RELATIONSHIPS OF SELECTED FACTORS AND THE LEVEL OF COMPUTER USE FOR INSTRUCTIONAL PURPOSES BY TECHNOLOGY EDUCATION TEACHERS IN OHIO PUBLIC SCHOOLS: A STATEWIDE SURVEY DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Graduate School of The Ohio State University By Mohammed I. Isleem, B.A., M.A. ***** The Ohio State University 2003 Dissertation Committee: Professor Paul E. Post, Advisor Professor Michael L. Scott Professor Rick J. Voithofer Approved by Adviser College of Education
Copyright by Mohammed I. Isleem 2003
ABSTRACT This study determined the level of computer use for instructional purposes by technology education teachers in Ohio public schools. The study also investigated the relationships between the level of use and selected factors: expertise; access; attitude; support; and teacher characteristics. This study derived its theoretical framework from Rogers (1995) model of diffusion of innovations. A survey-correlation research design was used. A questionnaire was developed and mailed to all technology education teachers (N = 1170) in Ohio public schools in the 2002 2003 school year. Validity and reliability were established for the survey instrument. The return rate of the survey was 66%. Descriptive and inferential statistical techniques were used. The findings of this study indicated that technology education teachers have high levels of computer use in mainstream computer uses such as word processing, e-mail, Internet, and classroom management. Strong positive correlation existed between the level of computer use and teachers perceived expertise and teachers perceived attitude toward computers as tools. In addition, moderate positive correlation existed between the level of use and teachers perceived access to computers. Multiple regression analysis indicated a positive predictive value toward computer use with the demographic characteristics of instructional experience and modular instructional method, and a ii
negative predictive value with age and urban geographic location. The independent variables that explain the greatest amount of variation in the level of computer use were in order of predictive value: teachers perceived expertise, attitude, and access. Technology education teachers have high levels of computer use in mainstream applications and low levels of computer use in specialized applications. These levels of use are slightly lower than the state levels. Those teachers that possess expertise are the ones who use the computer for instructional purposes. Positive attitudes toward computers as tools provide a starting point for adoption of computer use. To increase computer use, technology education teachers need to be given more training. In-service training needs to be a top priority. Pre-service programs should include more courses in using computers as tools for teaching and learning. iii
Dedicated to My Parents ù ú Ibrahim Salm Isleem (1896 1974) Amnh Mohammed (Al-Faleet) Isleem ù ú iv
ACKNOWLEDGMENTS This dissertation is the result of the collective efforts of a number of important and valued people who have directly or indirectly assisted and supported me during doctoral studies and in this present endeavor. To these people, I owe my gratitude and thanks. I wish to express sincere appreciation and gratitude to the members of my dissertation committee. Dr. Paul E. Post, my adviser, for all of your guidance and support not only with this dissertation, but during my entire degree program. May God bless you and your family. Dr. Michael L. Scott, for making my life hard, but full of meaning and high standards. Dr. Scott, without your faith in me, I would never have had this opportunity. Dr. Rick J. Voithofer, for your insights and abilities in not only sharing your knowledge, but inspiring me to problem solve and supporting my efforts. The suggestions, advice, and support of all my professors and academic support personnel at The Ohio State University and elsewhere were major factors behind the successful completion of this study. Special thanks to Dr. William Loadman, Dr. David Rouch, Dr. Dick Dieffenderfer and the staff of the Ohio Department of Education, Dr. William Notz and the staff of the Statistical Consulting Service, Ms. Terri Childres and the staff of the Office of Testing, and Ms. Mari L. Derouaux and the staff of University Mail Services. v
I am grateful to Dr. Yusef Abu Diya, President of Al-Aqsa University in Palestine, and Dr. Richard Wolfson, Chairperson of Curriculum and Teaching at Montclair State University, for believing in my ability and supporting this endeavor. My family and I also wish to express our thanks to our American friends who made our stay in Ohio so joyful. Your love, compassion, and support made this time special and one that we will always remember. My thanks go to my family and friends worldwide for their encouragement, patience, and support. Special thanks to my brothers, sisters, nephews and nieces may God keep you and provide you with your dreams. Of course, I would like to express appreciation to my wife who stood beside me and tolerated me and provided endless love, support, kindness and patience. My love and gratitude go to my children who shared the good and bad days with their beloved Dad during all these difficult years. My most heartfelt thanks goes to Ms. Linda Knapp for meticulous editing during my doctoral studies. Her encouragement, patience, candor and arguments were invaluable to the completion of this endeavor. Finally, special thanks go to my Mom, whose continuous prayers and encouragement helped me accomplish my goals. vi
VITA February 26, 1957...Born Gaza, Palestine 1980...Teaching Certificate in Mathematics, Science and Agricultural Education Teacher Training School, Gaza, Palestine 1996...BS in Mathematics Al-Aqsa University, Gaza, Palestine 1998...MA in Technology Education Montclair State University, Upper Montclair, NJ, USA 1998 present...chairman & Associate Professor Department of Technology Education and Instructional Technology, Al-Aqsa University, Gaza, Palestine 2000 present...graduate Teaching & Administrative Associate School of Teaching & Learning, College of Education, The Ohio State University, Columbus, OH, USA FIELDS OF STUDY Major Field...Education Minor Field...Technology Education Minor Field...Instructional Technology vii
TABLE OF CONTENTS Page Abstract...ii Dedication...iv Acknowledgments...v Vita...vii List of Tables...x List of Figures...xi Chapters: 1. Introduction...1 Computer Use for Instructional Purposes...1 Statement of the Problem...5 Purpose and Objectives of the Study...6 Significance of the Study...7 Limitations...9 Variables of the Study...10 Definition of Terms...11 Questions of the Study...14 Hypotheses...15 Summary...16 2. Review of Research Literature...18 Introduction...18 Diffusion of Innovations...20 Contextually Related Studies...27 Selected Factors Related to Computer Use for Instructional Purposes...30 Summary...36 viii
3. Methods and Procedures...37 Purpose of the Study...37 Design of the Study...38 Population...38 Variables of the Study...39 Dependent Variable...39 Independent Variable...40 Instrumentation...45 Validity and Reliability...47 Pilot Study...48 Data Collection...49 Data Analysis...51 Summary...53 4. Findings...54 Data Sample...54 Introduction to Data Analysis...57 Level of Computer Use for Instructional Purposes...58 Teachers Perceived Expertise in Computer Use...62 Teachers Perceived Access to Computers...66 Teachers Attitude Toward Computers as Tools...73 Teachers Perceived Support...77 Selected Teacher Characteristics...82 Multiple Regression on the Level of Computer Use on Selected Factors... 100 Summary... 102 5. Discussion, Conclusions and Recommendations... 103 Summary... 103 Discussion of the Findings... 105 Conclusions... 113 Recommendations... 117 Recommendations and Implications... 117 Recommendations for Further Study... 120 List of References... 122 Appendices... 127 A. Pilot Study Instrumentation... 127 B. Study Instrumentation... 133 C. Panel of Experts... 136 D. IRB Approval... 138 E. Correspondence... 140 ix
LIST OF TABLES Table Page 3.1 Schedule for Data Collection...50 4.1 Number of Usable Respondents...55 4.2 Chi-Square Significant Values for the Level of Computer Use...56 4.3 Chi-Square Significant Values for Teachers Perceived Expertise...56 4.4 Frequency of the Level of Computer Use...59 4.5 Frequency of Teachers Perceived Expertise in Computer Use...62 4.6 Canonical Correlation Between the Level of Use and Expertise...65 4.7 Frequency of Access to Computers...66 4.8 Canonical Correlation Between the Level of Use and Access...69 4.9 Frequency of Factors Affecting Access to Computers...70 4.10 Canonical Correlation Between Access and Limiting Factors...72 4.11 Frequency of Teachers Attitudes Toward Computers as Tools...73 4.12 Canonical Correlation Between the Level of Use and Attitude...76 4.13 Frequency of Teachers Perceived Support...77 4.14 Canonical Correlation Between the Level of Use and Support...81 4.15 Multiple Regression on Dependent Variable Computer Use... 101 x
LIST OF FIGURES Figure Page 1.1 Variables of the Study...10 2.1 Diffusion of Innovations Adapted from Rogers (1995)...19 3.1 Information Sources for Instrument Construction...46 4.1 Frequency Percentages for the Level of Computer Use...61 4.2 Frequency Percentages for Teachers Perceived Expertise...63 4.3 Frequency Percentages for Teachers Perceived Access to Computers...67 4.4 Frequency Percentages for Factors Limiting Access...71 4.5 Frequency Percentages for Attitude Toward Computers as Tools...74 4.6 Frequency Percentages for Teachers Perceived Support...79 4.7 Gender of Technology Education Teachers...83 4.8 Age of Technology Education Teachers...84 4.9 Geographical Location of Technology Education Teachers...86 4.10 Grade Level of Technology Education Teachers...88 4.11 Educational Achievement of Technology Education Teachers...89 4.12 Educational Background of Technology Education Teachers...90 4.13 Instructional Experience of Technology Education Teachers...92 4.14 Computer Experience of Technology Education Teachers...94 4.15 Instructional Expertise of Technology Education Teachers...95 xi
4.16 Computer Academic Content Taught...97 4.17 Instructional Method of Technology Education Teachers...98 xii
CHAPTER 1 INTRODUCTION Technology has now changed or altered how people access, gather, analyze, present, transmit, and simulate information. Today s technologies provide the tools, applications, and processes that empower individuals of our information society. (See, 1994, p. 30) Many educators believe that computer use for instructional purposes can be employed effectively to support needed reform in education, and many researchers and public officials have championed computer use for instructional purposes as a benefit to teaching and learning (U.S. Department of Education, 2002a; Dooley, 1999; Hunter, 1993). Multiple speeches by former U.S. Secretary of Education Richard W. Riley (February 17, 1998; July 29, 1998) included directives to education professionals concerning the benefits of technology use, specifically computers, in instruction efforts. To advance technology understanding and use in education, standards for technological literacy, instructional technology and information literacy have been proposed by professional education organizations: the International Technology Education Association (ITEA) (2000), the International Society for Technology in Education (ISTE) (1998) and the American Association of School Librarians (AASL) (1998) respectively. 1
The current attitude of the administration toward the use of technology in educational contexts is reflected in the introduction to e-learning: Putting a world-class education at the fingertips of all children (U.S. Department of Education, 2002a, 3). Research and evaluation studies demonstrate that school improvement programs that employ technology for teaching and learning yield positive results for students and teachers. Given that many schools and classrooms have only recently gained access to technology for teaching and learning, the positive outcomes of these studies suggest a future for education that could be quite bright if the nation maintains its commitment to harnessing technology for education. Kenneth Green, founder/director of The Campus Computing Project, (the largest continuing study of the role of information technology in U.S. colleges and universities) sees the current challenges as instructional technology integration and the human factors associated with this assisting students and faculty to make effective use of new technologies in ways that support teaching, learning, instruction and scholarship (University of Missouri, Columbia, 2002). Consistent with constructivist perspectives, computer technologies are changing the teacher s role from information giver to facilitator, counselor, advisor, guide, coach, co-learner, mentor, resource and technology managers, and mediator to the students (Jonassen, 1999; Dyrli & Kinnaman, 1994; Brooks & Brooks, 1993). The 1998 Teaching, Learning and Computing Study, conducted by Center for Research on Information Technology and Organizations (CRITO), University of California, Irvine, was one of the first major national research studies to examine teachers and students who use Internet computers on a regular basis. In examining the computer/constructivist relationship, Becker (1999) said, 2
This relationship is perhaps due to the fact that technology provides students with almost unlimited access to information that they need in order to do research and test their ideas. It facilitates communication, allowing students to present their beliefs and products to broader audiences and also exposes them to the opinions of a more diverse group of people in the real world beyond the classroom, school and local community all conditions optimal for constructivist learning. (p. 8) The application of computers in the curriculum is another area receiving attention in the literature and the data suggest that computers have, in fact, become an important component of technology education. (Sanders, 2001, p. 47) Additionally, these innovative methods provide a new, rich educational context within which educators may apply constructivist learning theories popular in current technology education discourse (Jonassen, 1999). While both Becker, Ravitz & Wong (1999) and Ohio SchoolNet Commission (2002) have conducted extensive studies on the levels of computer adoption by teachers, neither have produced any indication of the adoption levels of computer use for instructional purposes by technology education teachers. Technology is defined by the International Technology Education Association as human innovation in action that involves the generation of knowledge and processes to develop systems that solve problems and extend human capabilities and the innovation, change, or modification of the natural environment to satisfy perceived human needs and wants. (ITEA, 2000, p. 251) Technology education is also defined by ITEA as the study of technology, which provides an opportunity for students to learn about the processes and knowledge related to technology that are needed to solve problems and extend human capabilities. (p. 251) As an innovation, therefore, computer use for instructional purposes is both an example of technology and a tool to help study technology. 3
In this study, computer use was defined as the use of computer and its software to accomplish practical tasks, and instructional purposes were defined as lesson preparation, lesson delivery, evaluation, communication and administrative record keeping (i.e., grades, attendance). Computer use for instructional purposes was considered an innovation (Rogers, 1995). Given the perceived benefit to teaching and learning, the extent of computer use for instructional purposes became a necessary focus point for further research. While technology education utilizes many computers in different subject matters, this study focused on computer use for instructional purposes only, excluding those uses that are specifically content related (i.e., modular, robotics). According to ITEA (2000), technology is innovation in action. Innovations can be adopted or rejected. Rogers book Diffusion of Innovations, first published in 1962, and now in its fourth edition (1995), is the closest any researcher has come to presenting a unified theory of diffusion of innovations (Surry & Farquhar, 1997). Rogers (1995) promoted the need for a standard classification scheme for describing the perceived attributes of innovations in universal terms (p. 208). Rogers (1995) theory is based on his definition of diffusion the process by which an innovation is communicated through certain channels over time among the members of a social system. (p. 10) This theoretical framework was selected to provide structure to this inquiry. Researchers have validated Rogers theory by investigating the diffusion of various innovations (Jacobsen, 1997). The most relevant to the topic of this study included Blankenship s (1998) study of the use of computers in classroom instruction; Hoerup s (2001) study of computer technology integration; Jacobsen s (1998) study of computer technology integration in teaching and learning; and Albejadi s (2000) study of 4
Internet adoption by teachers in Ohio. Diffusion of Innovations has also been used as a framework in numerous studies within the field of technology education. Brusic & LaPorte (2000) used Rogers (1995) to study the status of modular technology education in Virginia. Bussey, Dormondy & VanLeeuwen (2000) applied Rogers theory as a framework for identifying some factors that could predict the adoption of technology education in New Mexico public schools. Ndahi (1999) used Rogers theory when studying the utilization of distance learning technology among industrial and technical teacher education faculty. Further validation of this theory in a technology education context provided insights into the variables that relate to the level of diffusion of computer use for instructional purposes by technology education teachers in Ohio public schools. Approaching a research problem within Rogers (1995) framework, and reviewing previous research, permitted the determination of the factors that might be associated with levels of computer use. Then, these factors were examined for relationships to it. A correlation between the factors studied and the level of computer use provided quantitative data and analysis on which local and state decision-makers in Ohio could then base reform policies and programs promoting the adoption of this innovation among technology education teachers in Ohio public schools. Statement of the Problem Information regarding innovations that resulted in improved teaching and learning outcomes was needed for successful education development and/or reform. Computer use for instructional purposes was one innovation that was worthy of further investigation. 5
A limited number of studies had been conducted on computer use for instructional purposes. However, these previous studies had been too few and the population studied too broad in size to permit any firm conclusions or generalizations to technology education teachers (Becker, 1999; Ohio SchoolNet Commission, 2002). Were technology education teachers more or less supportive or resistant to computer use for instructional purposes than teachers in general? Without this knowledge, it is difficult to develop strategies to promote the adoption if the reasons for teacher willingness or unwillingness to use these technologies are not understood. The problem addressed by this study was the lack of information regarding the level of computer use for instructional purposes by technology education teachers in Ohio public schools and the factors related to it. Purpose and Objectives of the Study The purpose of this study was to identify the extent to which technology education teachers use computers for instructional purposes in Ohio public schools. Furthermore, this study examined the relationships among factors identified as potentially related to it. Selected factors used in this study were based on Rogers (1995) diffusion theory and previous research and included: (1) teachers perceived expertise in computer use; (2) teachers perceived access to computers; (3) teachers attitude toward computers as tools for instructional purposes; (4) teachers perceived support for computer use; and (5) selected characteristics of technology education teachers. To accomplish this purpose, the objectives of the study were: 6
Determine to what extent technology education teachers in Ohio public schools use computers for instructional purposes. Determine teachers perceived expertise in computer use. Determine teachers perceived access to computers. Determine teacher s attitude toward computers as tools for instructional purposes. Determine teachers perceived support in using computer. Identify selected characteristics of technology education teachers in Ohio public schools in relation to adopter category characteristics. Identify the relationships between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and the selected factors: expertise; access; attitude; support; and selected characteristics. Identify which independent variables explain the greatest amount of variance in the level of computer use by technology education teachers in Ohio public schools for instructional purposes. Significance of the Study The Impact of Educational Technology on Student Achievement (Schacter, 1995) reflected the analysis of more than 700 studies and concluded that students who had access to educational technology showed positive gains in academic achievement when technology initiatives were focused on teaching and learning. In light of this benefit to teaching and learning, directives from the U.S. Department of Education encouraged the implementation of technology for instructional purposes of all grade levels and curricula (Riley, February 17, 1998; Riley, July 29, 1998). Since technology education 7
professionals are expected to embrace and encourage innovation, and technology education as a field is struggling for autonomy in the school curriculum, increased computer use for instructional purposes was believed to play an important role as a catalyst for encouraging decision-makers, educators, students, parents, and the community to support the adoption of this innovation as well as this vital field of technology education. Since the purpose of this study was to identify the extent to which technology education teachers use computers for instructional purposes in Ohio public schools and the factors related to it, the findings of this study could lead to the following practical benefits. 1. The Ohio Department of Education may acquire data and analysis to identify what factors were related to computer use for instructional purposes by technology education teachers in Ohio as well as specific recommendations about how best to increase computer use for instructional purposes. In addition, the study will provide a more current and detailed demographic view of technology education teachers in the state of Ohio, which may help decision makers to implement technological literacy standards in the school year 2003-2004. 2. Ohio Universities and Colleges may gain specific recommendations about how best to increase computer use for instructional purposes by technology education teachers for implementation in their teacher training programs. 3. Local School Districts may gain specific recommendations about how best to invest their resources in order to increase computer use for instructional purposes by technology education teachers. 8
4. Ohio Technology Education Teachers may become aware of computer use for instructional purposes as a teaching tool as well as the factors they might examine in their own contexts to improve their mastery of the tool. Limitations The following limitations served to narrow the scope of the study: This study was limited to computer use for instructional purposes as defined above. This study was limited to public schools in the state of Ohio. This study was limited to teachers who are teaching technology education (including programs still named industrial technology education or industrial arts education). Computer use did not include modular or robotics instruction modules. This study was conducted during the academic year 2002-2003. Due to time constraints, late respondents were used instead of non-respondents to validate generalizability. 9
Variables of the Study The dependent variable was the perceived level of computer use for instructional purposes by technology education teachers in Ohio public schools (See Figure 1.1). Independent variables were: 1. Teachers perceived expertise in computer use 2. Teachers perceived access to computers 3. Teachers attitude toward computers as tools for instructional purposes 4. Teachers perceived support for computer use 5. Selected characteristics of technology education teachers Figure 1.1: Variables of the Study 10
Definition of Terms The purpose of defining terms is to provide the technical details necessary for reproducing the study. This study used two types of definitions: constitutive and operational. According to Kerlinger and Lee (2000), a constitutive definition defines a construct using other constructs (a concept that has been designed for a specific purpose) (p. 42). The constitutive definition of the term intelligence, for example, is that intelligence is the ability to learn or understand or to deal with new or trying situations (Merriam-Webster, 2003). Kerlinger and Lee also described an operational definition as a definition that assigns meaning to a construct or variable by specifying the activities or operations necessary to measure it and evaluate the measurement. (p. 42) An operational definition of the term intelligence, for example, would be a person s score on the Stanford-Binet Intelligence Scale, which computes IQ. This study defined the following terms: Level of Computer Use for Instructional Purposes Constitutive definition Level was defined by the Merriam-Webster Dictionary (2003) as a position in a scale or rank; computer was defined as a programmable electronic device that can store, retrieve, and process data; use was defined as a method or manner of employing or applying something; and instruction was defined as the action, practice, or profession of teaching. Level of computer use for instructional purposes was constitutively defined as a position in a scale or rank of the application of a programmable electronic device in the practice of teaching. 11
Operational definition For the purposes of this study, level of computer use for instructional purposes was operationally defined as the use of computer and its software for lesson preparation, lesson delivery, evaluation, communication and administrative record keeping (i.e., grades, attendance) as measured by the instrument developed for this study. Expertise in Computer Use Constitutive definition Expertise was defined by the Merriam-Webster Dictionary (2003) as the skill of an expert [having, involving, or displaying special skill or knowledge derived from training or experience]. Operational definition For the purposes of this study, expertise was operationally defined as technology education teachers beliefs about personal efficiency and effectiveness when using computers for instructional purposes as measured by the instrument developed for this study. Access to Computers Constitutive definition Access was defined by the Encarta World English Dictionary (1999) as the right or ability to log on to a computer system or use a computer program and limitation was defined by the Merriam-Webster Dictionary (2003) as something that bounds, restrains, or confines. Operational definition For the purposes of this study, access was operationally defined as the perceived availability of computers that the technology education teacher may use as measured by the instrument developed for this study. 12
Attitude Toward Computers as Tools Constitutive definition Attitude was defined by the Merriam-Webster Dictionary (2003) as a feeling or emotion toward a fact or state. Operational definition For the purposes of this study, attitude was operationally defined as the teacher s attitude toward the use and integration of computers as tools for instructional purposes as measured by the instrument developed for this study. Support for Computer Use Constitutive definition The Encarta World English Dictionary (1999) provided three applicable definitions for support: to give active help, encouragement, or money to somebody or something; to be in favor of something such as a cause, policy, or organization, and wish to see it succeed; and to provide technical support for a computing system or package. Operational definition For the purposes of this study, support was operationally defined as the extent to which members of the school administration and colleagues support technology education teachers in computer use for instructional purposes as measured by the instrument developed for this study. Teacher s Characteristic Constitutive definition Characteristic was defined by the Merriam-Webster Dictionary (2003) as a distinguishing trait, quality, or property. 13
Operational definition For the purposes of this study, characteristic was operationally defined as demographic information about technology education teachers in Ohio public schools as measured by the instrument developed for this study. Questions of the Study Research questions were used to guide the research investigation. This study addressed the following questions: 1. What is the level of computer use by technology education teachers for instructional purposes in Ohio public schools? 2. What is the level of teachers perceived expertise in computer use? What is the relationship between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived expertise in computer use? 3. What is the level of technology education teachers perceived access to computers? What is the relationship between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived access to computers? 4. What is the level of teachers attitude toward computers as tools for instructional purposes? What is the relationship between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers attitude toward computers as tools for instructional purposes? 14
5. What is the level of teachers perceived support? What is the relationship between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived support? 6. What are the selected characteristics of technology education teachers in Ohio public schools? What is the relationship between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and the selected characteristics of the teachers? 7. Which independent variables explain the greatest amount of variance in the level of computer use for instructional purposes by technology education teachers in Ohio public schools? Hypotheses 1. There is no significant correlation between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived expertise in computer use. 2. There is no significant correlation between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived access to computers. 3. There is no significant correlation between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers attitude toward computers as tools for instructional purposes. 15
4. There is no significant correlation between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and teachers perceived support. 5. There are no significant correlations between the level of computer use for instructional purposes by technology education teachers in Ohio public schools and the selected characteristics of the teachers. Summary The perceived benefit to teaching and learning that computer use for instructional purposes offers has stimulated discourse in the areas of standards, constructivism, and human factors (U.S. Department of Education, 2002a; Dooley, 1999; Hunter, 1993; ITEA, 2000; ISTE, 1998; AASL, 1998; Becker, 1999; Jonassen, 1999; University of Missouri, Columbia, 2002). In addition, while Becker, Ravitz & Wong (1999) and Ohio SchoolNet Commission (2002) have conducted extensive studies on the levels of computer adoption by teachers, neither have provided any indication of the adoption levels of computer use for instructional purposes by technology education teachers in Ohio. This study addressed this lack of information regarding the level of computer use for instructional purposes by technology education teachers in Ohio public schools and the factors related to it so critical for informed local and state decision making. Approaching the research problem within the framework of Rogers (1995) Diffusion of Innovations, and reviewing previous research, permitted the determination of the factors that might be associated with levels of computer use for instructional purposes. This study set out to identify the extent to which technology education teachers 16
use computers for instructional purposes in Ohio public schools and examine the relationships among factors identified as potentially related to the level of computer use for instructional purposes. Selected factors used in this study included: (1) teachers perceived expertise in computer use; (2) teachers perceived access to computers; (3) teachers attitude toward computers as tools for instructional purposes; (4) teachers perceived support for computer use; and (5) selected characteristics of technology education teachers. This study provided quantitative data and analysis on which local and state decision-makers in Ohio could base reform policies and programs promoting the adoption of this innovation among technology education teachers in Ohio public schools. Recommendations were geared toward the Ohio Department of Education, Ohio universities and colleges, local school districts, and Ohio technology education teachers. This study was limited to teachers who were teaching technology education in public schools in the state of Ohio during the academic year 2002-2003, and computer use for instructional purposes as defined by this study, which did not include modular nor robotics instruction modules. Research questions and hypotheses were directly guided by the objectives of the study, which developed from reflection on the research problem and the purpose of the study. 17
CHAPTER 2 REVIEW OF RESEARCH LITERATURE Introduction Increased computer use for instructional purposes by technology education teachers may become a catalyst to encourage educators, students, parents and the community to better understand and support this vital field. However, there is currently very little research specifically targeting technology education teachers in relation to computer use for instructional purposes, which would help decision-makers to promote technology education. Therefore, the results of a focused study on the factors relating to computer use for instructional purposes by technology education teachers in Ohio would greatly benefit local and state decision-makers in Ohio. The purpose of this study was to examine the relationship between computer adoption factors and the perceived level of computer use for instructional purposes by technology education teachers in Ohio public schools. In order to better understand why the technology education teachers are or are not adopting computers for instructional purposes, there was a need to collect data on both the level of computer use by technology education teachers and the factors that relate to their level of computer use in their courses. 18
The theoretical framework for this study was the diffusion of innovations theory developed by Everett M. Rogers (1995) (See Figure 2.1). Many researchers considered Rogers the leader of adoption/diffusion research since publishing Diffusion of Innovations in 1962 (Carr, 1999). The book presented a thorough study and description of the model of diffusion of innovations. Many scholars considered this book to be the basic guide to the theory (McCormack-Brown, 1999). Figure 2.1. Diffusion of Innovations Adapted from Rogers (1995). 19
What are the most influential factors that are related to computer use for instructional purposes? Understanding and defining computer use for instructional purposes was the first and most important necessity of this study. Understanding and defining the factors related to computer use for instructional purposes, as found in the literature, was the next responsibility. A search of the literature about computer use suggested some major factors were expertise, access, attitude, support, and selected characteristics of teachers. This review consists of the discussion of Rogers and diffusion of innovations, in which this study was grounded; the use of diffusion of innovations in the contexts of educational research in general and technology education specifically; and the literature supporting the selection of the factors related to computer use for instructional purposes. Diffusion of Innovations Diffusion is the process by which an innovation is communicated through certain channels over time among the members of a social system. (Rogers, 1995, p. 10) The underlying infrastructure of this statement is comprised of complex, non-linear and interrelated concepts and systems that attempt to describe the process of change based on decision-making as it occurs in a community. In the academic community, the instructors are centrally positioned as the major stakeholders (Siegel, 2002). Rogers provided a visual for the adoption and diffusion process in relation to consequences both internal and external to the system, A system is like a bowl of marbles: Move any one of its elements and the positions of the others are inevitably changed also. The interdependency is often not fully understood by the adopters of an 20
innovation, and may not be comprehended by the change agents who introduce a new idea in a system. (Rogers, 1995, p. 419) Now imagine a particularly round bowl containing these marbles, and that this bowl is considered a marble in another larger bowl, and so on. This is the level of complexity in examining the diffusion of an innovation. Therefore, in order to build on the framework that Rogers provides, this study focused on those components most material to this endeavor and, with justification, left behind the rest. Figure 2.1 shows a schematic of the theoretical framework. Innovation An innovation, according to Rogers (1995), is an idea, practice or object perceived as new by an individual or other unit of adoption. The person may not have yet developed favorable or unfavorable attitudes, nor adopted or rejected it. Much of Rogers work dealt with technological innovations. A technological innovation usually has at least some degree of benefit for its potential adopters, while not always very clear-cut. Intended adopters are seldom certain that an innovation represents a superior alternative to the previous practice that it might replace. (Rogers, 1995, p. 13) Computer use for instructional purposes is a practice that while in existence for the last thirty years was generally perceived as new by educational professionals because of the increased capabilities afforded it by increased Internet connectivity and refinement of information technologies. While proponents of an innovation frequently cite the beneficial aspects, there is considerable uncertainty about the actual consequences of adoption (Rogers, 1995). 21
Technological Innovations, Information and Uncertainty Rogers (1995) sees technology as a design for instrumental action that reduces the uncertainty in the cause-effect relationship involved in achieving a desired outcome. This uncertainty drives the potential adopter to seek out information, which will help to reduce the uncertainty associated with adopting or rejecting the innovation. Technology, he goes on to add, usually has two components: (a) hardware, consisting of the tool that embodies the technology as a material or physical object and (b) software, consisting of the information base for the tool (p. 12). Related to this are two kinds of information in respect to technological innovations: (a) software information, embodied in a technology and serving to reduce uncertainty about the cause-effect relationship in achieving a desired outcome and (b) innovation-evaluation information, the reduction in uncertainty about an innovation s expected consequences. Computer use for instructional purposes, as an innovation, contained both hardware and software components that were consistent with general computer information systems models. Technology Clusters A technology cluster consists of one or more distinguishable elements of technology that are perceived as being closely interrelated. Associated with the idea of technology clusters is the assumption that an adopter s experience with an innovation influences that individual s perception of the next innovation to diffuse through the individual s system (Rogers, 1995). Computer use for instructional purposes belonged to the cluster of information and communication technologies that have been adopted by mainstream society in the U.S. since the 1980s. 22
Characteristics of Innovations The characteristics of an innovation, as perceived by individuals, help to explain their different rate of adoption and are associated with the first three out of five steps in the innovation-decision process [discussed later in this chapter]. Rogers (1995) five characteristics of innovations are: Relative advantage is the degree to which an innovation is perceived as better than the idea it supersedes; sub-dimensions are: economic profitability, low initial cost, decreased discomfort, social prestige, time & effort savings and immediacy of reward. Compatibility is the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters. Complexity is the degree to which an innovation is perceived as difficult to understand and use. Trialability is the degree to which an innovation may be experimented with on a limited basis. Observability is the degree to which the results of an innovation are visible to others; this stimulates peer discussion of a new idea (Rogers, 1995). According to Rogers (1995), past research indicates these five qualities are the most important characteristics of innovations in explaining the rate of adoption... the relative speed with which an innovation is adopted by members of a social system. (p. 22-23). Innovations that are perceived by individuals as having greater relative advantage, compatibility, trialability, observability, and less complexity will be adopted more rapidly than other innovations. In other words, an innovation will experience an increased rate of diffusion if potential adopters perceive that the innovation: 1) has an advantage relative to other innovations (or the status quo); 2) is compatible with existing practices and values; 3) is not overly complex; 4) can be tried on a limited basis before 23
adoption; and 5) offers observable results (Surry & Farquhar, 1997). An important fact to note is that perceptions count. Receivers perceptions of the attributes of an innovation, not the attributes as classified by experts or change agents, affect its rate of adoption (Rogers, 1995). These attributes were reflected in varying degrees in previous research and were refined in the scope in this study through the investigation of attitudes of and perceived support for computer use for instructional purposes. Re-invention Re-invention is the degree to which an innovation is changed or modified by a user in the process of its adoption and implementation. (Rogers, 1995, p. 17) This can significantly alter what some might consider a linear process. Re-invention is responsible for the major refinements that have occurred in the computer technologies in the last thirty years leading up to the increased capabilities of the current state of the art. Communication Channels A communication channel is the means by which messages get from one individual to another. (Rogers, 1995, p.18) Mass media channels are all those means of transmitting messages that involve a mass medium (i.e., radio, television, newspapers) which enable a few individuals to reach an audience of many. Interpersonal channels involve a face-to-face exchange between two or more individuals. Most adopters depend mainly upon the experience of near-peers (Rogers, 1995). Homophily is the degree to which two or more individuals who interact are similar in certain attributes, (i.e., beliefs, education, social status). More effective 24
communication occurs when two or more individuals are homophilous. However, one of the most distinctive problems in diffusion of innovation is that the participants are usually quite heterophilous. The very nature of diffusion demands that at least some degree of heterophily exist between the two participants (Rogers, 1995). Time Time is involved in diffusion in an innovation s rate of adoption in a system, the innovation-decision process, and the innovativeness of an individual. Rogers (1995) proposed that the ideal pattern of the rate of adoption of an innovation is represented as an S-shaped curve, with time on the x-axis and number of adopters on the y-axis incorporated in Figure 2.1. An innovation goes through a period of slow, gradual growth before experiencing a period of relatively dramatic and rapid growth. The time element is also involved in identifying the stage of the innovationdecision process and the innovativeness of the adopters. The innovation-decision process is the process through which an individual passes from first knowledge of an innovation to confirmation of his/her decision. It is essentially an information-seeking and information-processing activity in which the individual and/or organizations are motivated to reduce uncertainty about the consequences of the innovation. This aspect of the theory remains among the most useful and well known (Surry & Farquhar, 1997). The five steps of the process for individuals are knowledge, persuasion, decision, implementation, and confirmation (Rogers, 1995). Many innovation-decisions are made by an organization rather than by individuals. In those cases the decision process is more 25
complicated because a number of individuals are involved. This process for organizations also has five steps: agenda-setting, matching, redefining/restructuring, clarifying and routinizing (Rogers, 1995). Innovativeness is the degree to which an individual or other unit of adoption is relatively earlier in adopting new ideas than the other members of a system. Adopter categories are the classifications of members of a social system based on innovativeness (Rogers, 1995). The theory states individuals who are predisposed to being innovative will adopt an innovation earlier than those who are less predisposed (Surry & Farquhar, 1997). Figure 2.1 shows the normal distribution of individual innovativeness and the percentage of potential adopters theorized to fall into each category (Rogers, 1995). On one extreme of the distribution are the Innovators the risk takers and pioneers who adopt an innovation very early in the diffusion process and on the other end are the Laggards those who resist adopting an innovation until rather late in the diffusion process, if ever (Surry & Farquhar, 1997). Social System A social system is defined as a set of interrelated units that are engaged in joint problem solving to accomplish a common goal. (Rogers, 1995, p. 23). It constitutes a boundary within which an innovation diffuses. Important concepts within the social system are the structure (the patterned arrangements of the units in a system), system norms (established behavior patterns for the members of a social system), opinion leadership (the degree to which an individual is able to influence other individuals attitudes or overt behavior informally in a desired way with relative frequency) and 26
change agents (an individual who influences clients innovation-decisions in a direction deemed desirable by a change agency external to the system) (Rogers, 1995). There are three types of innovation-decisions (Rogers, 1995): optional innovation-decision (independent choices made by the individuals within the social system); collective innovation-decision (choices made by consensus among the members of a system); and authority innovation-decision (choices made by a relatively few individuals in a system who possess power, status or technical expertise). Contextually Related Studies Rogers (1995) discussed the importance of contexts in examining a social system as a factor influencing the rate of adoption. One thing to note about adoption research is that while Rogers work is highly regarded and often used, some researchers use other theories in addition to, or instead of, his diffusion of innovations theory (Sherry, Billig, Tavalin & Gibson, 2000; Blankenship, 1998). Also, while many researchers have studied the diffusion of computer technologies and diffusion in education, few have studied computer use for instructional purposes by public school teachers. The following are among those who studied contexts related to this study: Blankenship s (1998) study of Factors Related to Teacher Use of Computers in Classroom Instruction was centered on 241 K-12 teachers in public schools in Carroll County, Virginia. The study employed qualitative and quantitative methods grounded in three areas of research: school change, diffusion of innovations and behavioral psychology. Blankenship used diffusion of innovations (1995) theory as a model for studying diffusion of innovations in order to understand the diffusion of the use of 27