). By marginalizing the importance of social aspects of early literacy

acquisition, most studies on technology and early literacy fall short in their attempts to answer

19

the question about the role and integration of technology from an emergent literacy

perspective.

Current Investigation

Given the relevance of this topic to the educational system and the lack of research, the

purpose of this present study was to investigate the effect of technology and teacher literacy

support on the early literacy learning of young readers from an emergent literacy perspective.

Specifically, this study investigated whether regular use of the Istation®, an integrated learning

system, promoted the early literacy achievement of children in kindergarten classrooms.

Another purpose of this study was to investigate whether technology is an adequate substitute

for the “more knowledgeable other” in the classroom. In other words, did this particular

application of technology scaffold students’ learning as effectively as a classroom teacher? The

research questions considered for the current investigation were:

1. What effects does the Istation® reading program have on the literacy learning of kindergarten students? Is this learning significantly different than that of comparable children in classrooms without the Istation® program?

2. What effects does the level of literacy support provided by teachers in the classroom have on the literacy learning of the kindergarten students?

3. Is there an interaction between use of Istation® technology and the level of teacher literacy support in the classroom?

Theoretical Framework

This study was framed using the ideas of Labbo and Reinking (1999), who suggest that

studying literacy instruction and technology is a “process of negotiating multiple

realities…because new technologies intersect with a broad range of issues and practices in

literacy instruction” (p. 488). While the full range of issues and practices in literacy instruction

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are beyond the scope of this study, the data was interpreted in light of the complex relationship

between technology and literacy, and multiple realities were considered using a mixed-

methods approach.

There are two main ways to frame the relationship between literacy learning and

technology. The differences between the two perspectives are subtle, yet important. One

perspective is that children learn from a computer. Labbo and Reinking (1999) suggest that

learning from a computer “implies a focus on short term and specific learning outcomes in

which…the computer tends to be viewed as a device that is passive and essentially neutral in

regard to specific learning outcomes” (p. 483). Research from this viewpoint tends to be

atheoretical and focuses on behaviorist notions of learning (Labbo & Reinking, 1999). On the

other hand, children can learn with a computer. From this perspective, the focus is on “long-

term, broader, less specific, and sometimes incidental outcomes in which the computer plays

an active role” (Labbo & Reinking, 1999, p. 483). This perspective acknowledges the broader

cognitive and social components of learning using technology. Research from this viewpoint

tends to be guided by social theories of learning and focuses on the role of the technology as

well as the multiple realities of combining technology and learning (Labbo & Reinking, 1999).

For this study, I assumed that children learn with a computer.

Because of this study’s emphasis on an emergent literacy perspective, a framework

based on Vygotsky’s social learning theory (1978) seemed most relevant for investigating how

students interact with technology in the classroom. Vytgotky’s theory of learning assumes that

both teaching and learning are highly shared and interactive activities. His concept of the social

construction of knowledge is an important component of emergent literacy research. In his

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theory, Vygotsky suggested that the construction of meaning is always socially mediated,

influenced by both present and past social interaction. In addition, he viewed learning as a

transactional event, a mutually-shaping exchange between the child, the environment, and the

teacher (or the more knowledgeable other). Specific to literacy, children develop

understandings about language, reading, and writing through social interactions that occur with

more knowledgeable others. In most educational settings, teachers scaffold these interactions

through the zone of proximal development [ZPD], defined as the “distance between the actual

developmental level as determined by independent problem solving and the level of potential

development as determined through problem solving under adult guidance or in collaboration

with more capable peers” (Vygotsky, 1978, p. 86). The ZPD is used to negotiate the gap

between development and learning. The concept of the zone of proximal development or

scaffolding can be extended to examine the support offered by technology.

Educational technology can often serve as the facilitator or guide in what was previously

a teacher-student interaction. In general, the goal of many educational technology programs is

to emulate or copy the instructional methods of a human teacher (Johnson, Perry, & Shamir,

2010). Specific applications of technology attempt to take on the role of the teacher by giving

immediate feedback on responses and by providing further practice at the students’

instructional levels (McLoughin & Oliver, 1998). By giving feedback and adapting instruction

based on a student’s individual needs, educational technology attempts to provide instruction

in the student’s ZPD. In this way, technology becomes a digitally-mediated cognitive and

language “tool” for the students as they develop emergent literacy skills by scaffolding their

learning (Hisrich & Blanchard, 2009). To the degree that technology can simulate this human

22

interaction will determine its success as a more knowledgeable other and its success in

producing socially created knowledge for early literacy learners. Because of the importance of

social interactions, particularly those in which teachers scaffold children’s early literacy

development, this study carefully considered whether technology can be an effective mediator

between the child and the social construction of literacy knowledge, serving as a more

knowledgeable other in a classroom.

Methods

Research Design

Based on the nature of the research questions, this investigation was conducted using an

embedded mixed methods approach (Teddlie & Tashakkori, 2009). As Teddlie and Tashakkori

(2009) note, “[Mixed-methods] research provides better (stronger) inferences [and] provides

the opportunity for a greater assortment of divergent views” (p. 33). The opportunity for

divergent views and multiple realities is a particularly important aspect of why this study was

conducted using a mixed-methods approach, as it aligns with Labbo and Reinking’s (1999)

multiple reality theoretical framework for researching technology and literacy.

The qualitative analysis measured the gains made in literacy achievement by students

using Istation® and students not using Istation®. A second qualitative analysis, embedded

within the first stage, collected observational and interview data on the teachers and

classrooms within these twelve classrooms. The qualitative data were then analyzed and used

to create teacher profiles to match participants in the study and to create an additional

independent variable for further quantitative analysis. In addition, by examining teacher and

classroom variables through observation and survey, I was able to more adequately account for

23

the contribution of various teacher and classroom variables when matching students and

creating control and treatment groups.

Because randomly assigning children to use or not use Istation® was not possible,

matched control and treatment groups were constructed through the use of propensity score

matching in order to control potential variation (beyond the instructional format presented) at

the participant level. This approach allows for quasi-experimental comparisons between

children in naturally occurring treatment and control groups. Propensity score matching is one

way to mimic the random selection of participants of a randomized control trial (RCT) in an

observational survey (Rosenbaum & Rubin, 1983). Because of its ability to reduce selection bias,

propensity score matching is increasingly being used in educational research (Graham &

Kurleander, 2011; Murnane & Willet, 2011).

Rosenbaum and Rubin (1983) defined propensity scores as the conditional probability of

treatment assignment based on certain observed baseline covariates. More simply, the

propensity score is the predicted probability of treatment after accounting for important

matching variables (Reutzel, Spichtig, & Petscher, 2012). The goal or objective for a researcher

using propensity scores is to select a sequence of variables, based on theory and research, that

are considered important in matching participants (Reutzel, Spichtig, & Petscher, 2012). If the

theory and history on which the researcher bases his/her selection of covariates is good, then

the model is sound and causal inferences can be made (Reutzel, Spichtig, & Petscher, 2012;

Thoemmes & Kim 2011). In early literacy research, these variables include gender (Below,

Skinner, Fearrington, & Sorrell, 2010; Chatterj, 2006), age (Huang & Invernizzi, 2012),

race/ethnicity (Chatterji, 2006), socioeconomic status (Chatterji, 2006; D’Angiulli, Siegel, &

24

Hertzman, 2004; Taylor & Schatschneider, 2010; Ready, 2010), English language learner status

(Gottardo & Mueller, 2009; Yesil-Dagli, 2011), level of literacy support by the teacher (Boonen,

Van Damme, Onghena, 2014; Konstantopoulous, 2011), and some type of baseline measure of

achievement (Bishop & League, 2006; Schatschneider et al., 2004). The propensity scores for

this study were estimated using logistic regression in which the treatment status was regressed

using the relevant covariates to create a probability score for being in the treatment group

(Austin, 2011; Shadish, Cook, & Campbell, 2002). Once propensity scores were estimated for

participants from the control and treatment groups using logistic regression, the probabilities

were then used to match students who received the treatment with those who did not receive

treatment (Austin, 2011; Reutzel, Spichtig, & Petscher, 2012). By matching participants with

similar propensity scores, the measured covariates were more equally distributed among the

treated and control groups (Austin, 2011). As Thoemmes & Kim (2011) note, “The assumption

is that the matched samples of children are identical (or at least comparable) on many

background characteristics and only differ in their [treatment] status—just as we would expect

from a randomized experiment” (p. 93). I used both theory and prior empirical research to

identify variables that influence young children’s early literacy skills. Participants for this study

were matched on the following variables: (a) Age on the first day of kindergarten, (b) gender,

(c) ethnicity, (d) free and reduced lunch status, (e) English language learner status, (f) beginning

of year letter identification score, and (g) level of literacy support provided by the teacher (low,

medium, high).

Participants

Participants for this study were chosen from 12 kindergarten classrooms within two

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north Texas suburban school districts. District A is located in a medium-size suburb while

District B is a located in a large suburb in the same area. The six treatment classrooms were

located in three schools within District A. District A integrates Istation® into its kindergarten

literacy curriculum and requires all teachers to use the program regularly. The remaining six

classrooms served as a control and were located in three schools within District B. District B

integrates technology regularly into the kindergarten curriculum; however, the district uses a

more traditional curriculum to directly instruct students in literacy.

Selection of schools. Because of the differences in the demographic data between the

two districts and in order to create a more balanced sample for matching, I used purposeful

sampling to select three comparable schools in each district. Choice of schools was based on

my desire to create a diverse sample from which to collect data. I chose one school from each

district that was not classified as Title 1, one school that was classified as Title 1, and one that

was both Title I and had a high English language learner (ELL) population. The schools were

matched as closely as possible on school size, percentage of economically disadvantaged

students, ELL population, and ethnic and minority composition.

Selection of teachers. After meeting with each the school principals, I asked the

principals to provide the names of two kindergarten teachers who would be willing to

participate in the study. All students in the kindergarten classrooms of the teachers who

volunteered were asked to participate in the study.

Student participants. One hundred fifty students returned the consent forms for the

study. The final analysis included 72 students matched through propensity score matching,

with 36 students in each of the treatment and control groups.

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Table 2 Demographics of Six Schools Within District A and District B District A (Istation®) District B (control)

Scho

ol #

1 Student Population (K-4) 659

Scho

ol #

2 459

Economically Disadvantaged 16.5% 15.1%

English Language Learners 5.3% 4.9% Ethnic/Minority Composition 26.6% 29.7%

Scho

ol #


Scho

ol #

4 383

Economically Disadvantaged 61.7% 65.4%

English Language Learners 29.2% 30.1% Ethnic/Minority Composition 80.9% 84.6%

Scho

ol #


Scho

ol #

6 529

Economically Disadvantaged 75.7% 80.1% English Language Learners 41.9% 36.1% Ethnic/Minority Composition 71.3% 88.7%

Table 3 Demographics of Twelve Teachers by Group

Istation® (n = 6) Control (n = 6)

Mean/Freq Range/% M Range/%

Years of Experience

Years Teaching 14.2 years 3-19 17.2 years 5-34

Years Teaching Kindergarten 12.8 years 3-19 12.5 years 4-33

Certificationa

Early Childhood 6 100% 6 100%

Elementary Education 5 83% 6 100%

ESL 4 67% 6 100%

Special Education 1 17% 0 0% a Percentages under certification add up to more than 100% because most teachers were certified in multiple areas.

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Table 4

Demographics of Study Participants by Group

Istation® (n = 36) Control (n = 36)

Mean/% Mean/%

Gender

Male 38.9% (n = 14) 52.8% (n = 19)

Female 61.1% (n = 22) 47.2% (n = 17)

Ethnicity

White 55.6% (n = 20) 52.8% (n = 19)

Hispanic 27.8% (n = 10) 25% (n = 9)

Black 8.3% (n = 3) 19.4% (n = 7)

Asian 8.3% (n = 3) 2.8% (n = 1)

English Language Learners 16.7% (n = 6) 22.8% (n = 8)

Free and Reduced Lunch 41.7% (n = 15) 52.8 % (n = 19)

Age on first day of kindergarten (in months) 68.42 months 67.72 months

Beginning of the year letter ID 41.69 (SD = 16.0) 44.86 (SD = 12.6)

Instrumentation/Materials

DRA2. The Developmental Reading Assessment-2 [DRA2] is a widely used, criterion-

referenced reading assessment for children in kindergarten through third grade (Beaver, 2006).

It is modeled after an informal reading assessment and uses authentic texts to measure

students’ independent reading level. I chose the DRA2 as an outcome measure for

independent reading level for this study because both District A and District B already use the

assessment to determine the reading levels of their students at mid-year and end-of-year. Both

districts conducted training on the DRA2 with their teachers within the last year and required

teachers to use the leveled books provided with the DRA2 kit and follow all assessment

28

protocols as outlined in Beaver (2006). Reliability data from the DRA2 technical manual (2009)

indicate that both inter-rater reliability estimates and rater-expert reliability estimates were

moderate to substantial.

Clay’s Observation Survey. To accurately reflect an emergent literacy perspective and

the complexity of literacy, Clay’s Observation Survey (2002) was used to measure literacy

learning. Like the DRA2, the Observation Survey of Early Literacy Achievement [OS] (Clay, 2002)

is an individually administered assessment tool that is widely used in early literacy classrooms

in the United States and is conducted in the context of authentic literacy tasks. Research

suggests that authentic literacy assessments provide a more accurate measure of young

student’s reading abilities than more standardized measures (Barnhart, 1991; Hodges, 1997;

James & Tanner, 1993; Quay & Steele, 1998; West, 1998). In addition, there is a large

variability in the early literacy skills of kindergarteners, and this variability is still present at the

end of kindergarten. The Observation Survey is able to capture and measure this variability.

Clay’s survey can be broken down into several related dependent measures. These

subskills include hearing and recording sounds in dictation, writing vocabulary, letter sound

knowledge, concepts about print, word reading, and reading level, for a total of six possible

dependent variables; however, for this study, the reading level subtest of Clay’s survey was

replaced by the DRA2.

Procedure

Project design. All students in the studied classrooms followed the district-mandated

curriculum for kindergarten for the 24-week investigational period. District A, the treatment

group, requires its teachers to use Istation® as part of the kindergarten curriculum, while

29

District B, the control, does not. All of the studied schools in District A began Istation® use by

the third or fourth week of school. The average time that each of the treatment participants

spent on Istation® was 135 minutes per week. Both District A and B base their literacy

instruction on the Texas Essential Knowledge and Skills (TEKS), which are state standards for

what students should know and be able to do at each grade level. In addition, both districts

encourage an emergent literacy approach in their kindergarten classrooms, with authentic,

integrated methods of instruction, including shared reading, guided reading and journal writing.

The current study was conducted during the 2013-2014 school year.

Baseline measure of reading achievement. Because of the diverse nature of the schools

and teachers in naturalistic inquiries, it is often difficult to obtain pretest scores that can be

used across participants for baseline comparisons. For this reason, I chose letter identification

as a baseline measure for this study. Letter identification is a widely used screening and

assessment tool in many kindergarten classrooms. Kindergarten teachers use this easy-to-

administer assessment as a way to efficiently gauge their students’ initial levels of literacy

learning. While letter identification measures do not provide a complete picture of a student’s

literacy abilities, there is considerable research on the correlation between letter identification

and word reading (Clark, Hulme, & Snow, 2005; Neuhaus, Foorman, Francis, & Carlson, 2001;

Wolf & Obregon, 1992). Other researchers have found correlations between letter

identification and future reading ability (Bishop & League, 2006; Schatschneider, Fletcher,

Francis, Carlson, & Foorman, 2004). Letter identification is also a strong predictor of reading

disabilities among kindergarten and first grade students (O’Connor & Jenkins, 1999). All of the

participating teachers collected beginning of the year letter identification data within in the first

30

six weeks of the school year. These scores were used as a baseline measure of achievement for

the propensity score matching.

Controlling for teacher variables. Each kindergarten classroom was observed for a total

of four hours during literacy instruction during February 2014. Most classrooms were observed

two times for half days, averaging two hours for each observation. Observation protocols were

adapted from Paterson et al.’s (2003) study on a similar integrated learning system. The

following data were recorded on uniform observation worksheets: (a) Description of the

classroom, (b) start/end time of activities, (c) materials used for the lesson, (d) teacher

behaviors, and (e) child behaviors.

Coding of observations. The purpose of collecting the observational data was to

determine the level of early literacy support provided by each of the participating teachers.

Prior to conducting the classroom observations, I constructed teacher profiles and a coding

framework for low literacy support, medium literacy support, and high literacy support, using

descriptions of effective early literacy practices from the research (Cunningham & Allington,

2010; Thompkins, 2014). The coding framework listed and described 15 effective literacy

practices. Each of the 15 literacy practices included a detailed three-level description for low

literacy support, medium literacy support, high literacy support (see Appendix A for the

complete coding framework).

Using the original field notes, I coded the teacher behaviors and classroom interactions

as low, medium, or high according to each of the 15 literacy practices in the matrix. Based on

patterns of support in the coding, I determined an overall profile for each teacher and placed

the teachers into one of the three levels of literacy support, as shown in Table 5.

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Table 5 Teacher Profiles Matrix for Low, Medium, and High Levels of Literacy Support Low Literacy Support Medium Literacy

Support High Literacy Support

Overall Profile Teacher spends less time on literacy instruction (<50%) and more time on other issues such as classroom management, transitions, and/or discipline. Children are primarily passive during literacy instruction and/or literacy instruction is clearly in conflict with best practices. (Paterson et al., 2003).Worksheets are common. Children are not given a lot of choice in the classroom.

Teacher spends a large percentage of his/her instructional time (50%-75%) on literacy events, but those events include less student input or choice. While there is evidence of best practice models, these attempts are not always successful (Paterson et al., 2003). Worksheets are used occasionally. Students are given some choice in the classroom. Students are sometimes active in their demonstrations of learning.

Teacher spends most of his/her instructional time (75%-100%) on literacy events. The nature of these events is congruent with best practices in early literacy and students are highly active in constructing these events (Paterson et al., 2003). Worksheets are used rarely in the classroom. Students are given choice and are active in their demonstrations of learning. Teacher offers varied levels of scaffolding throughout the day, as needed. (modeled, shared, guided, independent)

Classrooms Istation® 4 Control 4

Istation® 1 Istation® 3 Control 2 Control 3 Control 5

Istation® 2 Istation® 5 Istation® 6 Control 1 Control 6

Intercoder agreement. To establish intercoder agreement on the observational data, I

asked a language and literacy doctoral candidate, who was also a certified teacher with 11

years of experience in the lower grades, to code a random sample of four observations using

the coding framework. This check coding was done after the observations were completed.

32

After a 30-minute training session, the doctoral student coded the teachers using the original

field notes from the observations as high, medium, or low on all 15 of the effective literacy

practices and assigned each teacher an overall profile. Agreement on the overall level of

literacy support provided by the teachers in the four observations was 100%.

Research memos. Shortly after each observation, I created a research memo that

contained reflective notes about the classroom observation and teacher behaviors. I noted any

relevant comments the teacher made to me and also noted emerging patterns, insights, and

connections in the observational data.

Teacher survey. The twelve participating teachers were asked to complete a survey of

literacy practices adapted from a survey by Paterson et al. (2003). The survey had a checklist of

12 components commonly found in early literacy programs as well as open-ended questions.

The 12 components ranged from shared reading to writer’s workshop. Teachers were asked to

rate each these components on a scale from 1 to 3, based on how important the component

was to their literacy curriculum (see Appendix B). The open-ended questions on the survey

asked teachers to further explain their future goals, areas of strength in literacy instruction, and

differentiation strategies. The teachers who used Istation® were also asked about the best

features and biggest concerns regarding the program. The list of practices the teachers

identified as a critical part of their curriculum were coded as high, medium, and low literacy

support using the same coding matrix developed for the observational data. The list of practices

the teachers identified as a critical part of their curriculum were triangulated with the coding on

the teachers’ observed literacy practices as well as the research memos to confirm the level of

literacy support provided by the teachers. The individual teacher profiles provided a practical

33

synthesis of the three qualitative data sources. The teacher profiles (high, medium, low)

created from the observational data and teacher surveys were then used for two purposes: (a)

as a covariate in creating propensity scores to match students for the study, and; (b) as an

independent variable in the second and third research questions about the effect of this

support on the literacy learning of the kindergarten students.

Measuring literacy achievement. Data on participants’ literacy achievement was

collected during February 2014 from two sources:

1. DRA2: The twelve participating teachers provided students’ middle of the year DRA2

[MOYDRA2] scores to me. This teacher-administered individual assessment was

given to all participants in January 2014. This measure was used to determine

participants’ independent reading levels.

2. Observation Survey: Two trained research assistants and I individually administered

five subtests of the Observation Survey to the 150 students who returned the

consent forms. Subtests include hearing and recording sounds, writing vocabulary,

letter sound knowledge, concepts about print, and word reading. Each testing

session averaged approximately 30 minutes.

Training. The two research assistants who assisted in collecting data for this study were

certified teachers with master’s degrees in education and an average of 28 years of teaching

experience. The assistants had backgrounds in early childhood, elementary education, English

as a second language (ESL), special education, and speech pathology. Each of the research

assistants conducted approximately a third of the Observation Surveys. Assistants were trained

on the Observation Survey during a one-hour session with the researcher. Standardization of

34

the assessment was accomplished through a detailed protocol for the order of subtests,

materials, instructions during the assessment, and scoring guidelines. All assessments were

scored individually and any discrepancies were reviewed and resolved according to the

protocols established for the assessment.

Data Analyses

To determine the effect of Istation® and the effect of the level of literacy support

provided by teachers on the literacy achievement of kindergarten students, I used propensity

score estimation to match students from the treatment and control groups. For this study,

students who used Istation® were matched with students who did not use Istation®, using

variables that both theory and research have identified as having an influence on early literacy

skills. Use of propensity score matching allowed for relatively unbiased estimates of Istation®’s

causal effect on the participants’ early literacy skills, closely approximating those that could be

obtained from randomized control trials (Austin, 2011; Murnane & Willet, 2011).

The full sample of 150 students was used to match students. In the data set, 80 of these

participants were in the treatment group while 70 participants were in the control group. An

initial propensity score was estimated using the seven variables derived from early literacy

theory and research. Treated and untreated participants were matched using an optimal,

nearest neighbor with caliper matching algorithm (Austin, 2011). The caliper width used was

equal to 0.2 of the standard deviation of the logit of the propensity score (Austin, 2011, 2014).

Research has confirmed that caliper matching leads to improved balance on baseline covariates

and less bias in treatment effect estimates (Austin, 2014). When participants who used

Istation® were matched with participants who did not use Istation® based on the logit of the

35

propensity score algorithm, 36 matched pairs were formed, for a total sample of 72

participants. Once students were matched, two analyses were conducted on the data to

answer the three research questions:

1. A descriptive discriminant analysis [DDA] (Huberty, 1994) was conducted to evaluate

the effect of Istation® on the early literacy skills of kindergarteners and to determine which

variables contributed to any differences between the two groups;

2. A 2 X 3 multivariate between-subjects analysis of variance (Istation®: No/Yes X

Teacher Support: Low/Medium/High) was conducted to test for main effects for level of

teacher literacy support and to test for a multivariate interaction between Istation® and level of

teacher literacy support.

Results

Summary of Findings

The principal findings of this study are that:

1. Istation® did have a statistically significant effect on the early literacy skills of the

kindergarten students studied and was able to explain almost 18% of the variance in group

differences.

2. Differences in Hearing/Recording Sounds and Letter Sound Knowledge were the two

main contributors to the variability between the two groups. Variability in Writing Vocabulary

contributed minimally to the group differences while Concepts About Print was a suppressor

variable in the model.

3. Level of teacher literacy support was able to explain 18% of the variance between

the two groups. Overall, the model was not statistically significant; however, analysis of the

36

individual group means did reveal significant group differences on Concepts About Print,

Reading Words, and middle of the year DRA2 based on the level of literacy support provided by

their teachers.

4. The interaction effect between the Istation®/control and the level of teacher literacy

support was not statistically significant partly due to the low number of matched participants in

some cells; however, the model was still able to explain 24.5% of the differences among

students receiving different levels of literacy support from their teachers.

Data Analysis

Because the main research question focused on the effects of Istation®, the first

quantitative analysis tested for the effect of Istation® on the DRA2 and the five subtests of the

Observation Survey. While there was not a research question that used a qualitative analysis,

the teacher variable discovered during the qualitative portion of this study was used to explain

any possible differences based on the level of literacy support provided by the teacher.

Effects of Istation®. A DDA (Huberty, 1994) was used to evaluate whether students who

used Istation® and students who did not use Istation® differed in their early literacy knowledge.

Table 6 reports the means and standard deviations of the two groups regarding early literacy

achievement. Visual analysis of the group means indicated there were differences and that the

groups would be good discriminators because the separations between the groups were

moderate.

Histograms and significance tests of the data indicated a violation of the assumption of

multivariate normality (z = -8.143, p = .001). For the Letter Sound Knowledge and Hearing and

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Recording Sounds subtests, in particular, a negatively skewed distribution was evident and

univariate tests of normality showed substantial deviations from a normal distribution.

Table 6 Means and Standard Deviations on the Six Literacy Concepts for Istation® vs. Control Istation® Control

M SD M SD Middle of the Year DRA2 [MOYDRA2]

3.75 2.26 4.11 2.44

Hearing /Recording Sounds 29.97 8.80 27.28 9.68 Writing Vocabulary 19.50 11.51 16.58 9.16 Letter Sounds 51.42 3.67 48.36 7.14 Concepts About Print 16.97 3.06 17.69 2.63 Reading Words 11.94 5.51 11.61 5.62

To help the data meet normality and heteroscedasticity assumptions, the six dependent

variables were transformed using Box-Cox procedures (Osborne, 2010). Tests of the

transformed data indicated that all of the variables met the assumption of multivariate

normality. To determine if the data met the homogeneity of variance assumption, a Box’s M

test was run on the transformed data. Box’s M, F(21,18022.2) = 1.43, p = .094, was not

statistically significant, indicating that the covariance matrices for each group were

approximately equal.

To determine differences in early literacy skills between the two groups, the

transformed data were then analyzed using discriminate analysis in SPSS, version 22. Canonical

discriminant functions are used to determine if the variance in the synthetic dependent variable

can be explained by the independent variable in the model.

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As shown in Table 7, the canonical discriminant correlations data for this study indicate

that there was a correlation between the synthetic dependent variable (early literacy skills) and

the independent variable (Istation® vs. control) on Function 1 (.421) with an effect size of R2c

17.7%. This means that the use of Istation® was able to explain 17.7% of the variance in group

differences. The full model test for Function 1 was statistically significant at p = .04.

Table 7 Wilks' Lambda and Canonical Correlation for Two Groups on Box-Cox Transformed Data

Functions Wilks’ Lambda

Chi-square Df p Rc 𝑅𝑅𝑐𝑐2

1 .823 13.073 6 .042 .421 17.7%

To help determine the relevance of the dependent variables and to evaluate which of

the six variables contributed to differences in the early literacy skills achievement between the

groups, I examined the standardized discriminant function coefficients and structure

coefficients for the transformed data (Henson, 2002). Table 8 combines these two sets of

coefficients. Analysis of the data indicates that Hearing/Recording Sounds and Letter Sound

Knowledge were the dominant contributors to the differences between groups, accounting for

35.3% of the variance. Writing Vocabulary contributed minimally to group differences. The

contributions of the DRA2 and Reading Words were negligible while Concepts About Print was a

suppressor in the model.

Effect of level of teacher literacy support. To evaluate the effect of the level of teacher

literacy support, a 2 X 3 (Istation®: Yes/No X Teacher Support: Low/Medium/High) multivariate

between-subjects analysis of variance was conducted on the transformed data. Neither the

39

multivariate main effect of teacher support nor the multivariate interaction was significant;

however, both models were able to explain a meaningful amount of the variance between and

among the groups.

Table 8 Standardized Discriminant Function and Structure Coefficients for the Transformed Data Function 1 Coefficient rs rs2

Hearing/Recording Sounds

.642 .441 19.4%

Letter Sounds .615 .399 15.9% Writing Vocabulary .338 .291 8.5% Concepts About Print -1.219 -.260 6.8% MOY DRA2 -.281 -.129 1.7% Reading Words .252 .062 .3%

The multivariate main effect of teacher support was able to explain 18% of the variance

between the groups. There were significant overall group mean differences based on level of

teacher support on three variables: DRA2 F (2,69) = 3.91, p = .025, η2 = .106; Concepts About

Print F (2,69) = 3.60, p = .033, η2 = .098 and Reading Words, F (2 , 69) = 3.232, p = .046, η2 =

.089. Table 9 reports the means and standard deviations on the non-transformed data. Further

examination of the individual group univariate statistics indicated that there were statistically

significant differences between low support teachers and high support teachers on three

variables: DRA2, Concepts About Print, and Reading Words. In addition, there was a significant

group mean difference between participants with medium support teachers and high support

teachers on one variable, the DRA2. There were no significant differences between medium

support teachers and low support teachers.

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Table 9 Means and Standard Deviations for Nonsignificant Teacher Support Main Effect on Non transformed Data

Dependent variable

Level of Literacy Support

Low Medium High F η2 MOY DRA2 2.78 1.30 3.36 1.81 4.69 2.69 3.91* .106 Concepts About Print

15.56 2.83 17.11 2.13 17.97 3.20 3.60* .098

Reading Words 8.22 5.70 11.21 5.25 13.14 5.37 3.23* .089 Note: F and η2ˆvalues are based on the transformed data set.

*p<.05, two tailed

The overall interaction effect was able to explain 24.5% of the variance in group

differences. Visual analysis and comparison of the non-transformed group means revealed

meaningful patterns among the different levels of teachers depending on whether Istation®

was used or not. Interestingly, participants in the control classrooms with a low support

teacher had higher scores on five out of six of the dependent literacy variables when compared

to their matched peers in the Istation® classrooms with low support teachers. This finding

suggests that Istation® may not have been as effective with students in classrooms with low

support teachers; however, it is worth noting that a wide variation in cell size existed, with a

lower number of participants with low support teachers. Conversely, participants in the

Istation® ® classrooms with a medium support teacher had higher scores on four out of the six

dependent variables, with the Istation® participants scoring higher on all subtests except for

the DRA2 and writing vocabulary. These findings suggest that overall, Istation® was more

effective when used in classrooms with medium support teachers. Finally, analysis of the group

41

means for high support teachers revealed interesting patterns. Participants in the Istation®

classrooms scored higher on hearing and recording sounds, letter sound knowledge, and

writing vocabulary, while participants in the control classrooms scored higher on the DRA2,

concepts about print, and reading words.

Discussion

By investigating technology from an early literacy perspective, I uncovered multiple

realities about the complex relationship between technology and early literacy learning. Results

indicate that overall, Istation® had a statistically significant effect on the literacy learning of the

students in the study given the dependent measures used. This study also considered the

effects of teacher support in early literacy classrooms, independent of the Istation® program.

Finally, I looked at patterns in the interaction between the use of Istation® and teacher support.

By considering these results together, I can speculate as to why the Istation® program and the

level of literacy support provided by teachers had an effect on particular measures of early

literacy skills and comment on the role that Istation® should play in early literacy classrooms.

Based on the results from this study, Istation® was particularly effective in developing

students’ letter sound knowledge and their ability to hear and record sounds. Istation®’s

approach to instructing students in early reading aligns closely with many behavioral theories of

learning and reinforces those reading skills (like letter sound knowledge) that require speed and

efficiency (Ehri & Roberts, 2006; Ertmer & Newby, 1993; NELP, 2008; Philips & Torgesen, 2006;

Skinner, 1954). Istation® encourages automaticity through multiple opportunities to practice

skills using highly structured, individualized instruction and by creating strong connections

between stimulus and response through reinforcement. Despite a significant overall effect,

42

Istation®’s approach to instruction did not seem to be as effective with what are arguably more

complex measures of early literacy such as overall reading level, concepts about print, and

reading words. In the case of these skills, the level of literacy support provided by the teachers

had a larger effect.

The data suggest that as the level of literacy support provided by the teacher increased,

students’ abilities to read and comprehend a book, understand concepts about print, and read

novel words also increased. While Istation® provided multiple opportunities for practice and

feedback on students’ individual levels, the more constructivist approach of the teachers in this

study allowed for greater social interaction, small group instruction, and flexibility in instruction

and student products. The main goal of many of the teachers did not appear to be speed and

accuracy; rather, the emphasis was on modeling the flexible application of strategies and

allowing students to practice these strategies within a social context. This shared and

interactive approach to literacy instruction closely aligns with emergent literacy theory and

research and would explain why teachers had a greater effect on literacy measures that require

a greater depth of processing and a more flexible application of strategies (Blair, Rupley &

Nichols, 2007; Clay, 1991; Hall, 2003; NELP, 2008; Schunk, 1991; Sulzby & Teale, 1991)

Patterns within the interaction effect were difficult to detect, but data suggest that

Istation® did not compensate for a low-level of literacy support in the classroom nor did it

supplement the literacy skills of students in these classrooms. Similarly, Istation® did not

increase the overall early literacy achievement in classrooms with high or medium support

teachers. In high support classrooms, in particular, Istation®’s overall effect did not translate

into higher scores on the DRA2, concepts about print, and reading words. Interestingly, overall

43

reading levels were higher in all non-Istation® classrooms, suggesting that the effects of

Istation® may not translate into higher overall reading levels. One explanation for this finding is

that students in non-Istation® classrooms received a larger percentage of their instruction from

teachers using a constructivist approach that incorporated activities and instruction that more

closely aligns emergent literacy theory (Blair, Rupley, Nichols, 2007; Hall, 2003).

A case could be made that, by definition, Istation® modeled the instruction of a more

knowledgeable other, guiding and scaffolding instruction as students practiced new skills.

Istation® provided feedback, evaluated students’ responses, and adapted instruction based on

students’ responses; however, based on my observations, I maintain that there are several

notable differences between the way that Istation® modeled and supported literacy learning

and the ways in which the teachers did. These differences help explain why Istation® did not

have a broader effect on students’ early literacy achievement.

The most significant difference between Istation® and the teachers was the authenticity

of the early literacy experiences observed. During Istation® instruction, students wore

headphones, were generally quiet, and did not interact with the teacher or each other.

Students did not produce or respond verbally to any texts—they simply clicked on the right

answer when prompted by the program. There was little variability in the presentation of the

content. On the other hand, during large and small group instruction with the teachers,

students interacted socially, responded to texts in a variety of ways (including writing), and

there were a variety of texts and contexts presented. Early literacy research supports social

interaction and variability during instruction (Blair, Rupley & Nichols, 2007; Hall, 2003; NELP,

2008; Ponitz & Rimm-Kaufman, 2011).

44

Another notable difference was the flexibility and adaptability of Istation® compared to

the teachers. As an adaptive sequence system, Istation® is based on the concept of mastery

learning. If a student masters a skill, the student progresses to the next skill. If the student fails

to master a skill, Istation® adapts and presents remedial information, reassessing until the

student achieves mastery of the skill. Istation® adapted to individual students based on their

responses; however, the program was not as flexible or responsive as the classroom teachers

were during similar activities. For example, many of the teachers were observed quickly

adapting instruction based on individual students’ interests, backgrounds, and specific needs.

The teachers often revised their approach based on social interactions that occurred during

instruction. One adaptive strategy that many of the teachers used that Istation® did not was

metacognitive instruction. The teachers explained, modeled, and used reading strategies

during instruction, thinking aloud as they did so. This metacognitive layer of instruction is vital

to creating strategic readers (Afflerbach, Pearson, & Paris, 2008; Ankrum, Genest, & Belcastro,

2014; Pressley et al., 1994).

Finally, I observed different emotions from students as they interacted with Istation®

compared to the emotions as they interacted with their teachers. As Cambourne (1995)

asserts, children are more successful when their learning is supported by “those to whom they

are bonded” (p. 185). Students appeared motivated to work on Istation® and were generally

engaged with the program; however, there was no “bond” observed between the students and

the computer. On the other hand, students often seemed emotionally connected to their

teachers, and they were observed smiling, laughing, and socially engaged during instruction.

45

These strong emotions and bonds during instruction have been shown to lead to increased

learning in students (Jensen 1998; Ponitz & Rimm-Kaufman, 2011; Wolfe, 2010).

Conclusion

One purpose of this study was to determine if Istation® was able to serve as a more

knowledgeable other. Based on the findings of this study, it depends. Istation® appears to

effectively instruct young students and serve as a more knowledgeable other within some

aspects of literacy instruction, particularly those that involve early literacy concepts that require

drill and repeated practice, such as letter sound knowledge, hearing and recording sounds, and

writing vocabulary. For these early literacy skills, Istation® was able to scaffold students’

learning, provide instruction within their zone of proximal development, and serve as an

effective mediator (or more knowledgeable other) between the child and the social

construction of early literacy knowledge.

In contrast, Istation® does not appear to be an adequate substitute for the more

knowledgeable other when it comes to creating meaning and applying early literacy skills to

more complex literacy tasks. Based on the data from this study, early literacy skills that require

the integration of a variety of literacy skills and strategies, such as reading and comprehending

a book, understanding concepts about print, and reading words, seem to require the instruction

and feedback of a human, one who is able to interact, provide multidimensional feedback and

allow for the student to take on a more active role in the social interaction.

Limitations. The results of this study were limited by the total sample size (n = 72).

Despite attempts to use create a more balanced sample through purposeful sampling of

schools, I was only able to match 72 of the 150 participants using propensity score matching. In

46

addition, propensity score matching assumes unconfoundedness and assumes that no further

variables exist that may predict the propensity of the participants (Austin, 2011; Murnane &

Willet, 2011; Reutzel, Spichtig, & Petscher, 2012). Because of this assumption, the design of

this study may be limited by the matching variables selected by the researcher.

This study is also limited by the geographical location and demographics. The study

took place in two medium to large, diverse, suburban school districts in the south, and the

results may not be generalizable to other regions or school districts.

Implications for use of Istation® in early literacy education. There is increasing pressure

on school districts to find quick and efficient solutions to perceived problems in reading

achievement, and often, the focus is on improving early reading skills (Paterson, et al., 2003). A

popular solution to these problems is educational technology. As the use of technology

becomes more prevalent in elementary schools, and particularly in early childhood classrooms,

there is an increased need for independent research on the relationship between technology

and literacy in order to justify (or discourage) districts’ large expenditures and inform their

decisions about how to integrate technology into the instructional curriculum (Tracey & Young,

2007). This study contributes to the scant literature on the effects of technology on the early

literacy skills of young students and provides emerging evidence supporting the use of

integrated learning systems, including Istation®, as one tool in the early literacy curriculum.

When choosing to integrate an ILS into the curriculum, district leaders must decide what

elements are important in an early literacy classroom and ensure that any technology that is

integrated into the curriculum aligns with the district’s philosophy about how children learn. In

addition, leaders must decide on the role of the ILS within the curriculum. Is the purpose of the

47

ILS to supplement or supplant the teacher? The present study suggests that ILS may be just one

tool that teachers can integrate into the curriculum and that a careful combination of

technology and teachers is needed in order for students to develop a variety of vital early

literacy skills. Technology can serve as a more knowledgeable other in an early literacy

classroom that uses a balanced, constructivist approach to literacy learning. Combining the

behavioral, skills-based, sequential approach of Istation® with the more constructivist approach

of most early literacy teachers can have a powerful effect on the literacy learning of emergent

readers.

Implications for future research. To increase the ability to generalize findings, future

researchers may want to use a larger sample size, include other grade levels, select different

types of school districts, or study specific populations (ELLs, economically disadvantaged,

struggling readers). In addition, a study on the qualitative differences between the instruction

and feedback of Istation® versus the teacher would be helpful in further evaluating when and

how technology can be integrated effectively into the curriculum.

Despite the limitations and suggestions for improvement, this study provides important

evidence supporting the efficacy of Istation® with a small sample of kindergarten students.

When integrated into a curriculum in which teachers support literacy learning through a

constructive approach, Istation® can offer teachers and districts a potentially efficient and

effective tool for providing some of the early literacy instruction for young students.

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Thoemmes, F.J., & Kim, E.S. (2011). A systematic review of propensity score methods in the social sciences. Multivariate Behavioral Research, 46, 90-118.

Thompkins, G.E. (2014). Literacy for the 21st century: A balanced approach. Boston, MA: Pearson.

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APPENDIX A

OBSERVATION CODING MATRIX FOR LEVEL OF TEACHER LITERACY SUPPORT

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Low Literacy Support Medium Literacy Support High Literacy Support Overall Profile Teacher spends less time on

literacy instruction and more time on other issues such as classroom management, transitions, and/or discipline. Children are primarily passive during literacy instruction and/or literacy instruction is clearly in conflict with best practices. (Paterson et al., 2003).Worksheets are common. Children are not given a lot of choice in the classroom.

Teacher spends a large percentage of his/her instructional time on literacy events, but those events include less student input or choice. While there is evidence of best practice models, these attempts are not always successful (Paterson et al, 2003). Worksheets are used occasionally. Students are given some choice in the classroom. Students are sometimes active in their demonstrations of learning.

Teacher spends most of his/her instructional time on literacy events. The nature of these events is congruent with best practices in early literacy and students are highly active in constructing these events (Paterson et al., 2003). Worksheets are used rarely in the classroom. Students are given choice and are active in their demonstrations of learning. Teacher offers varied levels of scaffolding throughout the day, as needed. (modeled, shared, guided, independent)

Read Alouds Teacher reads books to students but does not actively engage the listeners and does not develop adequate background knowledge. Teacher may not have a clear purpose or objective for reading.

Teacher sometimes reads aloud to students, modeling a couple strategies. Teacher may or may not engage listeners while reading. Teacher may only cursorily teach adequate background knowledge or critical thinking about book.

Teacher regularly reads aloud to students, modeling the strategies and skills that lead to comprehension. Teacher engages the listeners, developing background knowledge, comprehension skills, and critical thinking.

Shared/Interactive Reading

Teacher does not conduct shared/interactive reading regularly or has an inappropriate or unclear objective/purpose for reading. No think alouds or conversations around the text occur during the lesson

Teacher regularly conducts shared/interactive reading lessons. The objective/purpose may or may not be clear. The teacher asks questions during the book, but he/she may interrupt reading too frequently or may ask questions that are irrelevant to the purpose for reading the book. Questions may only be lower level thinking questions. Teacher may or may not identify relevant language features, discuss unfamiliar vocabulary or think aloud while reading the book.

Teacher regularly conducts shared/interactive reading lessons. These lessons have a clear, discernable objective/purpose that is appropriate for the instructional level of the class. The teacher models the behavior of a reader for the students, thinking aloud occasionally. Teacher asks a few carefully planned questions during the book. Teacher has a conversation about the text and asks students to help use information from the text to help them make meaning, identify relevant language features, discuss unfamiliar vocabulary, and think critically about the text. The teacher models how good readers process texts by

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“thinking aloud” from time to time. These “think-alouds” relate to the shared learning goal. Big books may be used with large groups.

Guided Reading Teacher does not conduct small guided reading groups regularly or does not use leveled readers when meeting with small groups of students. May use heterogeneous groupings.

Teacher regularly conducts guided reading with small groups of students; however, objective/purpose may not be clear. OR teacher may not use clear, lesson cycle with lesson (introduction, objective, picture walk, modeled input, student practice). Mostly homogenous groupings, but groupings may be fixed.

Teacher regularly conducts guided reading lessons with small groups of students using individual books. Objective/purpose for guided reading is clear. Teacher uses clear lesson cycle while reading with students (introduction, objective, picture walk, modeled input, student practice). Groups are homogenous and flexible.

Independent Reading

Students are not given any opportunities to read by themselves. Books on students’ independent reading level are not available.

Teacher gives students opportunities to read independently; however, there is not a lot a choice involved in which books they choose and the books may not be on their independent reading level.

Teacher gives students regular opportunities to read independently. Students are allowed to choose from a variety of books and genres on their independent reading level.

Modeled Writing Teacher does not model writing for the students.

Teacher occasional models writing for the students or only does modeled writing, to the exclusion of shared writing. Teacher may or may not do think alouds during instruction.

Teacher regularly models writing and demonstrates a range of skills, processes, and strategies for writing. Teacher thinks aloud as he/she writes. Minilessons are used to teach specific strategies and skills.

Shared Writing Teacher does not use shared writing in the classroom.

Teacher conducts shared writing occasionally in classroom. Teacher and students both contribute to the activity; however, student role may be minimized. Teacher may only minimally scaffold students understanding of writing.

Teacher conducts shared writing in the classroom regularly. There is a clear objective. Minilessons are used to teach specific strategies and skills. Teacher and students contribute to the writing and the activity is a collaborative process. Some sharing of the pen. Teacher scaffolds students’ understanding of writing and encourages the reciprocal process of reading/writing.

Guided Writing Teacher does not incorporate guided writing

Teacher occasionally meets with small groups of

Teacher supports and scaffolds student writing in

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into the classroom. students to guide and support them as they write.

small groups regularly. Groups are flexible. Teacher uses guided writing as a time to guide and support students based on their particular set of needs.

Independent Writing/Journals

Students are not expected or given opportunities to write regularly on their own in the classroom.

Students are expected to write independently regularly; however, there is very little choice when they write. There may be prescribed writing, prompts, or boundaries for their writing. Teacher may not conference with students about their writing or may conference only cursorily with students.

Students write daily in their journals. There is a clearly defined process that the students use to write. Students are given choice and freedom to write about what matters to them. Teacher conferences regularly with students about their writing and uses these conferences to plan future instruction.

Word Work/ Word Study

Teacher does not do word work regularly with students. No word wall evident.

Teacher does word work with the students; however, teacher may not regularly model the strategies for working with the words and may or may not differentiate the word work according to each student’s needs. Word work may involve worksheets. Word wall present.

Teacher has a clear objective for word work. Teacher models word work for the students and then has the students work independently on differentiated word work, according to each student’s needs. Students physically manipulate words/cards for activity. Word wall present, visible, and used regularly. Word study focuses on building interest in words and on looking for patterns in words.

Phonological Awareness

No evidence of phonological awareness in classroom.

Teacher teaches phonological awareness regularly but teaches it independently of other aspects of literacy.

Teacher incorporates phonological awareness activities regularly and in a variety of contexts. Integrated seamlessly into daily activities.

Alphabetic Principal Teacher emphasizes letter of the week. Worksheets and art projects on each letter are used.

Teacher addresses alphabetic principal regularly; however, it may be taught as an independent activity and not integrated into other areas of literacy or it may be overemphasized to the exclusion of other important aspects of literacy.

Teacher integrates alphabetic principal into other daily activities.

Integration of Literacy Across the

Teacher does not integrate literacy into other areas of

Teacher sometimes integrates literacy into other

Teacher integrates literacy regularly into all areas of the

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Curriculum the curriculum. areas of the curriculum. curriculum. Reading and writing integrated as well and integrated within content areas. Teachers make many cross-curricular connections.

Social Interaction Teacher does not allow students to interact or collaborate regularly in the classroom. Children are often asked to not talk. Generally a quiet classroom.

Teacher may allow students to interact with other students, but the purpose for the interaction is not clear. Teacher does not model interactions for students.

Teacher encourages students to interact and collaborate on a regular basis with partners or small groups at appropriate times in the classroom. Teacher models these interactions for students. Classroom is often noisy with students interacting but the noise is not distracting. All levels of conversations take place regularly. Children have conversations with each other, and teachers have conversations with students.

Classroom Management/ Instructional Time

Teacher spends much of the instructional time managing behavior and/or expectations. Instructional activities are interrupted excessively to address management and/or behavioral issues.

Teacher uses much of the instructional time well. Good organization in classroom; however, expectations may not always be clear. Instructional activities may be interrupted regularly to address management and/or behavioral issues.

Teacher uses almost every minute of class time well. Teacher turn even mundane routines into instructional events. Teachers are excellent classroom managers. Discipline issues handled quickly and quietly.

Levels of Support/Scaffolding

Teacher relies on modeling and/or independent practice only. Does not provide scaffolding within students’ zone of proximal development.

Teacher uses some levels of support (modeling, guided, shared), and provides some opportunities for independent practice. Scaffolding may be inadequate or not aligned with developmentally appropriate practice.

Teacher uses a lot of scaffolding and all levels of support (modeling, guided, shared), providing support and scaffolding learning in the child’s zone of proximal development, as needed. Allows time for independent practice.

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APPENDIX B

TEACHER SURVEY OF LITERACY PRACTICES

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Teacher Survey

Your name: ______________________________ School: ______________________

Years teaching: _______________ Years teaching kindergarten: _________________

Number of students: __________ Your degree(s): _____________________________

Certification(s): _______________________________________________________

How important do you consider each of the following to be in your literacy program?

1 Not an important part of my program OR Don’t use at all

2 Something I may do that is somewhat important

3 A critical part of my program

_______ Reading aloud to children _______ Shared reading of big books _______ Alphabet study (e.g. letter of the week) _______ Children reading little books that they may have memorized _______ Children learning how to write specific letters correctly _______ Teacher writing experience charts (“News of the Day”) _______ Journal writing/Writers’ Workshop _______ Art projects related to the letter of the week _______ Computer programs (please name __________________________________) _______ Children making books as a class or individually _______ Buddy reading or guided reading in groups Please check one _________mixed ability _________ homogeneous ______ Word study (spelling, sight words) Please respond to the following:

1. In general, what are you most proud of in your literacy program? 2. Do you have any goals for improving your literacy program this year? 3. How do you accommodate the range of ability levels in your classroom? 4. What week of school did you start using Istation® with your students? (District A only) 5. On average, how much time do your students spend using Istation® each week? (District

A only) 6. Please rate the effectiveness of Istation® on a scale from 1 to 10, with a 10 indicating

most effective. ___________ (District A only) 7. Best feature(s) of Istation®? (District A only) 8. Biggest concern with Istation®? (District A only)

Note: Adapted from Paterson, Henry, O’Quin, Ceprano, and Blue (2003)

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APPENDIX C

PROFILE OF INTEGRATED LEARNING SYSTEM IN STUDY

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Introduction

Istation® is one example of a computer assisted instructional (CAI) program that utilizes

an adaptive sequence system. Adaptive sequence systems are flexible and adapt to individual

differences in students’ learning (Lee & Park, 2007). These systems are based on the concept of

mastery learning. If a student masters a skill, the student progresses to the next skill. If the

student fails to master a skill, the computer adapts and presents remedial information,

reassessing until the student achieves mastery of the skill. Istation® can also be characterized

as an integrated learning system (ILS). Unlike CAI, ILS is not used only for isolated enrichment

or remediation; instead, ILS are fully integrated and aligned with the instructional curriculum

and provide feedback to the teachers about individual students through an assessment system

(Cassady & Smith, 2005; Tracey & Young, 2007). According to the publisher,

Istation® delivers individualized instruction — complete with age-appropriate content — for pre-K through high school students. Plus, every lesson is supported with data-rich benchmark and continuous progress monitoring assessments through Istation®'s proprietary ISIP™ [Istation® Indicators of Progress] technology. (Istation®, n.d., Istation® Reading section, para. 1)

Description

Istation® is a privately held, Texas-based publisher with a portfolio of products that

mainly focus on developing reading skills. There are several well-known educators and

researchers associated with this company including Dr. Reid Lyon, Dr. Marilyn Adams, Dr. Joe

Torgensen, and Dr. Patricia Mathes. The Istation® products include:

1. Istation® Early Reading for pre-K through 3rd grade (focus of this study)

2. Istation® Advanced Reading for 4th through 12th grade

3. Istation® Reading in Espanol for pre-k through 3rd grade

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4. Istation® Math (in development)

An accurate count of Istation® users is unavailable; however, a description of Istation®

on the EdSurge website reports that over 900,000 students in over 407 districts use Istation®

(EdSurge, n.d., Who Is Using It section). This number appears to grossly underestimate the

number of users since both Texas and South Carolina have recently implemented and funded

the use of Istation®, state-wide. Through a program called Texas SUCCESS, all Texas public

school students in Grades 3-8 have free access to Istation® Reading at school and at home.

According to the most updated enrollment reports from the 2011-2012 school year, there are

2,231,934 students in Grades 3-8 in Texas (Texas Education Agency, 2012, p. 15). Similarly, the

South Carolina Success Program recently provided funding for free access to Istation® Reading

for all students in Grades pre-K through 8 in public schools. For the 2011-2012 school year,

South Carolina had an average daily attendance of almost 500,000 for Grades K-8 (South

Carolina State Department of Education, 2011-2012). Based on these numbers alone, the

actual number of Istation® users is probably much higher than the 900,000 reported by the

EdSurge website. Istation® provides no cost estimates on its website; however, EdSurge reports

that a comprehensive license program costs $55 per student (EdSurge, n.d., What does it cost

section). Schools can purchase unlimited use licenses for $6500. This number does not include

the costs associated with training teachers and district personnel and the time needed to install

the program on district computers.

Despite the high number of users, the statewide implementations, and the associated

costs of Istation® Reading, there are no published reports on Istation®. There are a limited

number of reports and white papers available on the publisher’s website, with the focus of

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most of these papers on validity and reliability. Because of the lack of research on Istation®,

most of the information within this review will come from the publisher’s website and the

limited number of reports they provide.

Theory

The content of Istation® Early Reading is organized around five domains of reading:

phonemic awareness, alphabetic knowledge, vocabulary, comprehension and fluency (Mathes,

Torgesen, & Herron, 2012). These domains are based on the five pillars of reading presented in

the National Reading Panel’s (2000) The Report of the National Reading Panel: Teaching

Children to Read (NICCHD, 2000). The National Reading Panel was formed in 1997 to review

research on how children learn to read and make generalizations about which methods are the

most effective based on the research. The findings from this report still direct much of the

mandates in education. As noted in the technical report on Istation® Early Reading, “[Istation®]

Early Reading has been designed to automatically provide continuous measurement of

Kindergarten through Grade 3 student progress throughout the school year in all the critical

areas of early reading, including phonemic awareness, alphabetic knowledge and skills, fluency,

vocabulary, and comprehension, as mandated by the Elementary and Secondary Education Act,

No Child Left Behind (NCLB)” (Mathes, Torgesen, & Herron, 2012, p. 5).

Istation® and RtI

In 2004, the United States government passed the Individuals with Disabilities Education

Improvement Act (IDEIA). This act states that schools must provide all students with high

quality instruction through scientifically based interventions. Additionally, students in general

education must have access to the highest quality interventions before being considered for

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special education through a process called Response to Intervention (RtI). The goal of RtI is to

reduce the number of students identified as learning disabled by addressing individual

students’ needs in a prompt and effective manner. Components of RtI include assessment,

data-based decision making, responsive instruction, scientifically-based interventions, and

progress monitoring (Istation®,2006c). These components are implemented through a three-

tiered process in which all students receive high quality instruction through the regular

curriculum, or through a tier one level of instruction (Istation® ®, 2006c). In tier two, students

who are at-risk and are struggling academically receive targeted instruction through small

group instruction, tutoring, or other scientifically based interventions (Istation®, 2006c). The

highest level of academic support is tier three, in which students who did not respond well with

the tier one and two strategies receive more frequent individual instructional opportunities and

recurrent progress monitoring opportunities on the student’s academic level (Istation®, 2006c).

The developers of Istation® assert that the program corresponds with the components of the

RtI process by providing differentiated instruction, assessments, and continuous progress

monitoring. In addition, the Istation® website notes that the program helps provide

documentation of instruction and progress required by RtI. Recommendations for the use of

Istation® for all three tiers include:

1. Tier 1: Screening and regular assessment of students; 45 minutes per week minimum on Istation®;

2. Tier 2: Increase use of Istation® to 90 minutes per week and use teacher-directed small-group lessons provided by Istation®;

3. Tier 3: Increase use of Istation® to 120 minutes per week and use the teacher-directed one-on-one lessons provided by Istation®.

Many districts use Istation® to address the requirements of RtI and to provide documentation

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and data on individual students’ progress as required by RtI (Istation®, 2006c).

How Istation® works

The Istation® program was developed around four main components: assessment,

instruction, reporting, and teacher tools. These four components are aligned and integrated

into the state curriculums and are part of what makes Istation® an ILS. In fact, Istation® has

aligned each of its lessons with the common core objectives and with the learning objectives of

42 states plus the District of Columbia and the US Virgin Islands (Istation®, n.d., Instructions:

Correlations section).

Istation® begins by having students log in and take an assessment that lasts 40 minutes

or less (Mathes, Torgesen, & Herron, 2012). These assessments are called Istation® Indicators

of Progress [ISIP™]. ISIP™ attempt to determine students’ abilities in the five critical reading

areas and are mainly multiple-choice, with a few fill-in-the-blank questions. Using item

response theory and computer adaptive testing algorithms, the program adapts, varying the

difficulty and number of questions depending on how the student responds (Mathes, Torgesen,

& Herron, 2012). ISIP™ are independent of age or grade level. Based on the assessment

results, Istation® places the student within the reading curriculum. Regardless of how often the

students use the program, they are required to take these assessments at least once a month

to document progress and reevaluate reading skills in the five key developmental areas

(Mathes, Torgesen, & Herron, 2012).

After students are assessed, they receive systematic and explicit direct instruction and

practice on their level (Edsurge, n.d., How does it work section). The instruction follows a

typical lesson plan format, including an introduction, modeling, guided practice, independent

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practice, and an application within a book or passage (Edsurge, n.d., How does it work section).

Interactive activities, games, and animated characters such as Detective Dan and the Digraphs

are integrated into the lessons. If a student is successful during the lesson, the program adapts

and moves on to the next lesson in the Istation® curriculum. If a student struggles during a

lesson, the program will automatically adapt and reteach the skill in another format.

Teachers can generate reports of student progress at any time. These reports provide

data on students’ abilities in the five areas of reading (Istation®, n.d., Reports section). These

reports can be customized to meet the needs of the teacher, administrator, or school. Data can

be aggregated on a state, district, classroom, or individual level (Istation®, n.d., Reports

section). Reports can provide data on responses, time on task, amount of time spent, and

accuracy. Teachers may also request “on demand assessments” for specific reading areas so

that the student can receive instruction in a desired content area. Additional reports group

students by instructional needs and then provide links to scripted lessons related to student

needs.

The final component of the Istation® program is the teacher tools. This component

provides curriculum-related resources to teachers, including almost 2,000 scripted lessons for

whole-group, small-group, and one-on-one instruction (Istation®, n.d., Teacher tools section).

Many of the lessons are animated and can be used with interactive white-board technology. In

addition to scripted lessons, the teacher tools provide bibliographies for each lesson and links

to online interactive books.

Research on Istation®

As mentioned earlier, there are no published reports of Istation®. All research for this

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review comes from studies and reports posted on their website. There are four studies on the

reliability and validity of Istation® on the website, and of those four, only one of these studies

was conducted by an independent researcher. The independent study, conducted by a

researcher in the Hillsborough County Public Schools in Florida, found a strong correlation

between the Istation® assessment measures and the second grade Stanford 10 norm-

referenced assessment (Gaughan, 2011). In addition, the study reported a high correlation

between the Istation® assessment measure and the state mandated test in Florida for third

grade.

Three other studies (Mathes, 2007, 2009, 2010) investigated the validity and reliability

of Istation® using small student samples. Patricia Mathes, one of the Istation® assessment

developers, was the principal investigator on all three studies. Overall, these three studies

found high concurrent validity with many other standard literacy assessments, good internal

consistency among assessment items, and high test-retest reliability. When studying Istation®

and preschoolers, Mathes (2010) found that Istation® assessments have a high concurrent

validity with the Peabody Picture Vocabulary Test (PPVT) and Test of Preschool Early Literacy

(TOPEL), which are norm-referenced assessments as well as English Language Skills Assessment

(ELSA), an authentic assessment. A similar study (Mathes, 2009) examined the concurrent

validity of Istation® with external measures used with kindergarten through third grade. The

results of this study found high concurrent validity with common literacy assessments such as

Dynamic Indicators of Basic Early Literacy Skills (DIBELS), Texas Primary Reading Inventory

(TPRI), Woodcock Language Proficiency Battery-Revised (WLPB-R), Gray Oral Reading Test

(GORT-4), Woodcock Johnson III Tests of Achievement (WJ-III ACH), Wechsler Individual

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Achievement Test (WIAT II), Comprehensive Test of Phonological Processing (CTOPP), and the

Test of Word Reading Efficiency (TOWRE; Mathes, 2009). An earlier study (Mathes, 2007)

examined the concurrent and predictive validity of the Istation® assessment with DIBELS and

Texas Assessment of Knowledge and Skills (TAKS), a state assessment measure no longer used

by the state of Texas.

There are eight white papers posted on the Istation® website. Five of these papers

describe specific components of the program and describe the use of the program with specific

populations, such as preschool students and English language learners (Istation®, 2004, 2006a,

2006b, 2009, 2010). An additional paper describes how Istation® complements the

requirements of RtI (Istation®, 2006c). Only two of the papers describe research on the

effectiveness of Istation®. One descriptive study by Bugbee (2011) reported significant pretest-

posttest gains on a language arts assessment after Istation® use in one elementary school in

Louisiana. Another paper examined the relationship between the Istation® assessment and the

Developmental Reading Assessment 2 (DRA 2) scores (Hoelze, 2012). This study used data from

a large suburban school district and found that Istation® assessment measures are highly

correlated with DRA 2 scores (Hoelzle, 2012).

Overall, the small number of studies provided by Istation® limit their ability to make

bold claims about the effectiveness of Istation® on the literacy skills of students. Additional

high-quality research is needed to determine the effectiveness of Istation® and if any gains can

be maintained long-term. Despite the lack of research on its efficacy, Istation® is a popular and

widely used program in the United States.

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APPENDIX D

EXTENDED LITERATURE REVIEW

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Introduction

Four main bodies of research inform the review of literature for this study: history and

approaches to literacy and young children, educational technology, computer-assisted

instruction, and integrated learning systems. First, I provide a brief history of literacy beliefs and

instructional approaches as they relate to young children in order to provide a context in which

to place technology. The second section of the review summarizes the literature on technology

and education. The research in this section is divided into three subsections, based on the role

of the technology in the reviewed studies. Next, I narrow my focus even more exploring the

history and research on computer assisted instruction, a more specific application of

technology and literacy. Finally, I conclude the literature review with history and research on

integrated learning systems and literacy.

These areas vary widely in scope and focus, and it is impossible to provide an exhaustive

review of the literature over these topics; instead, I surveyed the literature and provide the

most significant and germane findings in each area as they relate to this study.

Early Literacy

Early Approaches to Literacy: Reading Readiness

To fully understand the evolution of early literacy and place it within a technological

context, it is helpful to explore the history of early literacy beliefs and instruction. Before 1920,

very little attention was paid to young children and the period before they entered school. The

common belief was that formal reading instruction and learning did not begin until children

entered school and the home environment had little impact on children. There was almost a

benign neglect of preschool children during this time. As a result, very little research or

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literature was devoted to how preschool children learn to read. Two exceptions to the lack of

research on young children were Iredell and Huey. Iredell (1898) published research that noted

parallels between young children’s oral language and their literacy development. In addition,

his research suggested that the period before children enter school was an important and

influential time. Similarly, Huey (1908) devoted an entire chapter in his seminal book on

reading and reading instruction to, “Learning to Read at Home”. In this chapter, Huey noted

the importance of the home environment in young children’s literacy learning and suggested

“natural ways” of teaching children to read a home.

Around 1920, there was a shift in thinking and researchers and the general public

started paying more attention to the period before young children entered school. Benign

neglect turned into an emphasis on preparation. While readiness was a familiar concept, it had

not been applied to the field of literacy before this time. The first explicit reference to reading

readiness occurred in 1925, in the Report of the National Committee on Reading. The reading

readiness paradigm was about to take hold. Within this paradigm, there were two views. The

first view was that reading readiness was a measure of “neural ripeness” or maturation. The

other view was that reading readiness was something that could be taught, and learning could

be accelerated through appropriate experiences.

The maturation view of reading readiness dominated the field of reading from the 1920s

to about the 1950s. During this time, the writings of a child psychologist, Arnold Gesell (1925,

1928, 1950), influenced the field greatly. From a maturation viewpoint, Gesell argued that

development in young children would happen naturally and automatically and that the

environment should not manipulated to interfere with this natural development. Durkin (1968)

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notes that research during this time on the natural progression of motor development was

applied beyond its original context to cognitive development. The shared assumption of the

time was that cognitive development (and thus literacy learning) would happen automatically,

with the common prescription to wait if a child was not ready to read. This view of

development, combined with the mental testing and measurement movement, set the stage

for the seminal research of Morphett and Washburn in 1931. Morphett and Washburn (1931)

tested 141 first graders on a variety of subskills. Based on their research, Morphett and

Washburn suggested that the ideal mental age for children to enter school and begin formal

reading instruction was 6 years, 6 months. The statistical nature of their research increased the

influence that the results had on education, and the influence of the 6.5 mental age on the field

of reading education was profound. Despite challenges to the Morphett and Washburn

research from some others within the field, including Gray (1937) and Betts (1946), the belief in

a 6.5 mental age persisted into the 1950s. This view of reading readiness, combined with the

emphasis on testing, created a field in which readiness tests flourished. Readiness tests, such

as the Metropolitan Readiness Test, measured young children on a variety of subskills, trying to

determine if they were ready to learn to read. The emphasis on subskills led to a variety of

workbooks, whose purpose was to get the children ready for the basals when they entered

school.

The maturation view of reading readiness persisted into the 1950s, when several

historical, social, and scientific events occurred that encouraged a move from the maturation

model to the acceleration model of reading readiness. In this case, it was not a complete

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paradigm shift; instead, it was more a refinement of the rules of the reading readiness

paradigm and an application to a new context. The focus shifted from nature to nurture.

The first impetus for changed happened when the Russians launched the Sputnik

spacecraft in 1957. Suddenly, Americans were fearful that the educational system was not

rigorous enough to keep up with the Russians and that our national defense would be

compromised. In response, the public called for a more difficult curriculum and for instruction

to start earlier. Bruner’s (1960) Process of Education book suggested a spiraling of the

curriculum, which was quickly interpreted to mean that the curriculum could be spiraled down

for younger children as well as spiraled up.

In addition, educational research started focusing on young children, even infants.

Research by developmental psychologists, such as Bruner and Brazelton, highlighted the

importance of the early years in development. Their research showed, among other things,

that infants and very young children knew a lot more than they had been given credit. In

addition, Bloom’s (1964) research showed that at least 50% of the intelligence measured at age

17 had been developed by age 4. Suddenly, the focus was on the early years of development

and learning and what could be done to encourage and even accelerate the learning during this

time.

In addition to the research on young children, several social issues affected how this

view of development and reading readiness was actually applied in the classroom and society.

The Civil Rights and War on Poverty movements of the 1960s highlighted the inequality in home

environments and shifted the emphasis in education to equality for all children. Policies were

put into place that encouraged instruction in reading readiness. It was believed that reading

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readiness could be developed and accelerated through proper instruction and environments

(Sulzby & Teale, 1991). Programs such as Head Start designed their curriculums around this

view of literacy learning. This view of accelerating reading readiness lead to a fixed curriculum

that focused on teaching a series of predefined subskills that would encourage effective literacy

learning when the child reached formal school. According to Sulzby and Teale (1991), principles

of this fixed approach to reading readiness included:

1. An emphasis on the scope and sequence of reading readiness subskills. Once mastery of these subskills occurred, formal reading instruction could begin.

2. A complete separation of reading and writing. Writing instruction was delayed until a child learned how to read.

3. An emphasis on the formal aspects of reading, while ignoring the functional aspects.

4. A belief that whatever happened before the child-entered school was irrelevant because proper instruction and sequencing of the subskills would lead to effective reading.

5. Regular measurement of the subskills through formal testing to determine weaknesses and intervention strategies.

Recent Approaches to Reading: Emergent Literacy

Delores Durkin had been publishing research on the reading behaviors of young children

for many years; however, her seminal piece in 1966 on precocious readers pointed out an

anomaly in the reading readiness paradigm. Durkin (1966) questioned the theoretical and

practical appropriateness of a paradigm that could not explain how 4-year-olds with no formal

instruction could read. Suddenly, the reading readiness paradigm had an anomaly that it could

not explain and a quiet crisis in the field occurred. This period of crisis lasted almost 20 years,

with many researchers trying to explain the anomaly noted by Durkin and present a new set of

shared assumptions and rules to guide the field of literacy education.

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The roots of the challenge to the reading readiness paradigm emerged from two main areas:

1. The cognitive revolution, that discarded behavioral views of reading and emphasized new models of development, learning, and reading.

2. A renewed interest in the early years of development, especially language acquisition.

The cognitive revolution, combined with research on language acquisition (e.g. Piaget,

Luria, Bruner) and construction of knowledge (Vygotsky, 1978), created a new view of the

young child. The young child was no longer a passive receiver of reading readiness knowledge

and subskills; instead, he was now viewed as an active learner in his environment, combining

elements of nature and nurture in a way that created new knowledge.

In 1966, Marie Clay, a pioneer researcher in studying literacy behaviors in light of the

new research on language acquisition, decided to study young children’s literacy behaviors for

her dissertation. Her goal was to observe these behaviors so that struggling readers could be

identified sooner and interventions started. She described the behaviors that she observed,

emergent literacy behaviors. In her research, Clay (1967) suggested that print should never be

withheld from young children and that the transformation from oral language to written

language could only occur in the context of real reading and writing.

During this same time, Yetta Goodman (1967) was conducting research on the early

reading behaviors of children in the US and applying the research of her husband, Ken

Goodman (1968) to the reading behaviors of young children. In addition, research on the

natural acquisition of the knowledge of environmental print by the Goodmans was being

applied to the field of early literacy. The Goodmans would eventually use this research to

suggest that all literacy learning occurs naturally.

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In 1972, Clay published her seminal work, Reading: The Patterning of Complex

Behaviors. In this book, Clay formally challenged the concept of reading readiness, delineating

between that model and her model of emergent literacy. Her model was able to explain the

anomaly that Durkin (1968) noted in her research. She emphasized the importance of the early

years in developing literacy behaviors and described the process of becoming literate and the

transformation from unconventional to conventional literacy behaviors. Clay’s (1972) model of

emergent literacy includes six main concepts:

1. Language, reading, and writing develop concurrently in young children.

2. Literacy learning begins at birth. The home and community play an important role in a child’s process of becoming literate.

3. Literacy develops in real life settings in real situations.

4. Critical cognitive development takes place during early literacy learning.

5. Emergent literacy behaviors take place within a social setting. Interactions between a child and another adult are critical to this learning.

6. Early literacy learning goes through predictable stages; however, these stages are flexible and not dependent on age.

The investigation of technology within the kindergarten classrooms in this study was guided by

these six emergent literacy principles suggested by Clay.

Effective Emergent Literacy Strategies

In recent years, researchers have focused a great deal of attention on literacy

development in early childhood using the emergent literacy paradigm. There has been a

copious amount of research dedicated to finding the most effective early literacy methods and

strategies. While there has not been universal agreement on specific early literacy methods,

there has been a general consensus regarding which variables within early literacy learning

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predict future literacy achievement (Adams, 1990; Anderson, Hiebert, Scott, & Wilkinson, 1985;

Bus & vanIJzendoorn, 1999; Bus, vanIJzendoorn, & Pellegrini, 1995; Chall, 1967; International

Reading Association and National Association for the Education of Young Children, 1998; Juel,

1988; NELP, 2004; Snow, Burns, & Griffin, 1998). One of the major findings of the National

Early Literacy Panel (2004) report was the correlation between certain emergent literacy skills

and abilities and later literacy achievement. The panel identified 11 variables that had a

predictive relationship with future literacy skills. There were six variables with a medium to

large predictive power. They included alphabet knowledge, phonological awareness, rapid

automatic naming of letters or numbers, rapid automatic naming of objects or colors, writing or

writing name, and phonological memory (NELP, 2004). In addition, there were five variables

that were moderately correlated with at least one measure of later literacy achievement;

however, these variables either did not maintain this predictive power when other contextual

variables were considered or have not been studied in a way that allows for long-term

predictions. These variables included concepts of print, print knowledge, reading readiness, oral

language, and visual processing (NELP, 2004). Together, these 11 variables are important to

early literacy instruction and many of them can help predict later literacy achievement for most

young students. Because of their predictive power, many classroom curriculums (including

technology) are designed, in part, around these variables.

There have been many studies that have examined the best ways to integrate these

variables into the early literacy curriculum. These general approaches include literacy-rich

environments, social collaboration among the students and teacher, real texts in real situations,

multiple opportunities to interact with texts, and the integration of explicit instruction and

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meaningful practice (Cunningham & Allington, 1999; Anderson, Hiebert, Scott, & Wilkinson,

1985; Fountas & Pinnell, 1996; Holdaway, 1979; International Reading Association and National

Association for the Education of Young Children, 1998; Morrow, Gambrell, & Pressley, 2007;

NELP, 2008; NICHHD, 2000; Sulzby & Teale, 1986). Within these general guidelines, specific

strategies have been developed that support early literacy learning. These strategies include,

but are not limited to, guided reading, shared reading, shared writing, big books, literacy-based

centers, writer’s workshop, phonological awareness activities, phonics instruction, and word

study. Examining each of these specific strategies is beyond the scope of this literature review;

however, these strategies are important components of early literacy programs. As stated

earlier, technology is addressed sparingly, if at all, in most of the major discussions and

research on effective early literacy strategies. In spite of this fact, software developers that

target early literacy consider these variables and strategies when designing their software.

These strategies and variables were considered when evaluating and discussing the

effectiveness of Istation® and the contextual factors as they related to the results of this study.

Technology and Education

“Technology” is a broad and somewhat vague term in education. Technology can refer

to anything from computers to electronic games to interactive smart boards to hand-held

electronic devices. Likewise, research on educational technology is wide-ranging and focuses

on various applications, populations, and purposes. Because of the diverse focus of the

research, it is often difficult to generalize findings and draw definitive conclusions about the

role and effectiveness of technology. Furthermore, making informed decisions about

educational technology is virtually impossible because very few of the published articles on

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technology are actual research studies that evaluate the effectiveness of specific applications of

technology; instead, most of the articles are theoretical in nature or are descriptions of how

technology is used in the classroom (Cassady & Smith, 2005; Lankshear & Knobel, 2003). In

describing previous research on the effects of technology on literacy learning, Cassady & Smith

(2005) said, “the primary theme has been that there is limited empirical research

demonstrating the effects of technology, with the bulk of research in areas such as multimedia

and hypermedia for children providing theoretical arguments rather than research-based

outcomes” (p. 363).

One issue specifically related to educational technology and early literacy is the

inconsistency between the design of the educational technology programs and the principles of

the emergent literacy paradigm. In general, most educational technology is based on

behaviorist assumptions, which focus on repetition, immediate feedback, and reinforcement,

rather than social learning (Johnson et al., 2010; McLoughlin & Oliver, 1998; Paterson et al.,

2003). Because most technology is based on these behavioral objectives, the programs are

usually restricted to lower level educational goals, such as remembering and reciting bits of

information out of context (McLoughlin, 1998). As a result, many technological applications for

early literacy are “isolated programs…few are attuned to desired pedagogical practices within

kindergarten classrooms as a whole” (McKenney, 2008, p. 271). This lack of pedagogical

models guiding many technology applications for early literacy means that much of the

technology does not align with early literacy principals that value social learning and the

interaction that takes place among adults and children in a classroom. Lankshear and Knoble

(2003) suggest that studying technology and literacy from a broadened perspective that

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includes learners, teachers, and context would provide research that more closely

approximates emergent literacy theory.

Recognizing the myriad of ways to investigate technology, some researchers have

attempted to categorize research on technology into broad categories, based on the focus of

the research (Burnett, 2010; Lankshear & Knobel, 2003). In their review of research on

technology and early childhood literacy research, Lankshear and Knobel (2003) made a

distinction between research that focuses on the teacher/teaching aspects of technology and

literacy, research that focuses on the learner/learning aspects, and research that focuses on

both. In making this distinction, the authors noted that most of the reviewed studies

emphasized the learner aspect and focused on “‘reading/receiving’ text-mediated meaning

rather than ‘writing/generating’ meanings” (p. 77). In addition, the reviewed studies rarely

examined the pedagogical roles and views of the teachers regarding technology.

Similarly, Burnett (2010) categorized the literature for her more recent review of

research on new technologies in early childhood literacy research into three broad categories,

based on the role of technology within literacy. For the purpose of this review, I will categorize

the review of research on technology into the three categories suggested by Burnett:

1. Technology as a deliverer of literacy

2. Technology as an interaction around text

3. Technology as a medium for meaning making

While these are not discrete categories, they will allow the reader to better understand the

research on technology using a framework that focuses on the role of technology within the

educational setting.

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While this review will cover a full range of dates, approaches, and applications of

technology focusing on literacy, it is important to acknowledge that technology is characterized

by rapid change. As Leu (2000) noted, “…we must also be cautious about generalizing patterns

from older digital technologies to newer digital technologies” (p. 749). Because of the rapid

rate at which technology (and literacy) is being redefined, it is difficult to make research-based

generalizations that last for an extended period of time. Burnett (2010) even suggested that

research and reviews on technology should be seen as “reifying existing approaches and

resources rather than informing future possibilities” (p. 251).

Technology as Deliverer of Literacy

Most of the reviewed studies on technology and early literacy have described the

relationship between child and technology (Burnett, 2010). These studies usually focus very

narrowly on specific populations or components of reading (Burnett, 2010; McKenney, 2008)

with an emphasis on “developing a generic capacity to encode and decode alphabetic print”

(Lankshear & Knobel, 2003, p. 77). The studies are primarily concerned with reporting learner

outcomes (Lankshear & Knobel, 2003) and generally ignore teachers and context.

Figure D.1. Technology as deliverer of literacy. Adapted from “Technology and Literacy in Early Childhood Educational Settings: A review of research,” by C. Burnett, 2010, Journal of Early Childhood Literacy, 10, p. 256. Copyright 2010 by Sage Journals.

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A large amount of the research on technology and literacy has focused on how

technology delivers literacy to young learners with mild to moderate disabilities. These studies

have found that technology is generally effective for struggling readers (Anderson-Inman &

Horney, 1998; Boone, Higgins, Notari, & Stump, 1996; Brett, 1997; Cassady & Smith, 2004,

2005; Godt, Hutinger, Robinson, & Schneider, 1998; Hecht & Close, 2002; Howell, 2000;

Hutinger & Clark, 2000; Hutinger et al., 1997; Hutinger and Johanson, 2000; Karemaker,

Pitchford, & O’Malley, 2010; Kamil, Intrator, &Kim, 2000; Lonigan et al., 2003; Macaruso, Hook

& McCabe, 2006; Macaruso & Walker, 2008; Mitchell & Fox, 2001; Parette & Murdick, 1998;

Tracey & Young, 2007; Verhallen, Bus, & De Jong, 2006; Volpe, Burns, DuBois, & Zaslofsky,

2011). For example, Marcaruso and Walker’s (2008) study of the effectiveness of Early Reading

(Lexia Learning Systems, 2003) reported that the technology had a statistically significant

impact on the phonological awareness of low performing students. In a similar study,

Karemaker, Pitchford, and O’Malley (2010) compared the effects of a traditional reading

intervention using big books versus a whole-word multimedia software reading intervention on

struggling beginner readers. This study found significantly greater gains in written word

recognition for students using the multimedia software intervention.

Additional studies report that technology is effective for other populations of learners

including English language learners (Eshet-Alkalai & Chajut, 2007; Kamil et al., 2000; Macaruso

& Rodman, 2011; Powers & Price-Johnson, 2007), children from low SES backgrounds (Hecht &

Close, 2002; Tracey & Young, 2007), and children in suburban schools (Cassady & Smith, 2004;

2005; Marcaruso & Walker, 2008). Macaruso & Rodman’s (2011) study investigated the

effectiveness of technology on the early literacy skills of English language learners in a bilingual

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kindergarten classroom. Their study reported that students who received computer assisted-

instruction had significantly greater gains in early literacy skills compared to students who

received regular classroom instruction. The biggest differences between the groups occurred in

the areas of phonological awareness and sight word recognition (Macaruso & Rodman, 2011).

In addition to investigating the effects of technology on literacy skills with particular

populations, many of the research studies have narrowly focused on the effect of technology

on specific components of early literacy, such as phonological awareness, vocabulary, and

reading comprehension. Like the previous studies that focused on particular populations,

researchers have found that technology generally has a positive effect on narrowly defined

components of literacy. Studies on vocabulary (Higgins & Cox, 1998; Higgins & Hess, 1998;

Labbo, Love, & Ryan, 2007; Segers & Verhoeven, 2002, 2004; Silverman & Hines, 2009), reading

comprehension (DeJong and Bus, 2004; Doty, Popplewell, & Byers, 2001; MacArthur & Haynes,

1995; Matthews, 1997; Segers, Takke, & Verhoeven, 2004; Tracey & Young, 2007), process

writing (Bangert-Drowns, 1993; Labbo, Love, & Ryan, 2007; Lankshear et al., 1997; Mott &

Klomes, 2001; Voogt & McKenney, 2008) and language acquisition (Eshet-Alkalai & Chajut,

2007) have shown that technology can assist in developing early literacy skills; however,

caution is urged when interpreting the results of these studies. Many of these studies did not

have a control group, which makes it difficult to isolate technology as the sole explanation for

the gains in literacy skills.

A large number of the technology studies focus on the effects of technology on the

phonological awareness of young children. These studies vary in scope and range from studies

on integrated learning systems (Bauserman, Cassady, Smith, & Stroud, 2005; Cassady & Smith

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2004, 2005) to studies of specific programs, such as talking books and electronic games

(Chambers, Cheung, Madden, Slavin, & Gifford, 2006; Chera & Wood, 2003; Comaskey, Savage,

& Abrami, 2009; DeGraaf, Verhoeven, Bosman, & Hasselman, 2007; Watson & Hempenstall,

2008; Wood, 2005). In addition, there are several studies that investigate the effect of

technology on letter recognition and letter sounds (Brabham, Murray, & Bowden, 2006;

Campbell & Mechling, 2009) and word recognition (Lewandowski, Begeny, & Rogers, 2006).

These studies that focus on a specific component of literacy are generally able to show that

technology has a positive effect on students; however, by focusing on such specific aspects of

literacy, the studies are not able to present an accurate picture of the complex nature of early

literacy. The context in which technology is integrated also remains largely unknown.

Overall, the findings from the studies which investigate technology as a deliverer of

literacy are varied; however, there is a general consensus that children who used the

technology did at least as equally well as children who received similar instruction from an

adult (Burnett, 2010). These findings suggest that technology might be helpful or useful in

classrooms as a supplement to teacher support or for students who are struggling readers and

need additional literacy support.

Technology as an Interaction Around Text

Another way to frame studies about technology and literacy is to focus on the

interactions between and among children as they use technology in the classroom (Burnett,

2010). These studies do not focus on learner outcomes or specific populations; rather, they

describe the exchanges between and among children as they interact with technology.

Figure D.2. Technology as a Site for Interaction Around Texts

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Figure D.2. Technology as site for interaction around texts. Adapted from “Technology and Literacy in Early Childhood Educational Settings: A review of research,” by C. Burnett, 2010, Journal of Early Childhood Literacy, 10, p. 257. Copyright 2010 by Sage Journals.

One example of a study that investigated the interactions around technology is Hyun

and Davis’ (2005) study of kindergarteners’ conversations in a technology-rich classroom. Using

discourse analysis, Hyun and Davis analyzed the dialogue among 5- and 6-year-olds while they

were using computers. This study found that the children’s speech and dialogue evolved over

time and influenced their emergent technological literacy skills (Hyun & Davis, 2005). In

addition, the researchers found that these interactions, combined with teacher input,

scaffolded student development. Related studies have described similar interactions

surrounding technology (Brooker & Siraj-Blatchford, 2002; Chung & Walsh, 2006; Clements,

Nastasi, & Swaminathan, 1993; Labbo & Kuhn 2000; Lankshear & Knobel, 2002; Lim, 2012; van

Scoter 2008; Yang & Lie, 2005). Siegal, Kontorouki, Schmier, et al. (2008) used a single case

study approach to analyze the effects of home literacy skills on the interactions among a

bilingual student and her peers as they composed texts on the computer. The researchers

found that the student’s behaviors surrounding technology in the classroom were impacted by

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her literacy experiences at home. In addition, technology allowed the child to create new social

spaces as she and her peers interacted around technology (Siegal, Kontorouki, Schmier, et al.,

2008).

The studies that analyzed the interaction surrounding technology found that technology

can be used to enhance social learning and can scaffold learning in the classroom. By

expanding their focus from learner outcomes to learner interactions, the researchers of the

cited articles were able to describe how technology can be used as a social learning tool in the

classroom; however, these studies did not determine the effectiveness of the technology and

did not consider the larger context of the classroom and how the teacher and classroom

environment plays a role in these interactions.

Technology as a Medium for Meaning Making

A final way to frame research on technology is to investigate the larger classroom and

social contexts as they relate to literacy learning and technology. Using this framework, the

emphasis shifts from specific populations/components of literacy and narrow social interactions

to meaning making and the production and consumption of technological literacy (Burnett,

2010). There is theoretical support for the collaborative and social aspects of using technology

in educational settings. Vygotsky’s (1978) theory of social learning did not specifically reference

technology; however, Vygotsky’s theory emphasizes that teaching and learning are highly social

activities that involve creating meaning through interactions with teachers (or the more

knowledgeable others), peers, materials, and environment (Kim & Baylor, 2006). It is

reasonable to assume that technology is a tool (or more knowledgeable other?) that falls within

this social dimension of learning. Despite theoretical support for the social and collaborative

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nature of technology, most researchers of technology and early literacy continue to frame their

research from a behavioral or cognitive perspective (Andrews, 2004; Burnett, 2009; Lankshear

& Knobel, 2003; McLoughin, 1998).

Figure D.3. Technology as medium for meaning-making. Adapted from “Technology and Literacy in Early Childhood Educational Settings: A review of research,” by C. Burnett, 2010, Journal of Early Childhood Literacy, 10, p. 260. Copyright 2010 by Sage Journals . A very small body of research has investigated the broader context of technology use in

early literacy classrooms. These studies cautiously suggest that technology can increase the

level of learning, interaction, and collaboration among students, especially during writing

activities (Bump, 1990; Dickenson, 1986; Hawkins, Sheingold, Gearhart, & Berger, 1982; Kamil

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et al., 2000; Kent and Rakestraw, 1994; Mehan, Moll, & Riel, 1985). Kent and Rakestraw’s

(1994) small study of two boys in first grade found that technology “facilitat[ed] complex

language use” (Kamil et al., 2000, p. 780)

Researchers have also investigated other social factors related to technology by

broadening the context for the study. For example, studies by Beck and Fetherston (2003) and

Tancock and Segedy (2004) described technology interventions that increased motivation

surrounding literacy. Others have described technology interventions, such as email,

networked learning environments, and online communities in their studies, investigating the

larger context of the literacy learning as they relate to specific applications of literacy (Teale &

Gambrell, 2007; Pelletier, Reeve, & Halewood, 2006; Cohen, 2005). Still others looked outside

the classroom and examined the notion of community discourse, linguistic capital and home

literacy as they relate to educational technology (Auld, 2007; Taylor, Bernhard, Garg, &

Cummins, 2008). Finally, several researchers approached their studies of technology and

literacy with an open-ended mindset, focusing on ways in which children experiment and

create their identities through technology and literacy (Schiller & Tillett, 2004; Marsh, 2006;

Merchant, 2005). While some of these studies reached well beyond the classroom walls to

create a context, the context of this study will remain in the classroom.

As Burnett (2010) suggested, research on technology and literacy should ideally

“consider the complex interactions that occur between children, technology, and their varied

and wide-ranging experiences of literacy” (p. 260). This approach to studying literacy

complements Labbo and Reinking’s (1999) views on studying the multiple realities of literacy

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and technology, focusing on the broader cognitive an social aspects of learning with a

computer.

Computer Assisted Instruction

Brief History of Computer Assisted Instruction

One specific application of educational technology is computer-assisted instruction

(CAI). The initial expectations when CAI was developed were that the computer would supplant

the role of the reading teacher. In one of the first descriptions of an early computer-based

system, Atkinson & Hansen (1966) outlined a system that was “completely computer-

monitored and minimized the role of the reading teachers” and would individualize instruction

based on students’ aptitudes and abilities (Blok, Oostdam, Otter, & Overmaat, 2002, p. 101).

The effectiveness of the Stanford CAI described by Atkinson & Hansen was reported in 1972.

The results of this early study suggested that students who used CAI achieved higher reading

scores than a group of students instructed by teachers (Fletcher & Atkinson, 1972). This early

study also suggested that CAI did not supplant the reading teacher; rather, it supplemented the

teacher’s reading instruction (Blok et al., 2002). Despite the early success of the Stanford CIA,

the program was discontinued because of the unmanageable size of the mainframe computer

and complex peripherals needed for the program (Blok et al., 2002). Historically, computers

were found in early childhood classrooms as early as the 1970s and 1980s; however, specific

programs designed to teach emergent literacy concepts did not emerge until the early 1990s

(Hisrich & Blanchard, 2009). Since the 1990s, several publishers have developed

comprehensive CAI programs designed to teach early literacy skills using advances in graphics,

sounds, and animation that appeal to younger students (Blok et al., 2002).

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Research on CAI

Early studies and meta-analyses of CAI and literacy were generally not favorable, with

effect sizes less than .2 (Bangert-Drowns, Kulik, & Kulik, 1985; Becker, 1987; Christmann,

Badgett, & Lucking, 1997). Since these studies in the 1980s and 1990s, there have been many

advances in CAI programs. Despite these advances, the research on their effectiveness remains

mixed. In a widely cited meta-analysis of the effects of CAI on beginning reading instruction,

Blok, Oostdam, and Otter (2002) suggested that CAI was generally effective and gave their

tentative endorsement; however, they cautioned that the sample sizes of the studies included

in their meta-analysis were small, averaging only 28 participants. In addition, they found the

overall effect size to only be .19, which is a fairly small effect size (Cohen, 1988). Interestingly,

Blok et al. (2000) found that two characteristics of the study participants, having an advantage

at pretest and instructing in English, explained 61% of the variance between the groups that

used CAI and the groups that did not use CAI. In addition, the meta-analysis did not find a

particular CAI format that positively influenced the overall study effect sizes (Cassady & Smith,

2005).

Since Blok, Oostdam, & Otter’s meta-analysis of 2002, sample sizes in studies on CAI

have increased, but study length continues to limit the researchers’ ability to make bold claims

about the effectiveness of CAI on early literacy skills (Lewandowski, Begeny, & Rogers, 2006;

Mioduser, TurKaspa & Leitner, 2000; Regtvoort & Van der Leij, 2007; Wood, 2005). Overall, the

research on CAI and literacy development has not provided compelling evidence that it is

effective, and there are concerns about the short- and long-term gains from CAI (Cassady &

Smith, 2004).

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Integrated Learning Systems

Brief History of Integrated Learning Systems

Going one step further, integrated learning systems (ILS) are one particular application

of CAI. There is considerable overlap in the use of these three terms (technology, CAI, ILS), and

they are often used interchangeably; however, there are important distinctions in their

definitions and use as noted in Table D.1.

In noting this distinction, Cassady & Smith (2004) wrote, “…Integrated Learning Systems (ILS)

move beyond standard computer-assisted instruction programs that function largely as

remedial instruction disconnected from the curriculum or game-like reward activities for

students completing their work” (p. 950). Furthermore, ILS are usually used to complement

and inform the instructional planning process (Cassady & Smith, 2005). Most of the published

research focuses on CAI, but there are a few studies that specifically investigate ILS.

Table D.1 Definitions of Technology, CAI, and ILS Term Definition Technology A broad array of tools that can be used to facilitate and support

student learning.

Computer assisted instruction (CAI)

A specific application of technology in which a computer program allows for the dynamic presentation of instructional material and individualized instruction.

Integrated learning systems (ILS)

An adaptive sequence CAI software package that includes content individualized to a child’s learning needs and an assessment system that provides feedback to the teacher regarding individual progress.

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Integrated learning systems (ILS) were first noted in schools in the 1970s and 1980s.

These initial ILS were teacher-independent systems that covered a comprehensive curriculum

and provided assessment data on the students (Paterson et al., 2003). ILS gained favor because

of the issues with most of the other educational technology during this time (Becker, 1992).

Most computer software was poorly designed and difficult to use (Paterson et al., 2003). In

addition, most teachers were uncomfortable with technology as a classroom tool (Paterson et

al., 2003). ILS were thought to overcome these obstacles and provide “research-supported

reading programs to enhance reading achievement and technological interventions that

promise quick improvement with their ‘teacher-proof’ programs” (Paterson et al., 2003, p.

175). These early ILS were based on behavioral assumptions about learning and used

reinforcement, feedback, shaping, rehearsal, and hierarchical skill building (Paterson et al.,

2003). As Clements (1985) noted, many of the early ILS emphasized “content rather than

process and the mechanical rather than the meaningful” (as cited in Paterson et al., 2003, p.

175).

In the 1980s, ILS lost favor as educators moved towards more constructivist theories

and the principles of Vygotsky’s social constructivism (Paterson et al., 2003). Because of this

shift in thinking, software developers started examining how computers might assist students in

the construction of meaning around literacy. The ILS regained favor in the 1990s in reaction to

a perceived literary crisis (Paterson et al., 2003). In a review of the advantages of the new ILS,

Becker (1992) noted that the newer systems offered individualized instruction and flexible time

and data management systems; however, his review did not provide an endorsement of ILS,

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with Becker emphasizing that there was not enough credible research to say that ILS was better

than teacher instruction.

In the late 1990s and 2000s, ILS vendors started marketing their products specifically to

very young children, in part because innovations in graphics, animation, and sound made the

systems more engaging (Paterson et al., 2003). The companies marketed these new and

improved ILS as “highly effective, systematic approaches to literacy instruction that will help

emergent readers acquire and practice skills in basic print concepts, the alphabetic principle,

phonological awareness, word identification, and other reading subskills” (Paterson et al., 2003,

p. 176). Since the introduction of ILS to young children, very few researchers have investigated

the software developers’ claims that ILS help develop early literacy skills.

Research on ILS

Several researchers have noted the lack of high-quality research on the effectiveness of

ILS on literacy achievement (Paterson et al., 2003; Tracey & Young, 2007). Most of the studies

on ILS and literacy skills have produced mixed results, and it is difficult to draw conclusions.

Bauserman, Cassady, Smith, and Stroud (2005) investigated the efficacy of PLATO’s Beginning

Reading for the Real World on kindergartener’s emergent reading skills. Their study found large

effect sizes for phonological awareness and concepts about print (Bauserman et al., 2005).

Both Tracey and Young (2007) and Cassady and Smith (2004, 2005) investigated the

effectiveness of another popular ILS, the Waterford Early Reading Program. The results from

these three studies indicated that the Waterford Early Reading Program had a statistically

significant impact on young students’ early literacy skills, particularly their phonological

awareness skills. In addition, Cassady and Smith’s (2005) study found the ILS to be particularly

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effective for students with the lowest initial reading skills. Conversely, Paterson et al. (2003)

studied the same ILS and found no benefits; instead, the researchers found that literacy

facilitation by the teacher and instructional time were much more important to early literacy

success. The study by Paterson et al. (2003) is one of the few studies on CAI and early literacy

development to consider the context of the technology integration and approach their research

from a social learning perspective.

Despite the mixed results, there are generalizations that can be made from the

research. First, ILS should not supplant teacher-led instruction; instead, ILS appear to be most

effective when integrated into the existing classroom curriculum (Cassady & Smith, 2004). In

addition, Cassady and Smith (2004) noted two broad generalizations about technology and

literacy in their review of ILS: “(a) Gains in research on computer-based tools are typically short-

lived due to the limitations in scope and content in most computer packages, and (b)

methodological design issues have hindered the examination of the impact of ILS in realistic

instructional settings” (p. 950).

Overall, studies on the effects of CAI and ILS on early literacy skills have generally found

positive effects; however, these studies often focus narrowly on one population or one aspect

of literacy while ignoring the broader context of technology use in early literacy classrooms.

Many researchers assert that there just is not enough evidence to endorse the widespread use

of CAI and ILS in classrooms (Blok et al., 2002; Cassady & Smith, 2005; Paterson et al., 2003). In

addition, a synthesis of the findings is difficult and definitive recommendations for integrating

technology into an emergent literacy curriculum are hard to make because early literacy skills

are defined and assessed very differently across studies.

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APPENDIX E

ADDITIONAL METHODOLOGY

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Introduction

The purpose of this study was to determine the effectiveness of Istation®, an integrated

learning system (ILS), on the early literacy skills of kindergarten students. In addition, I

investigated the relationship between the level of literacy support provided by teachers in the

classroom and the early literacy skills of their students.

Research Design

Based on the nature of the research questions, this investigation was conducted using a

embedded mixed methods approach (Teddlie & Tashakkori, 2009). In embedded mixed

designs, the researcher embeds qualitative data within a quantitative investigation. There are

three main advantages to combining quantitative and qualitative data in a single study:

1. Mixed-methods research can simultaneously address a range of confirmatory and exploratory questions;

2. Mixed-methods research provides better (stronger) inferences; and

3. Mixed-methods research provides the opportunity for a greater assortment of divergent views (Teddlie & Tasshakori, 2009, p. 33).

The opportunity for a divergent views and multiple realities is a particularly important aspect of

why I chose a mixed-methods approach, as it aligns with Labbo and Reinking’s (1999) multiple

reality theoretical framework for technology and literacy. This approach allowed me to conduct

a more complete analysis of the relationship between technology and early literacy learning.

The first quantitative stage measured the gains made in literacy achievement by students using

technology and students not using technology. A second qualitative stage, embedded within

the first stage, collected observational and interview data on the teachers and classrooms

within these twelve classrooms.

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Figure E.1. Mixed method embedded experimental design. The qualitative data were used to create a teacher variable that was used to match participants for propensity score matching as well as a three-level independent variable for the second research question.

The qualitative data were used to match participants in the study, and to create an additional

independent variable for the second and third research questions. In addition, by examining

teacher and classroom variables through interview and observation, I was able to more

adequately account for the contribution of various teacher and classroom variables when

matching students and creating control and treatment groups. As Macaruso and Walker (2008)

note, “Most studies that attempt to assess the benefits of [technology] to supplement reading

instruction do not include adequate controls for teacher and classroom variables, and these

variables may have a significant impact on the academic performance of young children” (p.

271).

The first research question for this study related to differences in literacy learning

between two groups. The variables for this analysis were determined by the nature of the

research question. The independent variable was a dichotomous technology variable

(Istation®/no Istation®). The dependent variable was literacy learning; however, literacy is a

complex construct that can be defined and evaluated through many different outcome

measures. To accurately reflect an emergent literacy perspective and the complexity of

literacy, I chose Clay’s Observation Survey (2002) to measure literacy learning. Clay’s survey

QUAN

qual

Analysis and Interpretation based on QUAN (qual)

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can be broken down into several related dependent measures. These subskills include

alphabetic knowledge, concepts of print, word recognition, hearing sounds and letters in

dictation, writing vocabulary, and reading level, for a total of six possible dependent variables;

however, the reading level subtest of Clay’s survey was replaced by another reading level

measure for the analysis for this study. The additional reading level dependent variable was

assessed using the Developmental Reading Assessment [DRA2] (2006), an individually

administered assessment of a child's reading capabilities. The DRA2 was chosen because it is an

existing assessment in all the classrooms to be studied.

Figure E.2. Diagram of the dichotomous independent variable (Istation® vs. no Istation® ) and the dependent variable (early literacy skills) as measured by six outcomes from the DRA and Clay’s Observational Survey. The analysis of the second research question used a three-level categorical variable to

characterize teachers’ implementation of literacy (low, medium, high facilitation of literacy).

The teacher variable was measured using qualitative measures, including an adapted teacher

Independent Variable Dependent Variable

Measured By:

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survey (Paterson et al., 2003), classroom observation, and research memos. Definitions for low,

medium, and high facilitation of literacy were developed a priori.

Figure E.3. Diagram of Variables and Outcomes for Research Question Two

Figure E.3. Diagram of the three-level independent variable (high, medium, or low teacher literacy support) and the dependent variable (early literacy skills) as measured by six outcomes from the DRA and Clay’s Observational Survey.

Instrumentation/Materials

DRA2. The Developmental Reading Assessment-2 (DRA2) is a widely used, criterion-

referenced reading assessment for children in kindergarten through third grade (Beaver, 2006).

It is modeled after an informal reading assessment and uses authentic texts to measure

students’ independent reading level. Typically, classroom teachers administer, score, and

interpret the individually administered assessment on an annual or semiannual basis (Rathvon,

2006). The DRA2 takes approximately 20 to 30 minutes to administer. In addition to identifying

students’ independent reading level, the DRA2 helps classroom teachers identify students’

Independent Variable

Dependent Variable

As Measured By:

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reading strengths and weaknesses for the purpose of planning instruction and documenting

growth in reading skills. I chose the DRA2 as an outcome measure for independent reading

level for this study because both District A and District B already use the assessment to

determine the reading levels of their students at mid-year and end-of-year. Both districts

conducted training on the DRA2 with their teachers within the last year and required teachers

to use the leveled books provided with the DRA2 kit and follow all assessment protocols as

outlined in Bever (2006). Reliability data from the DRA2 technical manual (2009) indicate that

both inter-rater reliability estimates and rater-expert reliability estimates were moderate to

substantial.

The DRA2 has two components: an oral reading survey and an individual reading

conference. During the individual reading conference, the student reads a designated text,

selected by the teacher. While the student reads aloud, the administrator uses a text-specific

observation guide to note and record nine different reading behaviors. An accuracy score is

computed based on the total number of errors during the read aloud. Comprehension is

measured through a retelling of the story, during which the administrator marks elements of

the story on a provided checklist. For the purpose of this study, only the participants’ reading

level will be considered for analysis.

There are several aspects about the DRA2 administration that affect the reliability and

validity of students’ reading levels. As with most informal reading assessments, subjective

judgments about text selection and scoring must be made. Studies of interrater reliability

among different administrators of the DRA2 have found interrater agreements vary widely;

however, most estimates of interrater agreement fall within the good to acceptable range

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(Weber, 2000). Test-retest reliability coefficients were high in a study on students in first grade

through third grade, rs = .92-.99 (Weber, 2000). In addition, one study (Williams, 1999)

provided internal consistency data that indicated a high level of internal consistency across

DRA2 texts (Cronbach’s alpha = .97). Studies and reviews of the content and construct validity

have been mixed and inconsistent, but generally support the use of the DRA2 to provide useful

data on young students’ reading abilities (Rathvon, 2006). Because of the high demands placed

on teacher judgment during administration and scoring, other measurements of literacy skills

will be used to help create a complete picture of the participants’ abilities for this study.

Clay’s Observation Survey. Like the DRA2, the Observation Survey of Early Literacy

Achievement (OS; Clay, 2002) is an individually administered assessment tool that is widely

used in early literacy classrooms in the United States. Primarily used for screening, planning

instruction, and monitoring, the OS provides a way for teachers to systematically observe early

literacy competencies (Denton, Ciancio, & Fletcher, 2006). Clay’s OS was chosen as a measure

for this study because of its ability to assess early literacy skills in the context of authentic

literacy tasks. Research suggests that authentic literacy assessments provide a more accurate

measure of young student’s reading abilities than more standardized measures (Barnhart,

1991; Hodges, 1997; James & Tanner, 1993; Quay & Steele, 1998; West, 1998). In addition,

there is a large variability in the early literacy skills of kindergarteners, and this variability is still

present at the end of kindergarten. The Observation Survey is able to capture and measure this

variability.

The survey has six subtests including the Running Record of Text Reading (Text Reading),

Letter Identification, Concepts About Print, Word Reading, Writing Vocabulary, and Hearing and

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Recording Sounds in Words. For the purpose of this study, all subtests were administered

except for the Text Reading. The Text Reading subtest was replaced by the DRA2 reading level

score. The five remaining subtests allowed me to assess multiple aspects of literacy in an

authentic context. Clay does not specify an order of administration for the subtests; however,

for consistency among participants, the tests were administered in the following order: Letter

Identification, Concepts About Print, Word Reading, Hearing and Recording Sounds in Words in

Dictation, and the Writing Vocabulary Test. A brief description of the five subtests follows:

1. Letter Identification: This task asks children to identify all the uppercase and

lowercase letters, plus the “printer’s” g and a. Directions for this subtest state that students

may identify a letter by its name, sound, or a keyword; however, the 2002 OS manual suggests

that optimal administration of the Letter Identification task would include only asking for the

letter sound. For the purpose of this study, the student will be asked for the letter sound only

and assigned a score between 0 and 54.

2. Concepts About Print: During this subtest, the administrator reads a specially

designed book, asking specific questions on each page. The 24 questions are scripted and

scored as correct or incorrect. Among the concepts tested are locating the front of the book,

directionality, one-to-one correspondence between the printed words and spoken words, and

the purpose of punctuation marks.

3. Word Reading: This OS task requires students to read words from a word list.

Several word lists are provided. For the purpose of this study, students will be asked to read

List A of the Ohio Word Test, which has 20 words. Students are scored correctly and given a

point for each word read correctly.

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4. Writing Vocabulary: During this task, students will be given a blank piece of paper

and a pencil and asked to write as many words as they can within a 10-minute period. The

administrator may provide prompts during this subtest. Prompts will be standardized for this

study. For maximum efficiency, this task will be given to the entire class at the same time.

Students will be given one point for each word that they spell correctly during this task. Any

word walls or other sources of information will be covered during this task.

5. Hearing and Recording Sounds: To assess a student’s ability to hear and record

sounds, the administrator reads a provided sentence and then repeats each word one at a time

while the students write the words. Students are given one point for each correctly recorded

phoneme. The maximum possible score is 37. For the purpose of this study, this task will be

given to the entire class at the same time.

While the scores of the subtests cannot be combined to create a composite score, the

scores on each of the subtests can be converted to normed stanine and percentile scores;

however, for this study, raw scores will be used for comparison. Interval data, such as the raw

scores from the OS will allow a more meaningful analysis of the data than the ordinal data of

stanine scores.

Similar to the DRA2, there are several concerns about the reliability and validity of an

assessment that requires subjective judgment during administration and scoring. An evaluation

of the reliability and validity of the OS by Denton, Cianco, and Fletcher (2006) found that the OS

had utility in some areas and that it “can be validly implemented to assess components of early

reading development” (p. 9); however, this same study urged caution in using the OS in studies

of program evaluation because the use of continuous scale variables, such as stanines, limit the

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analysis and interpretation of OS on a group level. Acknowledging this limitation, Gomez-

Bellenge & Rodgers (2004) suggest that the OS subtests can be used in program evaluation but

that the data “need to be analyzed with caution” (p. 46).

Procedure

Project design. All students in the studied classrooms followed the district-mandated

curriculum for kindergarten. District A, the treatment group, requires its teachers to use

Istation® as part of the kindergarten curriculum, while District B, the control, does not. All of

the studied schools in District A began Istation® use by the third or fourth week of school. The

average time that each of the treatment participants spent on Istation® was 135 minutes per

week. Both District A and B base their literacy instruction on the Texas Essential Knowledge

and Skills (TEKS), which are state standards for what students should know and be able to do at

each grade level. In addition, both districts encourage an emergent literacy approach in their

kindergarten classrooms, with authentic, integrated methods of instruction, including shared

reading, guided reading and journal writing. The current study was conducted during the 2013-

2014 school year.

Baseline measure of reading achievement. Because of the diverse nature of the schools

and teachers in naturalistic inquiries, it is often difficult to obtain pretest scores that can be

used across participants for baseline comparisons. For this reason, I chose letter identification

as a baseline measure for this study. Letter identification is a widely used screening and

assessment tool in many kindergarten classrooms. Kindergarten teachers use this easy-to-

administer assessment as a way to efficiently gauge their students’ initial levels of literacy

learning. While letter identification measures do not provide a complete picture of a student’s

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literacy abilities, there is considerable research on the correlation between letter identification

and word reading (Clark, Hulme, & Snow, 2005; Neuhaus, Foorman, Francis, & Carlson, 2001;

Wolf & Obregon, 1992). Other researchers have found correlations between letter

identification and future reading ability (Bishop & League, 2006; Schatschneider, Fletcher,

Francis, Carlson, & Foorman, 2004). Letter identification is also a strong predictor of reading

disabilities among kindergarten and first grade students (O’Connor & Jenkins, 1999). All of the

participating teachers collected beginning of the year letter identification data within in the first

six weeks of the school year. These scores were used as a baseline measure of achievement for

the propensity score matching.

Controlling for teacher variables. Each kindergarten classroom was observed for a total

of four hours during literacy instruction during February 2014. Most classrooms were observed

two times for half days, averaging two hours for each observation. Observation protocols were

adapted from Paterson et al.’s (2003) study on a similar integrated learning system. The

following data were recorded on uniform observation worksheets: (a) Description of the

classroom, (b) start/end time of activities, (c) materials used for the lesson, (d) teacher

behaviors, and (e) child behaviors.

Coding of observations. The purpose of collecting the observational data was to

determine the level of early literacy support provided by each of the participating teachers.

Prior to conducting the classroom observations, I constructed teacher profiles and a coding

framework for low literacy support, medium literacy support, and high literacy support, using

descriptions of effective early literacy practices from the research (Cunningham & Allington,

2010; Thompkins, 2014). The coding framework listed and described 15 effective literacy

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practices. Each of the 15 literacy practices included a detailed three-level description for low

literacy support, medium literacy support, high literacy support (see Appendix A for the

complete coding framework).

Description of the classroom: The classroom has a horseshoe table where the teacher gathers to work with children in small groups. Library center has a bright rug and bean bag chairs. Student work is displayed on walls and bulletin boards. Large rug for large group gathering near the front of the room, with the dry erase board in front. Children sit at five small, round tables. Start/end Materials Used Teacher behaviors Child behaviors

Time record sequences by minute

Note materials used by teacher and students in segment observed

Describe what teacher is doing Describe interaction with children Describe instructional sequence

Describe student actions Describe groups Note content of activity

9:00 am-9:15 am

9:15 am- 9:45 am

Figure E.4. Example of the worksheet used to record observations in each of the twelve classrooms. Adapted from “Investigating the Effectiveness of an Integrated Learning System on Early Emergent Readers,” by W.A. Patterson et al., 2003, Reading Research Quarterly, 38, p. 191. Copyright 2003 by International Reading Association.

Using the original field notes, I coded the teacher behaviors and classroom interactions

as low, medium, or high according to each of the 15 literacy practices in the matrix. Based on

patterns of support in the coding, I determined an overall profile for each teacher and placed

the teachers into one of the three levels of literacy support.

Intercoder agreement. To establish intercoder agreement on the observational data, I

asked a language and literacy doctoral candidate, who was also a certified teacher with 11

years of experience in the lower grades, to code a random sample of four observations using

the coding framework. This check coding was done after the observations were completed.

After a 30-minute training session, the doctoral student coded the teachers using the original

field notes from the observations as high, medium, or low on all 15 of the effective literacy

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practices and assigned each teacher an overall profile. Agreement on the overall level of

literacy support provided by the teachers in the four observations was 100%.

Research memos. Shortly after each observation, I created a research memo that

contained reflective notes about the classroom observation and teacher behaviors. I noted any

relevant comments the teacher made to me and also noted emerging patterns, insights, and

connections in the observational data.

Teacher survey. The twelve participating teachers were asked to complete a survey of

literacy practices adapted from a survey by Paterson et al. (2003). The survey had a checklist of

12 components commonly found in early literacy programs as well as open-ended questions.

The 12 components ranged from shared reading to writer’s workshop. Teachers were asked to

rate each these components on a scale from 1 to 3, based on how important the component

was to their literacy curriculum (see Appendix B). The open-ended questions on the survey

asked teachers to further explain their future goals, areas of strength in literacy instruction, and

differentiation strategies. The teachers who used Istation® were also asked about the best

features and biggest concerns regarding the program. The list of practices the teachers

identified as a critical part of their curriculum were coded as high, medium, and low literacy

support using the same coding matrix developed for the observational data. The list of practices

the teachers identified as a critical part of their curriculum were triangulated with the coding on

the teachers’ observed literacy practices as well as the research memos to confirm the level of

literacy support provided by the teachers. The individual teacher profiles provided a practical

synthesis of the three qualitative data sources. The teacher profiles (high, medium, low)

created from the observational data and teacher surveys were then used for two purposes: (a)

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as a covariate in creating propensity scores to match students for the study, and; (b) as an

independent variable in the second and third research questions about the effect of this

support on the literacy learning of the kindergarten students.

Measuring literacy achievement. Data on participants’ literacy achievement was

collected during February 2014 from two sources:

1. DRA2: The twelve participating teachers provided students’ middle of the year DRA2 [MOYDRA2] scores to me. This teacher-administered individual assessment was given to all participants in January 2014. This measure was used to determine participants’ independent reading levels.

2. Observation Survey: Two trained research assistants and I individually administered five subtests of the Observation Survey to the 150 students who returned the consent forms. Subtests included hearing and recording sounds, writing vocabulary, letter sound knowledge, concepts about print, and word reading. Each testing session averaged approximately 30 minutes.

Training. The two research assistants who assisted in collecting data for this study were

certified teachers with master’s degrees in education and a combined 55 years of teaching

experience. The assistants had backgrounds in early childhood, elementary education, English

as a second language (ESL), special education, and speech pathology. Each of the research

assistants conducted approximately a third of the Observation Surveys. Assistants were trained

on the Observation Survey during a one-hour session with me. Standardization of the

assessment was accomplished through a detailed protocol for the order of subtests, materials,

instructions during the assessment, and scoring guidelines. All assessments were scored

together and any discrepancies were reviewed and resolved according to the protocols

established for the assessment.

Data Analyses

Randomized control trials (RCT) are considered the gold standard approach to

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conducting research and estimating causal effects (Austin, 2011). RCTs allow researchers to

draw causal conclusions from the analysis, a goal of many researchers; however, RCTs are

nearly impossible to conduct in educational research because of the nature and structure of

educational settings. In recent years, there has been a growing interest in finding new

approaches to estimate causal effects in nonrandomized studies (Austin, 2011). Many of these

new approaches have suggested that observed bias can be removed from estimated treatment

effects by incorporating covariates, based on sound theory and previous research, into the

statistical models (Murnane & Willett, 2011). In theory, these covariates would help

researchers account for differences in baseline characteristics between treated and untreated

participants in a study, allowing them to estimate the true effects of treatment on the

outcomes (Austin, 2011). Accounting for these differences in characteristics between the two

groups in an observational study would mimic the random selection of participants in an RCT

and recreate a population that would have been expected in a randomized experiment

(Thoemmes & Kim, 2011).

One way to mimic the random selection of participants of a RCT in an observational

survey is propensity scores (Rosenbaum & Rubin, 1983). Rosenbaum and Rubin (1983) defined

propensity scores as the conditional probability of treatment assignment based on certain

observed baseline covariates. More simply, the propensity score is the predicted probably of

treatment after accounting for important matching variables (Reutzel, Spichtig, & Petscher,

2012). Propensity scores are most often estimated using logistic regression, “in which

treatment status is regressed on observed baseline characteristics” (Austin, 2011, p. 403).

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The overarching assumption when estimating propensity scores is unconfoundedness

(Murnane & Willett, 2011). That is, the researcher assumes that all variables that influence and

affect treatment assignment have been accounted for in the statistical model (Austin, 2011;

Murnane & Willet, 2011; Reutzel, Spichtig, & Petscher, 2012). The goal or objective for a

researcher using propensity scores is to select a sequence of variables that are considered

important in matching participants (Reutzel, Spichtig, & Petscher, 2012). If the theory and

history on which the researcher bases his/her selection of covariates is good, then the model is

sound and causal inferences can be made (Reutzel, Spichtig, & Petscher, 2012; Thoemmes &

Kim 2011). As Thoemmes & Kim (2011) point out, “Under the assumption that all relevant

covariates have been assessed, a propensity score analysis can yield unbiased causal effect

estimates” (p. 92). It should be noted that the assumption of unconfoundedness cannot be

empirically tested; instead, researchers must attempt to provide theoretical and empirical

evidence that all relevant covariates have been included in the model (Thoemmes & Kim,

2011).

While unbiased causal effect estimates are a desirable outcome, there has been no

consensus as to which variables to include in propensity score models (Austin, 2011).

Researchers have suggested many possibilities for variable inclusion, suggesting that all

measured baseline covariates should be included or that all baseline covariates associated with

treatment assignment should be included (Austin, 2011). Other researchers suggest including

all covariates that affect the outcome or including all covariates that affect both the treatment

assignment and the outcome (Austin, 2011). Still others have suggested nonparsimonious

models, in which all variables are included. As Rubin & Thomas (1996) note, “Unless a variable

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can be excluded because there is a consensus that it is unrelated to the outcome or is not a

proper covariate, it is advisable to include it in the propensity score model even if it is not

statistically significant” (p. 253).

Because randomly assigning children to use or not use Istation® was not possible,

matched control and treatment groups were constructed for this study through the use of

propensity score matching in order to control potential variation (beyond the instructional

format presented) at the participant level. This approach allowed for quasi-experimental

comparisons between children in naturally occurring treatment and control groups. Propensity

score matching is one way to mimic the random selection of participants of a randomized

control trial (RCT) in an observational survey (Rosenbaum & Rubin, 1983). Because of its ability

to reduce selection bias, propensity score matching is increasingly being used in educational

research (Graham & Kurleander, 2011; Murnane & Willet, 2011).

Rosenbaum and Rubin (1983) defined propensity scores as the conditional probability of

treatment assignment based on certain observed baseline covariates. More simply, the

propensity score is the predicted probably of treatment after accounting for important

matching variables (Reutzel, Spichtig, & Petscher, 2012). The goal or objective for a researcher

using propensity scores is to select a sequence of variables that are considered important in

matching participants (Reutzel, Spichtig, & Petscher, 2012). If the theory and history on which

the researcher bases his/her selection of covariates is good, then the model is sound and causal

inferences can be made (Reutzel, Spichtig, & Petscher, 2012; Thoemmes & Kim 2011). The goal

of the researcher is to select significant matching variables based on theory and research. In

early literacy research, these variables include gender(Below, Skinner….., 2010; Chatterj, 2006),

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age (Huang & Invernizzi, 2012), race/ethnicity (Chatterji, 2006), socioeconomic status (Chatterji,

2006; D’Angiulli, Siegel, Hertzman, 2004; Taylor, Schatschneider, 2010; Ready, 2010), English

language learner status (Gottardo & Mueller, 2009; Yesil-Dagli, 2011), level of literacy support

by the teacher (Boonen, Van Damme, Onghena, 2014; Konstantopoulous, 2011), and some type

of baseline measure of achievement (Bishop & League, 2006; Schatschneider et al., 2004). The

propensity scores are then estimated using logistic regression in which the treatment status is

regressed using the relevant covariates to create a probability score for being in the treatment

group (Austin, 2011; Sadish, Cook, & Campbell, 2002). Once propensity scores are estimated for

participants from the control and treatment groups using logistic regression, the probabilities

are then used to match students who received the treatment with those who did not receive

treatment (Austin, 2011; Reutzel, Spichtig, & Petscher, 2012). By matching participants with

similar propensity scores the measured covariates will be more equally distributed among the

treated and control groups (Austin, 2011). As Thoemmes & Kim (2011) note, “The assumption

is that the matched samples of children are identical (or at least comparable) on many

background characteristics and only differ in their [treatment] status—just as we would expect

from a randomized experiment” (p. 93). I used both theory and prior empirical research to

identify variables that influence young children’s early literacy skills. Participants for this study

were matched on the following variables: (a) Age on the first day of kindergarten, (b) gender,

(c) ethnicity, (d) free and reduced lunch status, (e) English language learner status, (f) beginning

of year letter identification score, and (g) level of literacy support provided by the teacher (low,

medium, high).

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Participants

Participants for this study were chosen from 12 kindergarten classrooms within two

north Texas suburban school districts. District A is located in a medium-size suburb while

District B is a located in a large suburb in the same area. The six treatment classrooms were

located in three schools within District A. District A integrates Istation® into its kindergarten

literacy curriculum and requires all teachers to use the program regularly. The remaining six

classrooms served as a control and were located in three schools within District B. District B

integrates technology regularly into the kindergarten curriculum; however, the district uses a

more traditional curriculum to directly instruct students in literacy.

Selection of schools. Because of the differences in the demographic data between the

two districts and in order to create a more balanced sample for matching, I used purposeful

sampling to select three comparable schools in each district. Choice of schools was based on

my desire to create a diverse sample from which to collect data, I chose one school from each

district that was not classified as Title 1, one school that was classified as Title 1, and one that

was both Title I and had a high English language learner (ELL) population. The schools were

matched as closely as possible on school size, percentage of economically disadvantaged

students, ELL population, and ethnic and minority composition.

Selection of teachers. After meeting with each the school principals, I asked the

principals to provide the names of two kindergarten teachers who would be willing to

participate in the study. All students in the kindergarten classrooms of the teachers who

volunteered were asked to participate in the study.

Student participants. One hundred fifty students returned the consent forms for the

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study. The final analysis included 72 students matched through propensity score matching,

with 36 students in each of the treatment and control groups.

The full sample of 150 students was used to match students. In the data set, 80 of these

participants were in the treatment group while 70 participants were in the control group. An

initial propensity score was estimated using the seven variables derived from early literacy

theory and research. Treated and untreated participants were matched using an optimal,

nearest neighbor with caliper matching algorithm (Austin, 2011). The caliper width used was

equal to 0.2 of the standard deviation of the logit of the propensity score (Austin, 2011; other

references). Research has confirmed that caliper matching leads to improved balance on

baseline covariates and less bias in treatment effect estimates (Austin, 2014). When

participants who used Istation® were matched with participants who did not use Istation®

based on the logit of the propensity score algorithm, 36 matched pairs were formed, for a total

sample of 72 participants. Once students were matched, two analyses were conducted on the

data to answer the three research questions:

1. A descriptive discriminant analysis (Huberty, 1994) was conducted to evaluate the

effect of Istation® on the early literacy skills of kindergarteners and to determine which

variables contributed to any differences between the two groups;

2. A 2 X 3 multivariate between-subjects analysis of variance (Istation®: No/Yes X

Teacher Support: Low/Medium/High) was conducted to test for main effects for level of

teacher literacy support and to test for a multivariate interaction between Istation® and level of

teacher literacy support.

117

APPENDIX F

ADDITIONAL RESULTS

118

This appendix contains additional results, supplementing the data summarized in the

main body of the dissertation article.

Table F.1 Skewness of Data Before and After Box-Cox Transformation Procedures (xnew = (xλ-1)/λ)

Dependent Variable Skewness of Data Before Skewness of Data After Box-Cox Transformation

MOYDRA2 1.31 -.032 OS Hearing Sounds -1.44 -.002 OS Writing Vocabulary .17 .052 OS Letter Sound Knowledge -2.03 -.002 OS Concepts About Print -.58 -.023 OS Reading Words -.26 .001

Table F.2 Mean Differences on Literacy Skills as Measured by Level of Teacher Support

Dependent Variable (I) Level of Teacher Support

(J) Level of Teacher Support Mean Difference (I-J)

MOY DRA2 Low Medium -.58 High -1.91*

Medium Low .58*

High -1.33*

High Low 1.91* Medium 1.33*

OS Hearing Sounds Low Medium -3.77

High -3.75

Medium Low 3.77 High .02

High Low 3.75 Medium -.02

OS Writing Low Medium 1.77

High -.36

Medium Low -1.77 High -2.13

High Low .36 Medium 2.13

(table continues)

119

Table F.2 (continued).

Dependent Variable (I) Level of Teacher Support

(J) Level of Teacher Support

Mean Difference (I-J)

OS Letter Sounds Low Medium -1.68 High -.49

Medium Low 1.68 High 1.19

High Low .49 Medium -1.19

OS Concepts About Print Low Medium -1.55

High -2.42*

Medium Low 1.55 High -.86

High Low 2.42* Medium .86

OS Reading Words Low Medium -2.99

High -4.92*

Medium Low 2.99 High -1.93

High Low 4.92* Medium 1.93

*p < .05 according to analyses run on transformed data.

120

Table F.3 Group Means According to Istation® Use and Level of Teacher Support

Group Level of Teacher Support

Mean Std. Deviation N

MOYDRA2 Control Low 3.20 1.304 5 Medium 3.38 1.758 13

High 4.89 2.888 18 Total 4.11 2.435 36

Istation® Low 2.25 1.258 4 Medium 3.33 1.915 15

High 4.47 2.528 17 Total 3.75 2.260 36

Total Low 2.78 1.302 9 Medium 3.36 1.810 28

High 4.69 2.687 35 Total 3.93 2.340 72

OS Hearing Sounds Control Low 28.00 15.264 5

Medium 28.08 6.396 13 High 26.50 10.388 18 Total 27.28 9.679 36

Istation® Low 22.00 11.916 4 Medium 30.00 8.552 15

High 31.82 7.691 17 Total 29.97 8.798 36

Total Low 25.33 13.407 9 Medium 29.11 7.554 28

High 29.09 9.438 35 Total 28.63 9.283 72

(table continues)

121




OS Writing Control Low 17.00 12.884 5 Medium 18.54 7.043 13 High 15.06 9.662 18 Total 16.58 9.163 36 Istation® Low 20.50 15.330 4 Medium 15.27 10.117 15 High 23.00 11.219 17 Total 19.50 11.505 36 Total Low 18.56 13.211 9 Medium 16.79 8.825 28 High 18.91 11.052 35 Total 18.04 10.431 72

OS Letter Sounds Control Low 49.40 5.413 5


Istation® Low 48.50 6.608 4 Medium 52.27 2.017 15 High 51.35 3.856 17 Total 51.42 3.667 36

Total Low 49.00 5.590 9 Medium 50.68 4.497 28 High 49.49 6.849 35 Total 49.89 5.840 72

(table continues)

122




OS Concepts About Print

Control Low 16.80 2.049 5 Medium 17.08 1.847 13 High 18.39 3.127 18 Total 17.69 2.628 36



OS Reading Words Control Low 9.20 6.760 5




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