roberts (2002)-role of computers in restructuring

8/7/2019 Roberts (2002)-Role of Computers in Restructuring

1/134

ORIGINAL COPY

This thesis copy is a reading copy made available by the author.

"In life we make the best mistakes we know how to make.

Then, with luck, we go out and make new ones."

Joan Oliver Goldsmith,How Can We Keeping from Singing? (Norton)

The very aim and end of our institutions is just this:

that we may think what we like and say what we think.

Oliver Wendell Holmes

It's not that I'm so smart it's just that I stay with problems longer.

Albert Einstein

"The wisdom of the wise and the experience of the ages

are perpetuated by quotations."

Benjamin Disraeli, Earl of Beaconsfield (1804-1881)


2/134

ii

ABSTRACT

THE ROLE OF COMPUTERS IN SCHOOL RESTRUCTURING:A META-ANALYSIS

This study explored how educators can more effectively use computer

technology to meet the needs of 21st

century students. David Jonassen proposes

that the effectiveness of computers as instructional tools depends upon how they

are used. An exploratory meta-analysis was performed to examine the relationship

between instructional technique and computer use and their combined effect on

student achievement. The results suggest that the instructional technique of

collaborative learning, in conjunction with the use of computers as a tool,

facilitates learning better than any other such combination of variables

investigated. Additionally, the findings support Jonassens theory that the way

computers are used in instruction determines the extent to which they affect

learning. Further, computers used as MindTools had the largest effect on student

achievement of all methodologies included in the meta-analysis. Finally, the

findings suggest that computers greatest impact on student achievement seems to

occur among students in grades 6 12.

Robin Michael RobertsDecember 2002


3/134


4/134

THE ROLE OF COMPUTERS IN SCHOOL RESTRUCTURING:

A META-ANALYSIS

by

Robin Michael Roberts

A thesis

submitted in partial

fulfillment of the requirements for the degree of

Master of Artsin Education

in the Kremen School of Education and Human Development

California State University, Fresno

December 2002


5/134

2002 Robin Michael Roberts

All Rights Reserved


6/134

APPROVED

For the Department of Curriculum and Instruction:


7/134

AUTHORIZATION FOR REPRODUCTION

OF MASTERS THESIS

Permission to reproduce this thesis in part or in its entirety must be obtained from

the author.


8/134

ACKNOWLEDGMENTS

This thesis has been what might be termed an exercise in actuality: doing

what one is studying. Collaborative computing is both studied and practiced in the

present study. One person cannot complete a study like this alone. Thus, I found

myself collaborating with a number of peopleyet nearly always within the

context of larger groups. In most cases, there we re three members in each group

that participated with me in this endeavor. I would like to thank those individuals

and the groups of which they were a part:

First, my three thesis advisors deserve a great deal of the credit for bringing

this thesis to its present form. Dr. Roy Bohlin and his wife Dr. Carol Fry Bohlin,

and Dr. Susan Tracz provided encouragement, insight, and information when

needed and pushed me to greater economy of prose and clarity of organization.

Roy Bohlin, especially, has been a good friend and teacher for five years and

shares with me whatever rewards accrue from the finished product.

Secondly, three professors not on my thesis committee played important

parts in the early development of this thesis: Dr. Susan Harris, Dr. Sharon Brown-

Welty, and Dr. Ron Unruh. Each of them, in their classes, provided the

opportunity, motivation, and training for much of what eventually became the

review of literature. In addition, each also provided, in different ways,

encouragement and support long after the last day I attended their class.

Three projects provided financial and collegial support during the time I

was engaged in writing and researching this study: The San Joaquin Valley

History-Social Science Project, the Teaching And Leading for Educational Needs

with Technology (TALENT) Project, both at California State University, Fresno


9/134

vi

and the Teacher-Researcher Initiative Project (TRIP) at the University of

California, Los Angeles.

Collaboration also took place within more informal, social contexts. Three

colleagues at Pioneer Middle School in Hanford acted as sounding boards for

ideas, discussion partners, and emotional releases for the stresses inevitably

associated with looming deadlines: Rich Callaghan, Principal of Pioneer Middle

School provided encouragement and flexibility in scheduling that allowed me to

physically meet many of these deadlines. Laurie Goodman, Literacy Mentor at

Pioneer Middle School, read parts of the literature review and served as a peer

evaluator and sounding board for many ideas. My classroom aide, Miguel

Rodriguez, took on extra duties to allow me to work on portions of the meta-

analysis and listened sympathetically when things werent working right.

The Three Musketeers created a mutual support group for ourselves.

Henry Placenti and Sopheak Real joined me in running the twin gauntlets of red

tape and deadlines to finish our programs together. The time was more special for

sharing it with these two good friends.

My family provided support throughout the 5 years I spent pursuing my

studies. During that time I spent far less time with them than they deserved, but

still they managed to assist me in numerous ways. My wife, Sylvia, who has been

through this process herself, served as the main collaborator for every idea that

germinated whilst I pursued my degree program. My eldest daughter, Terra, has

joined me at CSU, Fresnowhat fun to attend the same college as your child. Myyoungest daughter, Tamara, began her college career at West Hills during the last

semester in which this thesis was completed.

Lastly, three individuals who are not associated with each other also played

small parts in the process leading to completion of my studies: Mark Cave, D.D.S.,


10/134

vii

my best friend, was a good companion and leant his considerable intellect to the

discussion of several key aspects of the study. My parents, Joe and Maureen

Roberts, remained interested in my education even though they have long since

fulfilled any responsibilities they had for it.

Finally, I wish to thank Kathleen Vandermeer, of the CSUF Graduate Office

for her knowledgeable and skillful editing of the manuscript. She went above and

beyond to see that it was worthy of everyone above and of the university whose

name is on the cover.


11/134

TABLE OF CONTENTS

Page

LIST OF TABLES . . . . . . . . . . . . . . . . . x

LIST OF FIGURES . . . . . . . . . . . . . . . . . xi

Chapter

1. INTRODUCTION . . . . . . . . . . . . . . . 1

Relevance of the Study . . . . . . . . . . . . . 1

Purpose of the Study . . . . . . . . . . . . . . 3

Design of the Study . . . . . . . . . . . . . . 3

Definition of Terms . . . . . . . . . . . . . . 4

2. REVIEW OF THE LITERATURE . . . . . . . . . . 7

Background . . . . . . . . . . . . . . . . 7

Causative Factors for the 21st

Century Educational Imperative . . 8

Characteristics of 21st

Century Students . . . . . . . . 18

School Restructuring . . . . . . . . . . . . . 20

The Role of Computer Technology . . . . . . . . . 26

Computer Use Categories . . . . . . . . . . . . 31

Instructional Techniques Categories . . . . . . . . . 33

Restatement of the Research Question. . . . . . . . . 33

3. METHODOLOGY . . . . . . . . . . . . . . . 36

Introduction . . . . . . . . . . . . . . . . 36

Design of the Study . . . . . . . . . . . . . . 38

Limitations of t he Study . . . . . . . . . . . . 64


12/134

ix

Chapter Page

4. RESULTS . . . . . . . . . . . . . . . . . 66

Introduction . . . . . . . . . . . . . . . . 66

Individual Study Results . . . . . . . . . . . . 66

Results of the Meta-Analysis . . . . . . . . . . . 68

5. DISCUSSION . . . . . . . . . . . . . . . . 74

Controlling for Errors . . . . . . . . . . . . . 74

Accounting for Heterogeneity . . . . . . . . . . . 75

What Effect Size Estimates Represent . . . . . . . . 83

6. CONCLUSIONS . . . . . . . . . . . . . . . 88

Findings . . . . . . . . . . . . . . . . . 88

Discussion . . . . . . . . . . . . . . . . 90

Summary . . . . . . . . . . . . . . . . . 94

Implications of the Study . . . . . . . . . . . . 95

Recommendations for Further Research . . . . . . . . 97

REFERENCES . . . . . . . . . . . . . . . . . 99

APPENDIX . . . . . . . . . . . . . . . . . . 116


13/134

x

LIST OF TABLES

Table Page

1. Categories of Instructional Use of Computer Technology . . . . 34

2. Computer Use (CU) Coding Guide . . . . . . . . . . 47

3. Instructional Technique (IT) Coding Guide . . . . . . . . 47

4. Included Studies . . . . . . . . . . . . . . . 50

5. Number of Included Studies by Year of Publication. . . . . . 52

6. Number of Studies per Subject Age Group . . . . . . . . 52

7. Independent and Dependent Variables for Each Study . . . . . 53

8. Study Independent Variable CU: Computer Use by Year . . . . 55

9. Study Independent Variable IT: Instructional Technique by Year . . 55

10. Notation and Symbols . . . . . . . . . . . . . . 65

11. Complete Individual Study Statistics . . . . . . . . . . 67

12. Meta-Analysis Overall and Sub-Group Statistics: Standardized MeanDifference . . . . . . . . . . . . . . . . . 69

13. Binomial Effect Size Display (BESD) for Al l Studies and Sub-Groups . . . . . . . . . . . . . . . . . 72


14/134

LIST OF FIGURES

Figure Page

1. Intervention variable . . . . . . . . . . . . . . 61

2. Interaction variable . . . . . . . . . . . . . . . 62

3. Interaction in the meta-analysis . . . . . . . . . . . 76

4. Intervention in the meta-analysis . . . . . . . . . . . 77

5. Multiple interactions . . . . . . . . . . . . . . 82

6. Graphic depiction of standardized mean difference . . . . . . 84

7. Overall mean effect of computers . . . . . . . . . . . 84

8. Mean effect of collaborative learning . . . . . . . . . . 85

9. The overall mean effect of computers used as tools . . . . . . 86


15/134

1


16/134

Chapter 1

INTRODUCTION

In recent years, education has experienced an influx of computers into the

classroom. The presence of this new technology has caused many to ask how

computers might best be used to facilitate learning. Many studies have been

conducted that have found that classroom computer use contributes to learning (de

Jong & van Jooligan, 1998; Gerlic & Jarusovec, 1999; Ku & Sullivan, 2000;

Kulik, Kulik, & Cohen, 1980; Shaffer & Hannefin, 1986). Other studies have

found no significant computer-related effect on classroom performance (Barry &

Runyan, 1995; Clark, 1983, 1994; McClure, 1996; Russell, 1999; Wilson, 1996).

Some studies have found that computer use leads to poorer performance on

measures of learning (Brook & Boal, 1995; Healy, 1998; Wenglinsky, 1998).

These conflicting results make it difficult to assess the instructional value of

computers.

A number of hypotheses have been developed to explain the range of

findings obtained from studies of classroom computer use. One such hypothesis,

developed by Jonassen (1996, 2000), suggests that it is not the computer itself that

is responsible for differences in learning, but how the computer is used. While

there is currently little empirical evidence to support Jonassens theory, it has

received favorable attention from many educators.

Relevance of the Study

Beyond the presence of computers in the classroom, the advent of the 21st

century has occasioned another series of questions about the best way to prepare

students for this new century. A number of educators as well as political groups


17/134

2

have questioned whether the current American school system is meeting the

educational needs of 21st century students (Carnegie Forum on Education and the

Economy, 1986; Eastin, 1999; Institute for Learning Technologies, 1999; Layton,

2000; National Commission on Excellence in Education, 1983; Selfe, 1999; Smith

& Curtin, 1998;). Among the reasons cited for this concern are the shift from an

industrial age economy to a knowledge economy (Bowman, 1996; D'Agnese,

2000; Perelman, 1992; Poster, 1990; The Secretarys Commission on Achieving

Necessary Skills, 1991; Tapscott, 1996; Tapscott & Caston, 1993; Thornburg,

1996), the effects of an emerging postmodern culture (Bell, 1973; Best & Kellner,

1997; Kuhn, 1970), and new understandings of learning (Pinker, 1997; Sprenger,

1999).

Recent attempts at restructuring schools to address these emerging needs

have yielded mixed results, and the question of which restructuring strategies

might meet those needs remains unresolved (Knapp & Glenn, 1996; Oblinger &

Rush, 1998). This unresolved question is compounded by a lack of evidence for

the best directions that school restructuring should take (Knapp & Glenn, 1996;

Mehlenger, 1995; Oppenheimer, 1997; Perelman, 1992; Pogrow, 1996; Shouse &

Mussoline, 1999).

Some researchers have suggested that computers might be an important part

of meeting the educational needs of students in the 21st century (Bohlin, 1997;

Jonassen, 2000; Knapp & Glenn, 1996; Schlechty, 1997; Tapscott, 1996;

Thornburg, 1996). A primary reason for this suggestion is the central role thatcomputers play in current and future economies (Gershenfeld, 1999; Kaku, 1997;

OReilly, 2000; Patterson, 1996; Simon, 1999). This central role highlights the

view of some educators that computers are not being used effectively in American

education (Charp, 2002; Mayers & Swafford, 1998; Ulmer, 1995).


18/134

3

Purpose of the Study

The purpose of this study was to explore ways in which educators can more

effectively use computer technology to meet the needs of 21st century students.

This can be partially accomplished by answering the following questions: Which

use of computer technology leads to the greatest student achievement? Is there a

particular instructional technique that, when applied to the use of computers in

education, contributes to greater student achievement? Taken together, these two

questions formed the guiding research question for this study: Is there one

combination of computer use and instructional technique that appears to be most

effective in maximizing student achievement? Along with answering this

question, this study will add to the research base on Jonassens theories.

Design of the Study

In light of the large number of studies that exist that address either the

effects of computers or instructional techniques on student achievement, it seems

possible that the answer to the guiding research question posed above might be

discovered among the results of those studies. Consequently, this study applied

the technique of meta-analysis to a convenient sample of those studies gathered

from the Educational Resources Information Center (ERIC) database to derive a

preliminary answer to this research question.

The studies comprising the sample were placed in sub-groupings based on

computer use and instructional technique. The data from each study were

subjected to statistical analysis to derive an estimator of effect size d, thestandardized mean difference (Cohen, 1977). Homogeneity ?

2(Rosenthal, 1991a)

for each subgroup was tested to measure the impact of influences other than the

independent variables on the effect sizes. The fail-safe N (Orwin, 1983) was

calculated to determine the adequacy of each sample subgroup. These results


19/134


20/134

5

Inclusion criteria (eligibility criteria): Conditions that must be met by a primary

study in order for it to be included in the research synthesis (Cooper &

Hedges, 1994, p. 534).

Moderator variable: Any factor that influences the size of a particular relationship

and is itself not a consequence of the relationship (Cooper & Hedges,

1994, p. 537).

Overall effect size: The effect size derived from statistically combining a sample

population comprised of individual effect sizes from various single studies.

Study population: The actual group of extant studies from which the study sample

was selected.

Study sample: The ensemble of studies that are used in the review and that

provide the effect size data used in the research synthesis (Hedges, 1994a,

p. 30). See between-studies sample size.

Transformation: The application of some arithmetic principle to a set of

observations to convert the scale of measurement to one with more

desirable characteristics (Cooper & Hedges, 1994, p. 542).

Universe: The hypothetical collection of studies that could be conducted in

principle and about which we wish to generalize (Hedges, 1994a, p. 30).

It can be thought of as a collection ofensembles of studies. Hunt (1997)

differentiates between a universe of studies of a phenomenon and the

universe of actual instances of that phenomenon. Since it is unlikely that

every study ever conducted on a given phenomenon would be identicalwith the number of instances of that phenomenon, even a study sample (see

above) comprised of every extant study of a given phenomenon represents

only a sample of the actual instances of the phenomenon (p. 57). In

addition, since the actual extant collection of studies on any given


21/134

6

phenomenon rarely remains static for long, the search for a comprehensive

meta-analysis is an illusory one.


22/134

Chapter 2

REVIEW OF THE LITERATURE

Background

This review of literature falls largely within the bounds of a relatively new

approach to evaluating the effects of information technologies upon human beings,

particularly those human beings within a societal context. Called social

informatics, Kling, Crawford, Rosenbaum, Sawyer, and Weisband (2000) define it

as the interdisciplinary study of the design, uses and consequences of ICTs

[information and communication technologies] that takes into account their

interaction with institutional and cultural contexts. Perhaps the most

comprehensive example of social informatics is the three-volume series by

Castells (1996, 1997, 1998) entitled The Information Age: Economy, Society and

Culture. Castellss work centers around the idea of the bipolar opposition of the

Net and Self (1996, p. 3) as the organizing feature of a networked new century. In

his view, social changes and technological changes are always intimately related

by virtue of their interaction vis visproduction and development. As he puts it:

A new society emerges when and if a structural transformation can be observed

in the relationships of production, in the relationships of power, and in the

relationships of experience (1998, p. 340).

This literature review examines three causative factors that have combinedto help create a new educational imperative for schools, followed by an overview

of recent studies on school restructuring and a similar look at the recent use of

computers in schools. Finally, categories of instructional technique and computer

use are derived for use in the meta-analysis to follow.


23/134

8

Causative Factors for the 21st CenturyEducational Imperative

Moving From the Industrial Age

to the Information Age

The industrial economy of the 19th and early 20th centuries has

transitioned into what has been called the Information Age (Lubar, 1993;

Machlup, 1962). Newt Gingrich, former Speaker of the House of Representatives

said, upon taking office in 1995, that

the most accurate analogy to what is happening to us now is to look at theperiod between 1770 and 1800, when America was changing from a ruralto a manufacturing society. What is happening to us nowthe transitionfrom the industrial era . . . is forcing us to ask very similar questions aboutourselves. (quoted in Tapscott, 1996, p. 2)

A number of writers have suggested that the latter decades of the 20th

century exhibited the characteristics of what Thomas Kuhn (1970) called a

paradigm shift (e.g., Castells, 1996, 1997, 1998; Ronfeldt, 1996; Strackbein,

2001; Toffler, 1991; Toffler & Toffler, 1993). Toffler (1991) argues that this

period of time represents a third wavean information revolution which

succeeds the agricultural and industrial revolutions as the next important wave in

human history. Among the characteristics attributed to this new information age

are the centrality of digital computing technologies (Negroponte, 1995), an

increase in the pace of change (Drexler, 1987; Minsky, 1985), the information

float (Thornburg 1996), information overload (Besser, 1995), and the network as

metaphor for the age (Castells 1996, 1997, 1998).

Negroponte (1995), in comparing the Industrial Revolution and theInformation Revolution, suggests that the former was a period in which society

learned how to process, sort, rearrange, recombine, and transport atoms in

unprecedented fashion (p. 5). The Information Age, on the other hand, processes


24/134

9

bits(data) rather than atoms. Negroponte goes on to point out that the atom is the

fundamental unit of matter and the bit is the fundamental unit of information.

One ramification of the move from atoms to bits is that groups of bits can

generally be moved more quickly and easily than groups of atoms. Thornburg

(1996) observes that this causes not just a change in speed but also a change in the

rate of change (as the power of computing devices that control and move bits

increase according to Moores and Metcalfs laws) (Drexler, 1987; Morovec,

1988). Minsky, in his influential bookSociety of Mind(1985), calls it the law of

accelerating returnsa phenomenon marked by technological change occurring

as an exponential extension of Moores law. The resulting acceleration in the pace

of change creates two phenomena that are unique to the Information Age: the

volume of information doubles every 18-24 months; while the shrinkage or

collapse of the information float(the time lag between a discovery and its

application) decreases (Thornburg, 1996).

The digital computer is the prime mover of these bits of information, but its

ability to move them depends on being physically connected to other computers

that is, networked. Dewar (1998) suggests that no invention since the printing

press has had as profound an effect on world society as have networked

computers: There has only been one comparable event i n the recorded history of

communicationsthe printing press. It was the first true one-to-many

communications medium, and no change since has been as dramatic as networked

computers (p. 3).The importance of the networked computer is echoed by a number of

theorists who suggest that the best metaphor for the information age is the network

(Castells, 1996, 1997, 1998; Ronfeldt, 1996; Strackbein, 2001). Ronfeldt (1996)


25/134

10

sees the network as the next stage in the progression of societal forms that started

with tribes and moved through hierarchies to markets.

Postmodern Society

The term Postmodernism is applied, generally, to the corpus of ideas

surrounding a new philosophy which started as a movement within the art

community in the early half of the 20th century. It may have its genesis in the

rapidity and fecundity of technological innovation. Jean Francois Lyotard (1984),

one of the leading theorists of the postmodern condition, opens his seminal

book, The Postmodern Condition , by tying the causes of postmodernism to

modern technology:

Our working hypothesis is that the status of knowledge is altered associeties enter what is known as the postindustrial age and cultures enterwhat is known as the postmodern age. . . . the miniaturization andcommercialization of machines is already changing the way in whichlearning is acquired, classified, made available, and exploited. . . . Thenature of knowledge cannot survive unchanged within this context ofgeneral transformation. It can fit into the new channels, and becomeoperational, only if learning is translated into quantities of information.

(p. 1)Hlynka (1995) agrees with Lyotard that technology is an integral part of the post-

modern dilemma (p. 118).

Johnson-Eilola (1998) believes that the 21st century transition from modern

to postmodern has created a dichotomous culture formed from the last of the

modern generation and the first of the postmodern generation:

Those of us raised in the modernist first world tend to deride the second,

postmodernist world as superficial, artificial, and dehumanizing . . . Wehave lived through the shift, and are unfamiliar and uneasy (at best) withwhat we experience. (pp. 185-186)

The modern world Johnson-Eilola speaks of sees each generation as a link

in a chain from past to present. The modern world orients itself by where it has

been and sees the present as a preparation for passing the past on to the future.


26/134

11

The post-modern world, as Johnson-Eilola sees it, lives on the surface,

constantly stimulated from multiple directions simultaneously, and orients itself to

itself. It is characterized by the ability to process multiple streams of

information simultaneously and the propensity to experiment in free-form, ill-

defined problem domains (p. 191).

For the post-modernist, there are no universal truths, no depth, and no

differentiation between appearance and substance (Hlynka, 1995). Learning, then,

is done on-the-fly, as needed, and then discarded, because without a temporal

anchor (supplied by the past) there is no reason to retain it for the future.

The Knowledge Economy

Workers in an information age economy need skills that differ from those

required by an industrial age economy (Benjamin, 1998; Castells, 1996). This

emerging economy revolves around the manipulation of information rather than of

objects, but even that structure itself is beginning to change. According to Brown

and Duguid (2000) and Tapscott (1996), the information economy is in the process

of becoming the knowledge economy. Drucker (1969), Demming (2000), and

Senge (1990) have all advocated that the basic economic resource of todays

economy is not labor or capital, but knowledge.

The knowledge economy worker. The workers in a knowledge economy

will need to be better educated than either their industrial age or their

information age predecessors (Nax, 1996). They will need to be knowledgeworkers. A knowledge worker is a person who puts to use facts, ideas, theories,

beliefs, and supposed forms of knowledge to produce a product" (Schlechty, 1997,

p. 37). In other words, the worker in a knowledge economy uses information

rather than possesses it. Unlike an industrial age worker whose primary task was


27/134

12

to contribute to the production ofsomething (a physical object), the knowledge

worker produces an idea or the application thereof (Tapscott, 1996). This is not

unlike what academicians and researchers do.

Knowledge workers are the most vital resource in a 21st century company

(Microsoft, 1999) but their productivity depends on how both they and the

knowledge they use and create are managed (Gates, 1999). Computer technology

is both the imperative for, and the instrument of, a successful knowledge

economy. The ability to capture information, knowledge, and data has far

outstripped peoples ability to absorb and analyze this information in a focused

way (Gates, 1999, p. 2). This means that computers must take on much of the

task of dealing with the overabundance. Keith Bogg, quoted in Gates (1999), says

that people should use their intelligence to deal only with the exceptions [to

repetitive, non-thinking work], letting computers make decisions about everything

else (p. 223; see also Davis & Meyer, 1998). Tapscott (1996) suggests that this is

as true for the educational world as it is for the business world.

The learning organization. The foregoing suggests that 21st century

students will need more than the traditional three Rs to be viable members of a

knowledge economy. As future knowledge workers they will need to know how

to learn whatever it is that is needed to apply analyzed information in useful and

creative ways. Senge (1990) conceptualizes the 21st century company as a

learning organization. According to Senge, learning is both an individual and a

team effort and means, in the context of the learning organization, expanding the

ability to produce results we truly want in life (p. 142). Integral to the success of

the learning organization is the concept of creative tension (p. 154). It is what

stimulates the learning and drives the productivity.


28/134

13

If knowledge management and learning organizations are to be hallmarks

of business in the economic world of the next generation, it seems likely that those

businesses will expect the schools to follow suit.

Apart from the way societal changes wrought by information technology

and the differing demands of a knowledge economy give rise to changes in the

way 21st century students are educated, new understandings about the way people

learn suggest that some past educational practices may not be as effective as

previously thought.

New Understandings of Learning

Overview. The 21st century brings with it new understandings of

knowledge and learning, deriving primarily from cognitive science and the study

of the brain. The idea of brain-based learning seems redundant, as educators have

known for quite a while that the brain was involved in learning, but scientific

discoveriesmade possible by new technological developmentshave generated

new thoughts regarding how that learning takes place.

Cognitive science. In general, cognitive science is defined as the

interdisciplinary study of the mind and intelligence which attempts to further the

understanding of intelligent activities and the nature of thought (Audi, 1995).

Theories within cognitive science can be classified into three broad categories

(Lehrer, 1990): Connectionism, Symbolicism, andDynamism (Dynamical

Systems). The first, Connectionism, uses a systems or network model in its

approach to explaining cognition. The second, Symbolicism, uses a semantic or

symbolic language processing model in its attempt to explain thinking processes.

The last, Dynamical Systems, takes a mathematical view of cognitive behavior.


29/134

14

These broad categories all have at least two things in common: the recognition

that cognition is a process, and an approach to the problem from the point of view

of one particular discipline, i.e., computational systems, language processing, or

mathematics.

Connectionism is a computational approach to understanding the function

of the brain. It sees cognitive processes as consisting of interconnections which

take place between nerve cells in a vast network. In this sense, it parallels the

discoveries made by recent research into the physical functioning of the brain. It

is based on the hypothesis that the mind is a type of computer whose functions can

be reduced to algorithms (Bechtel, 1987; Bechtel & Abrahamsen, 1990; Cotrell &

Small, 1983; Rumelhart, McClelland, & The PDP Research Group, 1986). Brain-

based learning (Jensen, 1998; Pinker, 1997) is the instructional method most

closely associated with connectionism.

Symbolicism (Classicism) is a semantic modeling approach to cognition.

Central to this model is the belief that symbolic language processing best explains

the functions of the mind. It grew out of research in artificial intelligence (Minsky

& Papert, 1969) and Chomskys (1957) ground-breaking work in syntactical

structures for linguistics. Representative of this approach is the Physical Systems

Symbol hypothesis of Newell and Simon (1976).

The theory ofDynamical systems , the most recently developed of these

categories, attempts to explain the behavior of the brain through treating it as a

complex system and employs differential and difference equations to explain it.This approach had been used for analysis ofany complex system prior to its

application to cognitive science. Van Gelder and Port (1995) have developed the

view that natural cognitive systems are a kind of dynamic system and thus are best

understood from the perspective of dynamics. In so doing, Van Gelder and Port


30/134

15

reject the validity of both the connectionist and symbolic schools of thought

(which, in turn, reject the claims of dynamicism as well as the claims of the other).

Functionalism is the view that the essential property of a component is its

role in relating inputs to outputs and to other components. This is integral to any

systems or network view. Ned Block (1980) recognizes three types of

functionalism:Decompositional functionalism, Computation-representation

functionalism, and Meta-physical functionalism.

Decompositional functionalism, which is primarily a methodology

(Eliasmith, 1996), explains any system in terms of the functionality of its

components parts (i.e., the entire system is the sum of its parts, the parts'

functionality, and the relationship of the parts to every other component).

Computation-representation functionalism (Block, 1980) adheres to the

mind-as-computer analogy. The mind is a computer and as such, mental processes

are decomposable to the point where they are thought of as simply instantiations

of a digital computer (e.g., the Turing machine). Computation-representation

functionalism is a special case of decompositional functionalism and is more a

theory of mind than a methodology.

Meta-physical functionalism (Block, 1980) is a theory of mind which sees

cognition as a mental state or a functional state. The actual physical

implementation of the processes are irrelevant to what makes a mind; only the

functional relations matter. In other words, understanding how the brain itself

works is less important than understanding how the mindworksat least foreducators. However, recent discoveries regarding the way the brain physically

functions suggest that there are some things that educators can do to facilitate the

thinking that the mind does.


31/134

16

Brain research. In the late 19th century a connection between thinking and

neurons was posited by Spencer (1872), Meynert (1884), James (1890), and Freud

(1895). Later, researchers such as Lashley (1929), Rashovsky (1938), and others

expanded on this earlier work. Modern brain research, in turn, builds upon that

work.

Brain research is concerned with thephysical processes that take place

when the brain thinks or learns. Brain-based learning, on the other hand, is

concerned with the instructional strategies that facilitate the way the mind learns

by supporting the physical processes used by the brain (Sprenger, 1999).

Physically, the brain is what might best be described as a neural-network (Pinker,

1997). What happens chemically and electrically in the brain is only now being

understoodprimarily as the result of newer technologies that allow scientists to

observe the process. What is known suggests that the brain learns by creating

electro-chemical connections that represent, in some way not currently

understood, meaning and memory. These connections can be invoked, again

through a process which is only beginning to be understood, so as to reproduce in

the mind the meanings and memories stored in those connections (Jensen, 1998)

According to Robin and Malkas (2000), the learning theory associated with

brain research is based on the structure and function of the brain. Integral to this is

the idea that as long as the brain is not prohibited from fulfilling its normal

processes, learning will occur. The Core Principles of brain-based learning are the

following (Robin & Malkas, 2000):1. The brain is a parallel processor, meaning it can perform several

activities at once, like tasting and smelling.

2. Learning engages the whole physiology.

3. The search for meaning is innate.


32/134

17

4. The search for meaning comes through patterning.

5. Emotions are critical to patterning.

6. The brain processes wholes and parts simultaneously.

7. Learning involves both focused attention and peripheral perception.

8. Learning involves both conscious and unconscious processes.

9. We have two type of memory: spatial and rote.

10.We understand best when facts are embedded in natural spatial

memory.

11.Learning is enhanced by challenge and inhibited by threat.

12.Each brain is unique.

Thus, people learn best when solving realistic problems (contextual learning), and

the big picture cant be separated from the details (holistic learning). Because

every brain is different, one implication is that educators should allow learners to

customize their own learning environments. This suggests that teachers may want

to design learning around student interests and make learning contextual.

Educators should let students learn in teams and use peripheral learning. Learning

experiences should be structured around real problems, encouraging students to

also learn in settings outside the classroom and the school building (Blumenfeld,

et al.,1991; Chard, 1998).

There are the three instructional techniques primarily associated with brain-

based learning: The first is orchestrated immersion in which learning

environments are created that fully immerse students in an educational experience.Relaxed alertness, a second technique, tries to eliminate fear in learners while

maintaining a highly challenging environment. The last, active processing, allows

the learner to consolidate and internalize information by actively processing it

(Robin & Malkas, 2000).


33/134

18

Characteristics of 21st Century Students

Part of childrens attraction toand connection withcomputers may stem

from the fact that computers interface with them via a screen (Johnson, 1997).

Johnson calls them screen-agers (p. 7). Today's children are members of what

might be termed the educational television generation: their first formal learning

experiences are via TV. In many ways, it is more natural for them to learn from a

screen than from an adult. Parents have often utilized TV for direct teaching. As

a result, todays children might be more comfortable with TV instructors than they

are with parental instruction or classroom teachers.

Rushkoff (1998) believes that todays children are people of the future.

They are, as he puts it, the latest model of human being. As such, they seem to

be better equipped for life in the 21st century than their parents or even their

teachers. Part of this difference lies in the fact that they seem to be intrinsically

forward-focused. That is, they appear to have fewer ties to the past than to the

future. This may be one reason why the children of today seem so ignorant

concerning history: they perceive it as irrelevant. It may also be a mistake to

assume that the current generation is a continuation of the previous one: Looking

at the world of children, Rushkoff suggests, is not looking backwards at our own

pastsits looking ahead. They are our evolutionary future (p. 2).

Smith and Curtin (1998) believe that postmodern children differ from

children of the past. They based this upon the fact that new forms of

communication (such as that offered by computers) affect social relationships and,

thus, psychological make-up. The shift in social relationships is, as they see it,

from face-to-face to symbolic communities (p. 214).

Tapscott (1998), in his recent book, Growing Up Digital: The Rise of the

Net Generation, observes that for the first time in history youth are an authority


34/134

19

on an innovation central to societys development (p. ix). He calls todays

postmodern children the N-Genthe Net Generation. They are different than

the generation McLuhan (1964) wrote about which grew up as part of the post-war

baby boom. Tapscott defines the Net Generation as children who, in 1999, will

be between the ages of two and twenty-two (p. 3).

If McLuhans children were the TV generation, shaped by the pervasive

presence and influence of television, the N-Gen is equally likely to be shaped by

the interactive nature of the Internet. A major difference between the two, and one

that educational researchers seem to have over-looked, is that a computer screen is

connected to an interactive programit is two-way communication. The

television, on the other hand is one-way; it broadcasts to the viewer. Viewers'

interactions with television are limited to changing channels or turning it off.

For Tapscott, this difference is central: The shift from broadcast to

interactive is the cornerstone of the N-Generation. They want to be usersnot

just viewers or listeners (p. 3). From this it follows that teaching methods

predicated on a broadcast naturewhether by television or lecturemay not

connect with children of the post-modern N-Generation.

The interactivewith the emphasis on activenature of the post-modern

child, who is also a 21st century citizen facing a career in a globally-networked

knowledge economy is something substantially different from that of previous

generations. There is a kind of generation gap between the Net generation and

all other generations currently alive. The difference is, unlike the Sixties, the gapdoesn't appear to be focused around cultural mores or societal values, but around

technology and infrastructure. Todays parents deal with chat-rooms and web

surfing rather than rock music and war as ignition points in the traditional battle of

growing pains. The nature of the Internet as a legitimate tool of business and


35/134

20

government has blunted its potential as a device of teen protest. Hackers as they

are sometimes incorrectly called, can still cause mischief and trouble, but it is hard

for parents to deny their child access to something that has become an everyday

tool for so much of the working world. This may explain why the N-Gens

fundamental difference in world outlook and cognitive constructs are so often

overlookedtheir manifestations are obscured by the more overt expressions of

identity and protest.

School Restructuring

Recent attempts to meet the needs of 21st century students have resulted in

a number of restructuring efforts that have met with limited success, possibly

because they are based on Industrial Age principles. The effects of the transition

from manipulating data to manipulating bits, of a networked world, and so on,

suggest a new task for educationwhich, in turn, implies new methods and new

structures.

School restructuring refers to the practice of using non-traditional structural

practices at the local or district level. In general, traditional school structures are

those that are identified by Lee and Smith (1994)as being fundamentally

bureaucratic in nature while those considered "restructured" exhibited more

"communal" tendencies. Using a list of 12 practices that they identified as

"significant departures from conventional practices," Lee and Smith concluded

that there was "solid" evidence that students in schools using non-traditional

structures learned more than those in traditionally structured schools.

Such a categorical statement is hard to accept without broad-based support.

A follow-up study based on data from the National Education Longitudinal Study

in 1988 and 1990 made by Lee, Smith, and Croninger (1995) not only confirmed


36/134

21

their earlier findings but included the further revelation that the positive effects of

restructuring appear to be cumulative. Moreover, Lee, Smith, and Croninger

identified three features common to more effective communal (or, as they termed

them, "organic") schools: common academic curriculum, academic press (the

expectation of high standards and maximum effort), and authentic instruction. It is

important to note that both studies identified the significant role which the social

component of restructuring efforts played in the positive findings.

This social significance is the focus of a study by Andrew Coulson (1994),

who argues that "the success of any human organization depends upon the

unification of its participants' goals"which is fundamentally social in nature (p.

31). Psychologically, this may be a manifestation of the "locus of control" effect

whereby a person does not seek a goal that he or she believes does not fall within

his or her sphere of control (Coulson, 1994). To support his contention that

success in educational achievement derives from social factors rather than from

organizational factors, Coulson surveyed a variety of studies on the effects of

desegregation upon student achievement and found that there was no significant

positive effect on student academic achievement to be gained fromforced

desegregation, but that voluntary desegregation resulted in a few positive

significant differences. Coulson believes that it is the shared goals of the

participants who voluntarily chose to desegregate rather than the act of being

desegregated itself that resulted in positive academic achievement. Shouse and

Mussoline (1999) support Coulson when he notes that ". . . restructuring offers tomake school systems more collegial and participatoryindeed more democratic

(p. 1).

In their meta-analysis of studies on the effects of non-graded schools on

student performance, Gutierrez and Slavin (1992) found that the preponderance of


37/134

22

evidence indicated that nongraded schools resulted in higher achievement, but that

the conclusion was only valid for simple forms of non-grading and not for the

more complex forms which exist. Further, they concluded that the effects of non-

grading depend on the form that the nongrading strategy takes. Their analysis

suggests that much of the benefits of nongrading accrue from two factors: flexible

grouping and flexible timeframes. In other words, the effectiveness of the non-

graded program stems from the increased amount of time for "direct instruction at

the students' precise instructional level (p. 360).

Elmore (1990) notes the emergence of a general agreement that

restructuring is about at least three types of changes: teaching and learning in

schools, the conditions of teachers work in schools, and the governance and

incentive structures in schools. The first, teaching and learning in schools, is what

he refers to as reforming the core technology of schools. He wonders what form

schools would take if they were designed around the best available knowledge

about teaching and learning. Hunter Moorman and John Egermeier (1992) add to

this idea:

Restructuring suggests the need to rethink the mission of education in lightof changing conditions and imperatives of the coming century, to exchangetraditional forms of schooling for pedagogical and organizational processesthat fit new missions, to shift from one set of guiding values and assump-tions to another, and, perhaps, to embark on an ongoing process of trans-formation instead of seeking static solutions to fixed problems. (p. 18)

There is evidence that some restructuring efforts can be detrimental to

student performance. In a study completed at Pennsylvania State University,

Shouse and Mussoline (1999) said, ". . . our data show that it [restructuring] has

been disruptive to student performance in poor school districts and especially the

very poor. Even in affluent schools, it has had no empirical benefit (p.1).

Shouse and Mussoline opined that the primary cause for these disruptions lay in


38/134

23

two areas: (a) the inherent complexity of most restructuring plans and (b) the

demand on resources that such plans make on the institution being reformed. The

more complex the plan, the more disruptive it became. In essence, the effort

applied to making complex restructuring work offset any educational gain that

might have accrued due to those changes. Secondly, restructuring is expensive.

Many educators and members of the public believe spending money on

educational reform of dubious value is a poor use of scarce monetary resources

particularly when many schools are in such a state of disrepair that the GAO in

1995 reported that one-third of the nation's schools were either unsafe or

unsuitable for children (cited in Mehlinger, 1995, p. 51).

Other researchers find that certain types of restructuring make no

significant difference at all in student academic success. For instance, Childs and

Shakeshaft (1986) and Alspaugh (1993), cited in Coulson (1994, pp. 14-15) find

that there is no correlation between educational spending and student achievement.

Frequently, educators and politicians look to increase funding as a remedy for

education's ills (whatever those may be). The fact that simply spending money

doesn't necessarily result in any measurable gains was addressed by Coulson who

hypothesized that this was because money did not guarantee any alteration in

instructional practices and often ended up being spent for noninstructional

purposes. The similarity between Coulson's findings and those of Shouse and

Mussoline is obvious: Many restructuring efforts seemed to get sidetracked in the

implementation stage, thus adversely affecting the possibility of a positive result.There does not seem to be a consensus about what works in regards to

restructuring. While the evidence presented so far seems to indicate that

restructuring is a risky, but conditionally effective strategy for increasing student

achievement, it is not conclusive for any one particular restructuring method.


39/134

24

Newmann and Wehlage (1995) suggest that the reason for this is that no single

reform is sufficient to ensure ongoing success. Even in combination, restructuring

methods do not always result in the desired increase in student performance.

Newmann and Wehlage conclude from their study that:

The quality of education for children depends ultimately not on specifictechniques, practices or structures, but on more basic human and socialresources in a school, especially on the commitment and competence (thewill and skill) of educators, and on students' efforts to learn. (p. 2)

Potential Impacts

Schlechty (1997) suggests that the reason reform has been tried so often is

because

what the schools were designed to do is no longer serving the needs ofAmerican society . The schools were designed to ensure that all citizens willbe basically literate (able to decode words), and that most will be

functionally literate (able to read well), and that a relatively small number(20 percent or less) will be able to meet reasonably high academicstandards. This goal has been achieved. (p. 11)

In terms of a knowledge economy, it might be said that while computers

may create the need for knowledge management and anchor business ability to

put knowledge workers to effective use, it is learning that makes intellectual

property, capital, and assets useable (Brown & Duguid, 2000) and learning is the

business of schoolsor should be.

Learning in schools, like profit in business, is what happens when schools

do their business right. However, according to Schlechty (1997), learning is not

the business of schools:

The business of schools is to design, create, and invent high-quality,intellectually demanding work for students: schoolwork that calls onstudents to think, to reason, and to use their minds well and that calls onthem to engage ideas, facts, and understandings whose perpetuation isessential to the survival of the common culture and relevant to theparticular culture, group, and milieu from which students come and inwhich they are likely to function. (pp. 49-50)


40/134

25

In other words, learning is the business of learners.

The business of schools, therefore, seems to be much the same as the

business of business; i.e., knowledge management. In order for students to engage

in the kind of activity Schlechty proposes, they need the same type of support that

knowledge workers require. They are both doing what Microsoft CEO Bill Gates

calls thinking work. Thinking work is what people do when they find, select,

organize, and present information in a new way (Gates, 1999, chapter 13).

Integral to thinking work is the ability to innovate and adapt in the face of

change (Microsoft, 1999). The question is whether knowledge management is

what todays schools are doing or what they were designed to do.

Schlechty (1997) believes that todays schools are better at doing what they

were designed for than they have ever been, but what they were designed for is not

what is needed for the 21st century. The system emulated the prevailing 19th

century thought about industrial management by being designed with an eye

toward centralization of authority and funding (Lane & Epps, 1992). This 19th

century structure serve d its purpose better than most give it credit for, but that

does not diminish the fact that it is poorly suited for the 21st century task of

knowledge management. As Schlechty (1997) points out,

Americas schools are now being asked to do things they have never done[before] in an environment that is more hostile to supporting qualityeducation than has ever before existed. . . . What educators must do,therefore, is to invent a system of education the like of which has neverbeen seen anywhere in the world: a system of education that provides anelite education for nearly every child. (pp. 14-15)


41/134

26

The Role of Computer Technology

Positive Effects of ComputerTechnology

Perhaps the most comprehensive study concerning the use ofand

potential oftechnology in education was completed in 1997 by the President's

Committee of Advisors on Science and Technology. In its report on the use of

technology to strengthen K-12 education in the United States, the committee

found, in general, that the use of traditional computer-based learning systems

resulted in superior performance by the students using them when compared to

students who did not use them. Further, these same students were found to learn

significantly faster and to have a more positive attitude toward their classes and

toward computers.

Such a blanket finding, particularly when based upon such a broad-based

study (a meta-analysis of four meta-analyses encompassing a total of 172 studies),

would seem to suggest that the use of computer technology, at least, is practically

mandatory in the interests of effective and efficient education. However, some

researchersincluding some on the committee itselfquestioned the validity of

such a conclusion in light of what they term "serious problems" with both the

meta-analyses and the studies upon which they were based (President's Committee

of Advisors on Science and Technology, Panel on Educational Technology, 1997,

p. 42). These problems focused on questions of methodology and interpretation of

the results, typical problems faced in any area of educational research. The

committee felt that these limitations merely spelled-out the need for more research

rather than invalidating the results.

Knapp and Glenn (1996) in a meta-analysis of research that represented an

aggregate of over 120 studies on the effectiveness of computers in producing


42/134

27

positive educational outcomes, concluded that children favor computers over

television because of the interactive nature of computers and that computer-

assisted instruction (CAI) leads to higher academic gains. They noted that CAI

primarily addressed lower-cognitive material and that research on the effect of

computers on higher-order thinking skills (HOTS) was still "emerging. The one

caveat Knapp and Glenn placed on their sweeping conclusions is that "computer

applications alone do not achieve the results teachers and learners want."

Effectiveness resides in CAI being a part of a total program (i.e., instructional

milieu).

The California Education Technology Task Force (1996) reported that a

1995 survey of more than 100 studies showed that technology-based instruction

"significantly improved student performance" in the core academic disciplines.

The same study reported that the U.S. military found that computer-based

instruction required 30% less time to achieve its educational goals than did

traditional methods (see the executive summary).

In a paper presented to the Conference on Teacher Education and the Use

of Technology Based Learning Systems in 1996, J. D. Fletcher surveyed the bulk

of research on the effectiveness of technology as a teaching tool and derived from

that study ten commonalities regarding instructional technology use: (a)

Technology can teachin other words technology is more effective than no

instruction at all; (b) technology increases instructional effectiveness; (c)

technology reduces the time required to reach instructional objectives; (d)technology promotes equity in achievement; (e) technology appears to be equally

effective for knowledge and performance outcomes; (f) technology can be used to

teach "soft skills" (social or interpersonal skills); (g) Interactivity is important (i.e.

increased interactivity yields increased student achievement); (h) simulation


43/134

28

requires guidance; (i) students enjoy using technology; and (j) technology lowers

instructional costs and appears to be cost-effective. Fletcher does note that

"hardware alone does not define an instructional approachwhat is done with the

hardware is what counts (p. 2). He also points out that a major problem with

assessing innovative technologies is their very nature: because they are innovative,

such technologies often have nothing with which they can be compared.

Negative Effects of Computers onLearning

Hawley and Duffy (1998) found that the benefits of computer simulations

tended to be diluted when teachers either failed to coach students in problem-

solving strategies or played too big a role in the actual discovery process. This

coincides with one of the findings of Fletcher (1996) listed previously. The

delicate balance required for optimal effectiveness seemed a difficult one to

maintain by the majority of participating teachers.

Hawley and Duffy's study illustrates a common problem with using modern

technology in the classroom: new technologies are not always a good fit with

traditional teaching methods, nor with traditional learning theories. In fact, new

technologies used in traditional fashion have been shown to have a detrimental

effect on academic achievement. Among the findings by Wenglinsky (1998) was

the disturbing fact that the use of computers to teach lower-order thinking skills

was negatively related to academic achievement and the social environment of the

schoolat least for eighth grade students.One of the more high profile books to attack the use of computers in the

classroom, Failure to Connect(Healy, 1998), finds fault with the educational use

of computer technology, not the technology per se. Healy argues that (a)

computers divert scarce resources from other, more sound, educational disciplines;


44/134

29

(b) computers are used in age-inappropriate waysespecially with younger

children; (c) so-called edutainment software teaches children more about

impulsive pointing and clicking than about thinking; and (d) some software may

interfere with the childs natural impulse to learn.

Much of the fault for these problems lies, according to Healy, not with the

computers themselves, but with the fact that schools do not provide sufficient

budgets for technical support or teacher training. These arguments parallel those

which characterize school restructuring and are the type of deployment problem

that social informatics tries to address (Kling et al., 2000). The similarity in the

arguments against the use of computers and those against school restructuring

suggest that the two may address the same core structures in modern education.

Further, Healy does not contend that computers are bad for children, but that they

are bad for children when used improperly. This is the converse of saying that

computers are good for children when used appropriately. Again, Jonassens point

that the way in which computers are used is of the greatest consequence is

supported.

Like Healy, Oppenheimer (1997) believes that computers divert resources

that might be better used for more verifiable change. Oppenheimer bases his

belief not so much on what research shows, but on what it doesn'tshow and on the

history of repeated failure of technological innovations to produce lasting change

(see pp. 45-46). It is in the closing quote that Oppenheimer reveals the core

argument behind his resistance to computers:

The purpose of the schools [is] to, as one teacher argues, Teach carpentry,not hammer, . . . We need to teach the whys and ways of the world. Toolscome and tools go. Teaching our children tools limits their knowledge tothese tools and hence limits their futures. (p. 62)


45/134

30

Here again, as Jonassen has suggested, the problem is not with the

computer, but how it is used. David Gelernter, professor of computer science at

Yale, in a recent interview forMITs Technology Review, characterized the

computer as follows:

The PC isnt a Swiss Army knife. Its like a hammer. People dont want amillion tools. They want a single hammer that can do a million things,because its a tremendously flexible, elegant and powerful tool (quoted inTristram, 2001, p. 59).

The Role of the Computer inSchool Restructuring

Even granting that each of the major meta-analyses detailed above may

have looked at some of the same individual studies, the scope of the total is

staggering. The shear number of individual studies on the effectiveness of

computer-based education says volumes about the preoccupation of both the

academic world and the general public with this new technology. That in itself

might be enough to recommend the use of computers in the classroom but, when

combined with the generally positive results of those studies as regards the

effectiveness of computer technology upon student achievement, suggests that

educational institutions should do whatever is required to deploy that technology

as quickly as possibleeven if that means radical departures from traditional

organizational structures.

In fact, it is the popularity of the computerparticularly among businesses

and politiciansthat argues most soundly for adopting the computer as an

instrument of restructuring. Because it has been shown to be an effective tool for

learning and because it coincides well with the best guess about what students wi ll

spend their careers using, the willingness of the power structures in education


46/134

31

which might otherwise resist other forms of restructuringto make computers

available allows educators to better meet the needs of 21st century students.

Computer Use Categories

Theoretical Basis: Jonassen

Jonassen (1996, 2000) categorizes computer use in education relationally,

that is, according to the interaction between humans and computers. His analysis

of existing computer use produced three such interactions: learning about

computers (Computer Literacy), learningfrom computers (Computer Assisted

Instruction or CAI), and learning with computers, what he calls Mindtools.

The keys to understanding Jonassens differentiations is in the

instrumentality accorded the computer and linked to the role of the learner. This

notion of instrumentality focuses on the relationship between the user and the

computer and the roles each plays in the learning process. The teacher, in this

case, plays an external role, usually in terms of defining the instrumentality. That

is, it is the teacher who, in his or her role as person in charge of the learning

environment, determines how the computer is to be used, its instrumentality.

Computer literacy (learning about computers). When students learn about

the computer, how to use it, what the various constituent parts are called, and so

on, they are not using the computer as a tool. The computer, in this case, is the

objectof the learningit is what the student is learning. The relationship between

the learner and the computer is completely one-sided: only the student is active

and only to a certain extent. The teacher plays a more active role than does the

student and the body of knowledge to be learned is set and static. While knowing

how to use the computer is essential to using it in any other way there is little that


47/134

32

is required of the student in the way of higher order thinking skills (see Jonassen,

2000).

Computer assisted instruction (CAI) (learning from computers). In

computer assisted instruction (CAI)the computer takes on a significant portion of

the teachers role and the student responds to the computers lead. Both the

computer and the student are now involved in the learning process, with the

teacher primarily demanding accountability. The computer is generally in

charge and the body of knowledge that can be learned is, as before, pre-

determined and static. The learner is active but not in charge of the learning.

Mindtools (learning with computers). It is only in the last of the three

interactions between students and computers that the role of the learner takes

precedence. In fact, when used as a Mindtool, the role of the computer is reversed

from that in CAI: It is the learner who is in charge and the computer that responds

to the learner. The body of knowledge that can be learned is essentially unlimited,

because the student uses the computer to discover or construct it. The teachers

role becomes that of a designer of the learning environment, a problem poser, and

a holder of accountability. Teaching takes on the role of the proverbial guide on

the side so emphasized in constructivism. Jonassen (2000) elaborates on the

basic concept of Mindtools:

Mindtools are computer-based tools and learning environments that havebeen adapted or developed to function as intellectual partners with the

learner in order to engage and facilitate critical thinking and higher orderlearning. (p. 9) . . . [A] Mindtool is a concept . . . [which] . . . represent[s] aconstructivist approach for using computers or any other technology,environment, or activity to engage learners in representing, manipulating,and reflecting on what they know, not reproducing what someone tellsthem. (p. 10)


48/134

33

Categories of Computer Use

Using Jonassens three computer interactions as a basic model, and adding

the defining elements of role of the learner, role of the computer, and locus of

control (who is in charge), categories for computer use in the meta-analysis

can be created. By creating categories based upon the above characteristics,

instructional situations involving computers can be grouped with others of similar

functionality, regardless of what label might have been placed on the use of the

computer in the sample studies. These categories of computer use created appear

in Table 1. These categories were later adapted for use in the meta-analysis and

will be discussed in Chapter 3.

Instructional Techniques Categories

Unlike categories of computer use, where the categories were preselected

and relatively limited in scope, the variety of instructional techniques that might

appear in the sample studies is potentially so large that grouping them ahead of

time would be counterproductive. Consequently, creating categories for grouping

according to instructional technique was reserved until after the study sample was

finalized and the actual techniques were inventoried. The categories for

instructional technique, as finally used in the meta-analysis, will be introduced in

Chapter 3.

Restatement of the Research Question

The educational needs of 21st century students are not being met and

computer technology seems to hold some potential for meeting those needs.The

purpose of this study was to explore how educators can more effectively use

computer technology to meet the needs of present-day students. This can be


49/134

34

Table 1

Categories of Instructional Use of Computer Technology

Computer LiteracyLearning to use the computer

hardware use, software use, networking, programming, etc.

Computer Assisted Instruction (CAI)Defined, static content

a

Roleof the Computer

Roleof the Learner

Roleof the Computer

Locusof Control

Delivery Mechanism Passive Passive Third Party

Tutoring Mechanism I Active Active Program control

Tutoring Mechanism II Active Active Learner control

Assessment Mechanism Testing tool: A special category of tutoring mechanism

Computer as ToolSomething is produced

Roleof the Computer Roleof the Learner Roleof the Computer Locusof Control

Communications tool Active Passive

Productivity tool Active Active Learner control

Mindtool Active Active Learner control

Living Tool Active Active shared control

Note: These categories of computer use will be adapted for use on coding the studiesincluded in the meta-analysis (Chapter 4).

aSee Loveless, A., DeVoogd, G. L., & Bohlin, R. B. (2001). Something old,

something new . . . Is pedagogy affected by ICT? In A. Loveless and V. Ellis, (Eds.),ICT, Pedagogy and the curriculum: Subject to Change (pp. 71-77). New York:Routeledge/Falmer.


50/134

35

accomplished by answering the following question: Is there one combination of

computer use and instructional technique that leads to greater student achievement

than any other such combination? Implied within this question are two others:

Which use of computer technology leads to the greatest student achievement? Is

there a particular instructional technique that, when applied to the use of

computers in education, contributes to greater student achievement?

In light of the large number of studies that exist which address either the

effects of computers or instructional techniques on student achievement, it seems

possible that the answers to the question posed above might be discovered among

the results of those studies. Consequently, this study will employ the technique of

meta-analysis to a sample of those studies in an attempt to derive a preliminary

answer to that question.


51/134

Chapter 3

METHODOLOGY

Introduction

The purpose of this thesis is to explore how educators can most

effectively use computer technology to meet the educational needs of 21st century

students. The preceding literature review suggests that todays students have

different educational requirements than students in the past and that those

differences call for a change in the instructional milieu by which they are

educated. It was suggested that the instructional milieu required of the new

millennium be centered around the use of computers and brain-based educational

strategies. Though it has been established that computers seem to facilitate

learning under a variety of circumstances, these studies are somewhat isolated and

undifferentiated.

Previous research syntheses have tended to focus on the effect of

computers in relation to particular subject matter areas or the use of particular

computer software types or functions. This thesis seeks a somewhat different set

of data: the combined effect of the use of computers and particular teaching

strategies or techniques on learning or student achievement.This study seeks to

ascertain the effective use of computers as instructional tools, not merely the effect

of the tools themselves.

The assumption, based upon the Review of the Literature, is that

computers, in general, have a positive effect on student learning, but that the effect

is determined more by how the computer is used rather than simply that it was

used. If this is, in fact true, then the resultant effect on measurement of student


52/134

37

achievement derived from the instructional use of computers will vary according

to changes in the way they are used. This variance should be accompanied by a

corresponding change in estimated effect size. By comparing the estimated effect

size of various combinations of computer use and instructional technique, some

idea of which such combinations are more effective on student learning can be

estimated. Thus, this study used a convenient study sample (i.e., a convenience

sample), derived from a finite study population, to explore the foregoing notion

using the statistical technique of meta-analysis.

A meta-analysis, according to Glass (1976, 1978b), compares the results

of individual studies by translating those results into a standardized metric he

called effect size. Briefly, an effect size is a proportion that compares the

differences between the mean of two sample distributions as measured in standard

deviations. The two distributions can be either a control group and a treatment

group, also called an experimental group, or the pre-treatment and post-treatment

performances of the same group. By comparing the difference or change between

the mean of the two groups in terms of standard deviations, the effect of the

treatment on the experimental or post-treatment group can be calculated. The

advantage to this translation is that the resulting effect sizes can be used to

compare studies that use different dependent measures. Effect size is calculated,

according to Glasss (1976) formula, as follows:

(1)

Mathematically this is expressed as (2):


53/134

38

Me Mc

Glasssd=

sdc

(2)

Where Me = Mean of experimental group, Mc = Mean of control group, and sdc =standard deviation of control group.

Design of the Study

The empirical research design of this study centers around the use of an

exploratory meta-analysis as an analytic procedure to estimate the instructional

effect that computers used under various instructional strategies have on student

learning.

Outline of the Procedure

Cooper and Hedges (1994) outline five major steps to conducting a meta-

analytic research synthesis. With a few minor modifications, this is the procedure

followed in the present study. The five steps are:

1. Problem Formulation Stage: Primary research must exist consisting of

a minimum of two hypothesis tests (p. 9).

2. Data Collection Stage: Identify, locate, and retrieve all relevant study

documents.

3. Data Evaluation Stage: Coding the literature; missing data will arise in

every research synthesis (p. 11).

4. Analysis and Interpretation Stage: Estimating the magnitude of aneffectthe degree to which the phenomenon is present in the population or the

degree to which the null hypothesis is false (p. 11).

5. Public Presentation Stage: Assembling and presenting the results of theanalysis.


54/134

39

Problem Formulation

There is a body of extant research on many of the individual aspects of

the problem addressed by this study and that reservoir of data, or universe,

provides ample material upon which to conduct a research synthesis.

Unfortunately, many of the studies forming this universe are in direct

contradiction to other studies or involve dramatically different study populations.

Both instances create difficulties for those looking for some point of consensus or

mutual agreement. That, however, is what a research synthesis strives to locate:

Any research synthesis should allow the researcher to see patterns across studies

that are not apparent when studies are examined individually or serially" (Cooper

& Hedges, 1994, p. 360). Such a research methodology exists: the meta-analysis.

Research hypotheses. Light and Pillemar (cited in Hedges, 1994a)

identify two types of questions or hypotheses that can be asked in a research

synthesis: The Type 1 question refers to a precisely specified hypothesis posed

in advance of the analysis, for example, On average, does this treatment work?

The Type 2 question, on the other hand, asks a vague question intending to derive

a more explicit hypothesis from the data gathered and analyzed. For example:

Under what kind of conditions does the treatment work best? The Type 2

question allows one to modify the research hypothesis as a greater understanding

of the subject is developed in response to the information gathered. Normally, as

Cooper points out, in primary research, [this] redefinition of a problem as a study

proceeds is frowned on. In research synthesis, it appears that some flexibilitymay be necessary and may indeed be beneficial [italics added] (Cooper, 1984, p.

55).

Type 1 and Type 2 research questions should not be confused with Type I

and Type II errors in statistical analysis. The data speak for itself" in this thesis.


55/134

40

In other words, a Type 2 question was posed, namely, Under what instructional

strategies (conditions) do computers (the treatment) produce the best results?

Data Collection

Rationale for data selection. The most egalitarian sources of literature

are the reference database systems such as PsychINFO, ERIC and MEDLINE.

Still, these broad, non-evaluative systems exclude the unpublished and most recent

literature (Cooper & Hedges, 1994, p. 10). The ERIC database provides an

accessible, convenient, and replicable study population. By using the ERIC

database with a defined time frame of studies to choose from, it becomes possible

to compare the results of this meta-analysis with future meta-analyses composed

of groups of studies which precede and succeed this one.

Criteria for document selection. The criteria for document selection used

in this study are shown below. Explanations for the establishment of the criteria

follow.

Criterion 1: The report must have been published on the ERIC Document

Retrieval Service (EDRS).

Criterion 2: EDRS search criteria

1. The word Computer must be found in the documents abstract.

2. Only studies published since 1997 will be considered.

3. Studies must be English language documents.4. Studies must be research documents.

Criterion 3: initial screening of the documents returned by the search

1. The use of computers was recorded.

2. The instructional strategy was identified or inferred.


56/134

41

3. Student achievement was recorded.

Criterion 4: Final stage of selection; required the study document to complete

1. The study identified either a control group and a treatment group, or

the study identified a Pre-test/Post-test assessment of a treatment

group, and

2. the necessary statistical data must have been reported (i.e., F, df, N,

r, d,z, t).

The ERIC database was chosen as the study population from which to

extract the specific study samples. ERIC was chosen over PsychINFO and

MEDLINE because it specializes in educational studies, including instructional

technology, whereas PsychINFO is focused on psychological issues, of which

learning is only a part, while MEDLINE is oriented around medical research.

The search was limited to studies published since 1997 for two reasons:

First, to take advantage of any advances in computer technology that might have a

meaningful impact on its use in the classroom, and second, to allow for the

possibility that with the passage of time, a larger number of educators will have

become technologically literate, leading to a greater variety in the instructional

milieu surrounding the use of computers in the classroom. The intent is to avoid,

as much as possible, the limitations that earlier, less powerful computer

technologies might have placed on instructional choices.

Computing includes more than just computers; it includes such categories

of computer use as distance educ

roberts (2002)-role of computers in restructuring

Documents