Factors That Influence Dissemination in Engineering Education

Although the need for new educational materials and methods in engineering education is increasing, the process of disseminating (making target groups become aware of, accept, and use) these innovations remains a challenge. A literature review shows that few studies have thoroughly investigated this area. The purpose of this article is to identify factors that may affect the adoption and use of educational innovations used in engineering education and to offer advice to educators on how they may better disseminate their materials. This study uses extant theories related to diffusion and acceptance of innovation as the basis for identifying factors that may impact the dissemination of educational innovations. These factors are tested via a Delphi study employing 21 subject-matter experts and content analysis of 410 research abstracts. The results suggest nine factors that are most important for facilitating acceptance and use of educational engineering innovations. In particular, new materials should be designed such that they demonstrate an obvious relative advantage over existing materials, are compatible with and adaptable to existing pedagogy, lack complexity, and are generally easy to use. Management support and availability of resources are found to be important environmental conditions that facilitate acceptance; logistical issues and cultural differences are the chief impediments.

[1]  Kay S. Bull,et al.  The light applications in science and engineering research collaborative undergraduate laboratory for teaching (LASER CULT)-relevant experiential learning in photonics , 2005, IEEE Transactions on Education.

[2]  John C. Henderson,et al.  Strategic alignment: a model for organizational transformation via information technology , 2011 .

[3]  C. Henderson,et al.  Beyond Dissemination in College Science Teaching: An Introduction to Four Core Change Strategies , 2010 .

[4]  Michael R. Simonson,et al.  Development of a Standardized Test of Computer Literacy and a Computer Anxiety Index , 1987 .

[5]  James C. Wetherbe,et al.  The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing , 1990, Inf. Syst. Res..

[6]  Reed Stevens,et al.  Multiple Perspectives on Engaging Future Engineers , 2011 .

[7]  Richard,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace , 2022 .

[8]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[9]  Heidi A. Diefes-Dux,et al.  What is an Engineer? Implications of Elementary School Student Conceptions for Engineering Education , 2011 .

[10]  W. Neuman,et al.  Social Research Methods: Qualitative and Quantitative Approaches , 2002 .

[11]  Jim Richardson,et al.  The Evolution of Curricular Change Models within the Foundation Coalition , 2004 .

[12]  Wei-Tek Tsai,et al.  Collaborative Learning Using Wiki Web Sites for Computer Science Undergraduate Education: A Case Study , 2011, IEEE Transactions on Education.

[13]  Liesl Hotaling,et al.  A paradigm for vertically integrated curriculum innovation - how curricula were developed for undergraduate, middle and high school students using underwater robotics , 2007 .

[14]  Euan Lindsay,et al.  Effects of laboratory access modes upon learning outcomes , 2005, IEEE Transactions on Education.

[15]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[16]  E. Brynjolfsson,et al.  Beyond Computation: Information Technology, Organizational Transformation and Business Performance , 2000 .

[17]  Michael Huberman,et al.  Knowledge dissemination and use in science and mathematics education: A literature review , 1994 .

[18]  Luis L. Martins,et al.  A Model of Business School Students' Acceptance of a Web-Based Course , 2004 .

[19]  Moez Limayem,et al.  E-Mail and V-Mail Usage: Generalizing Across Technologies , 2000, J. Organ. Comput. Electron. Commer..

[20]  Allen Newell,et al.  The keystroke-level model for user performance time with interactive systems , 1980, CACM.

[21]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[22]  Gordon Hayward,et al.  Engineering the Future: Embedding Engineering Permanently Across the School–University Interface , 2010, IEEE Transactions on Education.

[23]  Jeanne L. Tunks,et al.  Changing practice, changing minds, from arithmetical to algebraic thinking: an application of the concerns-based adoption model (CBAM) , 2009 .

[24]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[25]  Younghwa Lee,et al.  The Technology Acceptance Model: Past, Present, and Future , 2003, Commun. Assoc. Inf. Syst..

[26]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[27]  A. Mohr,et al.  Cultural Determinants of Learning Style Preferences , 2010 .

[28]  Maura Borrego,et al.  Constructive Alignment of Interdisciplinary Graduate Curriculum in Engineering and Science: An Analysis of Successful IGERT Proposals , 2010 .

[29]  C Duffield,et al.  The Delphi technique. , 1988, The Australian journal of advanced nursing : a quarterly publication of the Royal Australian Nursing Federation.

[30]  Chetan S. Sankar,et al.  Dissemination of Innovations from an Educational Research Project through Focused Workshops , 2002 .

[31]  C. Henderson,et al.  Increasing the Impact and Diffusion of Stem Education Innovations , 2022 .

[32]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[33]  Antonio J. López-Martín Attracting Prospective Engineering Students in the Emerging European Space for Higher Education , 2010, IEEE Transactions on Education.

[34]  Nigel Melville,et al.  Information technology innovation diffusion: an information requirements paradigm , 2008, Inf. Syst. J..

[35]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[36]  Andrew T. Roach,et al.  School-Based Consultants as Change Facilitators: Adaptation of the Concerns-Based Adoption Model (CBAM) to Support the Implementation of Research-Based Practices , 2009 .

[37]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[38]  Maura Borrego,et al.  Diffusion of Engineering Education Innovations: A Survey of Awareness and Adoption Rates in U.S. Engineering Departments , 2010 .

[39]  Magid Igbaria,et al.  The effects of self-efficacy on computer usage , 1995 .

[40]  William M. Marcy,et al.  The making of the special issue on the application of information technologies to engineering and science education , 1996 .

[41]  Sree Nilakanta,et al.  Implementation of Electronic Data Interchange: An Innovation Diffusion Perspective , 1994, J. Manag. Inf. Syst..

[42]  Jane M. Howell,et al.  Personal Computing: Toward a Conceptual Model of Utilization , 1991, MIS Q..

[43]  C. Steinfield,et al.  A Social Information Processing Model of Media Use in Organizations , 1987 .

[44]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[45]  David J. Weerts Toward an Engagement Model of Institutional Advancement at Public Colleges and Universities , 2007 .

[46]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[47]  Karl A. Smith,et al.  EngineeringEducation: Departments, Degrees and Directions , 2010 .

[48]  Robert Chia,et al.  Developing Paradigmatic Awareness in University Business Schools: The Challenge for Executive Education , 2007 .

[49]  J. Fairweather,et al.  Linking Evidence and Promising Practices in Science , Technology , Engineering , and Mathematics ( STEM ) Undergraduate Education A Status Report for The National Academies National Research Council Board of Science Education , 2008 .

[50]  Sumit Ghosh,et al.  Integrating design into undergraduate honors theses in a computer engineering program: an experiment , 2000, IEEE Trans. Educ..

[51]  Suzanne W. Dietrich,et al.  Developing Advanced Courses for Undergraduates: A Case Study in Databases , 2008, IEEE Transactions on Education.

[52]  H. Russell Bernard,et al.  Social Research Methods: Qualitative and Quantitative Approaches , 2000 .

[53]  Joseph J. Martocchio,et al.  EFFECTS OF FEEDBACK AND COGNITIVE PLAYFULNESS ON PERFORMANCE IN MICROCOMPUTER SOFTWARE TRAINING , 2006 .

[54]  Klaus Krippendorff,et al.  Content Analysis: An Introduction to Its Methodology , 1980 .

[55]  J Lomas,et al.  Diffusion, Dissemination, and Implementation: Who Should Do What? , 1993, Annals of the New York Academy of Sciences.

[56]  Maryam Alavi,et al.  Using Information Technology in Learning: Case Studies in Business and Management Education Programs , 2003 .

[57]  Robert G. Fichman,et al.  The Role of Aggregation in the Measurement of IT-Related Organizational Innovation , 2001, MIS Q..

[58]  Cristina Pomales-García,et al.  Excellence in Engineering Education: Views of Undergraduate Engineering Students , 2007 .

[59]  Brett J. L. Landry,et al.  Measuring Student Perceptions of Blackboard Using the Technology Acceptance Model , 2006 .

[60]  I. Ajzen The theory of planned behavior , 1991 .

[61]  Gregory J. Skulmoski,et al.  Journal of Information Technology Education the Delphi Method for Graduate Research , 2022 .

[62]  Experiential placements : dissemination and stakeholder engagement for curriculum planning action to prepare future pharmacy professionals , 2012 .

[63]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[64]  M. Lichtenstein,et al.  Disseminating the Positively Aging® Teaching Materials: Results of a Controlled Trial , 2005 .

[65]  Charles D. Barrett Understanding Attitudes and Predicting Social Behavior , 1980 .

[66]  J. B. Arbaugh,et al.  Is There an Optimal Design for On-Line MBA Courses? , 2005 .

[67]  Ted Baker,et al.  Bridging the valley of death: lessons learned from 14 years of commercialization of technology education , 2009 .

[68]  Jeffrey P. Landry,et al.  Encouraging Students to Adopt Software Engineering Methodologies: The Influence of Structured Group Labs on Beliefs and Attitudes , 2002 .