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Instructional Technology Integration Models and Frameworks: Diffusion, Competencies, Attitudes, and Dispositions

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Second Handbook of Information Technology in Primary and Secondary Education

Part of the book series: Springer International Handbooks of Education ((SIHE))

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Abstract

Models and frameworks help us better understand complex ideas and processes by providing a simplified explication of a concept, phenomenon, relationship, structure, system, or aspect of the real-world that allows us to focus on essential aspects of that which is being modeled. Relative to classroom technology integration, models can be useful in helping us understand and explain how technology integration occurs, allow us to better make decisions about how to effectively utilize technology resources, and provide insights that support development of strategies to more effectively and efficiently promote the kinds of pedagogical reforms that reformers hope to see in schools. The purpose of this chapter is to provide an overview of current models and frameworks that inform teacher adoption of technologies that support the integration of technology into student learning experiences in K-12 school settings, and to link them to theories of diffusion, adoption and change that underpin them.

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References

  • Agyei, D. D., & Voogt, J. M. (2011). Exploring the potential of the will, skill, tool model in Ghana: Predicting prospective and practicing teachers’ use of technology. Computers & Education, 56, 91–100.

    Article  Google Scholar 

  • Ajzen, I. (2006). Constructing a TpB questionnaire: Conceptual and methodological considerations. Retrieved 1 Feb 2017 from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.601.956&rep=rep1&type=pdf.

  • Ajzen, I. (2012). Theory of planned behavior. In P. Van Lange, A. Kruglanski, & E. Higgens (Eds.), The handbook of theories of social psychology (Vol. 1, pp. 438–454). Thousand Oaks: Sage.

    Google Scholar 

  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 3.

    Article  Google Scholar 

  • Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice Hall.

    Google Scholar 

  • Bauer, J., & Kenton, J. (2005). Toward technology integration in the schools: Why it isn’t happening. Journal of Technology and Teacher Education, 13(4), 519.

    Google Scholar 

  • Benbasat, I., & Barki, H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 211–218.

    Article  Google Scholar 

  • Brinkerhoff, J. (2006). Effects of a long-duration, professional development academy on technology skills, computer self-efficacy, and technology integration beliefs and practices. Journal of Research on Technology in Education, 39(1), 22–43.

    Article  Google Scholar 

  • Casey, T., & Wilson-Evered, E. (2012). Predicting uptake of technology innovations in online family dispute resolution services: An application and extension of the UTAUT. Computers in Human Behavior, 28(6), 2034–2045.

    Article  Google Scholar 

  • Damanpour, F. (1996). Organizational complexity and innovation: Developing and testing multiple contingency models. Management Science, 42(5), 693–716.

    Article  Google Scholar 

  • Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38, 475–487.

    Article  Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  • Ertmer, P. A. (2005). Teacher pedagogical beliefs: The final frontier in our quest for technology integration? Educational Technology Research and Development, 53(4), 25–39.

    Article  Google Scholar 

  • Ertmer, P. A., Evenbeck, E., Cennamo, K. S., & Lehman, J. D. (1994). Enhancing self-efficacy for computer technologies through the use of positive classroom experiences. Educational Technology Research and Development, 42(3), 45–62.

    Article  Google Scholar 

  • Fishbein, M. (1965). A consideration of beliefs, attitudes, and their relationship. In I. Steiner & M. Fishbein (Eds.), Current studies in social psychology (pp. 107–120). New York: Holt, Rinehart and Winston.

    Google Scholar 

  • Foulger, T. S., Waker, M. L., Burke, D., Hansen, R., Kim Williams, M., & Slykhuis, D. A. (2013). Innovators in teacher education: Diffusing mobile technologies in teacher preparation curriculum. Journal of Digital Learning in Teacher Education, 30(1), 21–29.

    Article  Google Scholar 

  • Fuller, F. F. (1969). Concerns of teachers: A developmental conceptualization. American Educational Research Journal, 6(2), 207–226.

    Article  Google Scholar 

  • George, A., Hall, G., & Stiegelbauer, S. (2006). Measuring implementation in schools: The stages of concern questionnaire. Austin: SEDL.

    Google Scholar 

  • Hall, G. E. (1974). The concerns-based adoption model: A developmental conceptualization of the adoption process within educational institutions. Paper presented at the Annual Meeting of the American Educational Research Association, Chicago, IL.

    Google Scholar 

  • Hall, G. E. (2010). Technology’s Achilles heel: Achieving high-quality implementation. Journal of Research on Technology in Education, 42(3), 231–253.

    Article  Google Scholar 

  • Hall, G., Loucks, S., Rutherford, W., & Newlove, B. (1975). Levels of use of the innovation: A framework for analyzing innovation adoption. Journal of Teacher Education, 26(1), 52–56.

    Article  Google Scholar 

  • Hall, G. E., Dirksen, D. J., George, A. A. (2006). Measuring implementation in schools: Levels of use. Retrieved 18 Mar 2017 from http://www.sedl.org/cbam/lou_manual_201410.pdf.

  • Hancock, R., Knezek, G., & Christensen, R. (2007). Cross-validating measures of technology integration: A first step toward examining potential relationships between technology integration and student achievement. Journal of Computing in Teacher Education, 24(1), 15–21.

    Google Scholar 

  • Hao, Y., & Lee, K. S. (2015). Teachers’ concern about integrating Web 2.0 technologies and its relationship with teacher characteristics. Computers in Human Behavior, 48, 1–8.

    Article  Google Scholar 

  • Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research and Development, 55(3), 223–252.

    Article  Google Scholar 

  • Hu, P. J. H., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school teachers: A longitudinal study. Information Management, 41(2), 227–241.

    Article  Google Scholar 

  • Hutchison, A., & Reinking, D. (2011). Teachers’ perceptions of integrating information and communication technologies into literacy instruction: A national survey in the United States. Reading Research Quarterly, 46(4), 312–333.

    Google Scholar 

  • Kim, C., Kim, M. K., Lee, C., Spector, J. M., & DeMeester, K. (2013). Teacher beliefs and technology integration. Teaching and Teacher Education, 29, 76–85.

    Article  Google Scholar 

  • Knezek, G., & Christensen, R. (2016). Extending the will, skill, tool model of technology integration: Adding pedagogy as a new model construct. Journal of Computing in Higher Education, 28(3), 307–325.

    Article  Google Scholar 

  • Knezek, G., Christensen, R., Miyashita, K., & Ropp, M. (2000). Instruments for assessing educator progress in technology integration. Denton: Institute for the Integration of Technology into Teaching and Learning (IITTL).

    Google Scholar 

  • Lankshear, C., & Knobel, M. (2007). Sampling “the new” in new literacies. In C. Lankshear & M. Knobel (Eds.), A new literacies sampler (pp. 1–24). New York: Peter Lang.

    Google Scholar 

  • Lent, R., Brown, S., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45, 79–121.

    Article  Google Scholar 

  • Lent, R. W., Brown, S. D., & Hackett, G. (2002). Social cognitive career theory. In D. Brown (Ed.), Career choice and development (pp. 255–311). San Francisco: Jossey-Bass.

    Google Scholar 

  • Liaw, S. S., & Huang, H. M. (2003). An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, 19(6), 751–765.

    Article  Google Scholar 

  • Loucks, S.F., & Hall, G.E. (1979). Implementing innovations in schools: A concerns-based approach. Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.

    Google Scholar 

  • Ma, W. W. K., Andersson, R., & Streith, K. O. (2005). Examining user acceptance of computer technology: An empirical study of student teachers. Journal of Computer Assisted Learning, 21(6), 387–395.

    Article  Google Scholar 

  • Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017.

    Article  Google Scholar 

  • Moersch, C. (1995). Levels of technology implementation (LoTi): A framework for measuring classroom technology use. Learning and Leading with Technology, 23, 40–40.

    Google Scholar 

  • Niederhauser, D. S., & Perkmen, S. (2010). Beyond self-efficacy: Measuring pre-service teachers’ instructional technology outcome expectations. Computers in Human Behavior, 26(4), 436–442.

    Article  Google Scholar 

  • Niederhauser, D. S., & Perkmen, S. (2008). Validation of the intrapersonal technology integration scale: Assessing the influence of intrapersonal factors that influence technology integration. Computers in the Schools, 25(1–2), 98–111.

    Google Scholar 

  • Niederhauser, D. S., & Stoddart, T. (2001). Teachers’ instructional perspectives and use of educational software. Teaching and Teacher Education, 17(1), 15–31.

    Article  Google Scholar 

  • Pajares. (2002). Overview of social cognitive theory and of self-efficacy. Retrieved 3 Feb 2017 from http://www.uky.edu/~eushe2/Pajares/eff.html.

  • Petko, D. (2012). Teachers’ pedagogical beliefs and their use of digital media in classrooms: Sharpening the focus of the ‘will, skill, tool’ model and integrating teachers’ constructivist orientations. Computers & Education, 58(4), 1351–1359.

    Article  Google Scholar 

  • Puentedura, R. R. (2012). The SAMR model: Background and exemplars. Retrieved 8 Mar 2017 from http://www.hippasus.com/rrpweblog/archives/2012/08/23/SAMR_BackgroundExemplars.pdf.

  • Purcell, K., Heaps, A., Buchanan, J., Friedrich, L. (2013). How teachers are using technology at home and in their classrooms. Pew Internet & American Life Project. Retrieved 23 Jan 2017 from http://www.pewinternet.org/∼/media//Files/Reports/2013/PIP_TeachersandTechnologywithmethodology_PDF.pdf.

  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Simon & Schuster.

    Google Scholar 

  • Rosen, L. D., & Weil, M. M. (1995). Computer availability, computer experience and technophobia among public school teachers. Computers in Human Behavior, 11(1), 9–31.

    Article  Google Scholar 

  • Sandholtz, J. H., Ringstaff, C., & Dwyer, D. C. (1992). Teaching in high-tech environments: Classroom management revisited. Journal of Educational Computing Research, 8(4), 479–505.

    Article  Google Scholar 

  • Sandholtz, J. H., Ringstaff, C., & Dwyer, D. C. (1997). Teaching with technology: Creating student-centered classrooms. New York: Teachers College Press.

    Google Scholar 

  • Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK) the development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123–149.

    Google Scholar 

  • Schunk, D. H. (2001). Learning theories: An educational perspective (3rd ed.). Upper Saddle River: Prentice-Hall/Merrill.

    Google Scholar 

  • Sheingold, K. (1991). Restructuring for learning with technology: The potential for synergy. Phi Delta Kappan, 73(1), 17–27.

    Google Scholar 

  • Sherry, L. (1998). An integrated technology adoption and diffusion model. International Journal of Educational Telecommunications, 4(2), 113–145.

    Google Scholar 

  • Smarkola, C. (2008). Efficacy of a planned behavior model: Beliefs that contribute to computer usage intentions of student teachers and experienced teachers. Computers in Human Behavior, 24(3), 1196–1215.

    Article  Google Scholar 

  • Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of Educational Research, 79(2), 625–649.

    Article  Google Scholar 

  • Teo, T. (2015). Comparing pre-service and in-service teachers’ acceptance of technology: Assessment of measurement invariance and latent mean differences. Computers & Education, 83, 22–31.

    Article  Google Scholar 

  • Teo, T., Lee, C. B., & Chai, C. S. (2008). Understanding pre-service teachers’ computer attitudes: Applying and extending the technology acceptance model. Journal of Computer Assisted Learning, 24(2), 128–143.

    Article  Google Scholar 

  • Velazquez, C. M. (2007). Testing predictive models of technology integration in Mexico and the United States. Computers in the Schools, 24(3–4), 153–173.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425–478.

    Article  Google Scholar 

  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

    Google Scholar 

  • Wang, S. K., Hsu, H. Y., Campbell, T., Coster, D., & Longhurst, M. (2014). An investigation of middle school science teachers and students use of technology inside and outside of classrooms: Considering whether digital natives are more technology savvy than their teachers. Educational Technology Research and Development, 62(6), 637–662.

    Article  Google Scholar 

  • Webb, M., & Cox, M. (2004). A review of pedagogy related to information and communications technology. Technology, Pedagogy and Education, 13(3), 235–286.

    Article  Google Scholar 

  • Wesley, M. T., & Franks, M. E. (1996). Advanced adoption of computer technology in the classroom and teachers’ participation in voluntary innovation adoption activities. Paper presented at the annual meeting of the Mid-South Educational Research Association, Tuscaloosa, AL.

    Google Scholar 

  • Zacharia, Z. (2003). Beliefs, attitudes, and intentions of science teachers regarding the educational use of computer simulations and inquiry-based experiments in physics. Journal of Research in Science Teaching, 40(8), 792–823.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Education and Human Services, West Virginia University, Morgantown, WV, USA

    Dale S. Niederhauser

  2. Department of Curriculum & Instruction/Literacy Studies, College of Education and Human Services, West Virginia University, Morgantown, WV, USA

    Denise L. Lindstrom

Authors
  1. Dale S. Niederhauser
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  2. Denise L. Lindstrom
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Correspondence to Dale S. Niederhauser .

Editor information

Editors and Affiliations

  1. University of Amsterdam , Amsterdam, The Netherlands

    Joke Voogt

  2. University of North Texas , Denton, Texas, USA

    Gerald Knezek

  3. University of North Texas , Denton, Texas, USA

    Rhonda Christensen

  4. University of Otago , Dunedin, New Zealand

    Kwok-Wing Lai

Section Editor information

  1. University of North Texas, Denton, Texas, USA

    Gerald Knezek

  2. University of North Texas, Denton, Texas, USA

    Rhonda Christensen

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Niederhauser, D.S., Lindstrom, D.L. (2018). Instructional Technology Integration Models and Frameworks: Diffusion, Competencies, Attitudes, and Dispositions. In: Voogt, J., Knezek, G., Christensen, R., Lai, KW. (eds) Second Handbook of Information Technology in Primary and Secondary Education . Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-319-53803-7_23-2

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  • DOI: https://doi.org/10.1007/978-3-319-53803-7_23-2

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  • Print ISBN: 978-3-319-53803-7

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Chapter history

  1. Latest

    Instructional Technology Integration Models and Frameworks: Diffusion, Competencies, Attitudes, and Dispositions
    Published:
    21 February 2018

    DOI: https://doi.org/10.1007/978-3-319-53803-7_23-2

  2. Original

    Instructional Technology Integration Models and Frameworks: Diffusion, Competencies, Attitudes, and Dispositions
    Published:
    29 December 2017

    DOI: https://doi.org/10.1007/978-3-319-53803-7_23-1

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