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Acceptance of learning management system: The case of secondary school teachers

Abstract

There are many ICT tools that teachers can use to support teaching and learning. In recent years, Learning Management Systems (LMSs) have been present in most higher education institutions. However, the availability of LMSs in K-12 is more recent. Furthermore, we believe that LMSs are promising even for K-12 teachers in face-to-face learning contexts because they have many educational features that can support learning with students. The goal of this study is 1) to identify the factors that influence the acceptability of the LMS by teachers, 2) to see if teachers’ ICT use influences their intention to use the LMS, and finally 3) to see if teachers’ ICT use influences their perception of the affordances of LMS educational features. The LMS in our study was introduced in a school board of more than 35,000 students and approximately 2400 teachers. To study the acceptability of the LMS, we used the Technology Acceptance Model. The results obtained from the show that the perception of usefulness is a good predictor of the intent to use the LMS. As for ICT use and the affordances of LMS educational features, the results show that they are not a good predictor of the intention to use.

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References

  • Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Ananiadou, K. and Claro M. (2009). 21st Century Skills and Competences for New Millennium Learners in OECD Countrie, OECD Education Working Papers, No. 41, OECD Publishing.

  • Angeli, C., & Valanides, N. (2009). Epistemological and methodological issues for the conceptualization, development, and assessment of ICT-TPCK: Advances in technological pedagogical content knowledge (TPCK). Computers & Education, 52(1), 154–168.

    Article  Google Scholar 

  • Barab, S., & Squire, K. (2004). Design-Based Research: Putting a Stake in the Ground. The Journal of the Learning Sciences, 13(1), 1–14.

    Article  Google Scholar 

  • Basque, J., & Lundgren-Cayrol, K. (2002). Une typologie des typologies des applications des TIC en éducation. Sciences et techniques éducatives, 9, 263–289.

    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 AIS, 8(1), 16.

    Google Scholar 

  • Bingimlas, K. A. (2009). Barriers to the Successful Integration of ICT in Teaching and Learning Environments: A Review of the Literature. Eurasia Journal of Mathematics, Science & Technology Education, 5(3), 235–245.

    Article  Google Scholar 

  • Brangier, É., Hammes-Adelé, S., & Bastien, J. M. C. (2010). Analyse critique des approches de l’acceptation des technologies : de l’utilisabilité à la symbiose humain-technologie-organisation. Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 60(2), 129–146.

    Article  Google Scholar 

  • Brown, A. L. (1992). Design experiments: Theoretical and Methodological Challenges in Creating Complex Interventions in Classroom Settings. The Journal of the Learning Sciences, 2(2), 141–178.

    Article  Google Scholar 

  • CEFRIO (2015). Usages du numérique dans les écoles québécoises - Rapport synthèse. Montréal, Canada : CEFRIO.

  • Conole, G., & Dyke, M. (2004). What are the affordances of information and communication technologies? Alternatives Journal, 12(2), 113–124.

    Google Scholar 

  • Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 1–9.

    Google Scholar 

  • Cuban, L., Kirkpatrick, H., & Peck, C. (2001). High Access and Low Use of Technologies in High School Classrooms: Explaining an Apparent Paradox. American Educational Research Journal, 38(4), 813–834.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 3, 319–340.

    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 

  • De Smet, C., Bourgonjon, J., De Wever, B., Schellens, T., & Valcke, M. (2012). Researching instructional use and the technology acceptation of learning management systems by secondary school teachers. Computers & Education, 58(2), 688–696.

    Article  Google Scholar 

  • Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1):5-8.

  • Drent, M., & Meelissen, M. (2008). Which factors obstruct or stimulate teacher educators to use ICT innovatively? Computers & Education, 51(1), 187–199.

    Article  Google Scholar 

  • Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284.

    Article  Google Scholar 

  • Février F., Jamet É., & Rouxel G. (2008). Quel outil d’évaluation de l’acceptabilité des nouvelles technologies pour des études francophones? In IHM 2008, Metz. 20 ans d’interaction homme-machine francophone : de l’interaction à la fusion entre l’humain et la technologie. New York: ACM Press, p. 199-204

  • Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. MA: Addison-Wesley.

    Google Scholar 

  • Gaver, W. W. (1991). Technology affordances. Proceedings of CHI'91 (New Orleans, April 28 - May 2, 1991). New York: ACM, 79-84.

  • Gaver, W. W. (1996). Affordances for Interaction: The Social is Material for Design. Ecological Psychology, 8(2), 111–129.

    MathSciNet  Article  Google Scholar 

  • Gibson, J. J. (1979). The Ecological Approach to Visual Perception (Classic ed.). Boston: Houghton Mifflin.

    Google Scholar 

  • Hatcher, L., & O'Rourke, N. (2013). A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling. Cary: SAS Institute.

    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, L. t., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Article  Google Scholar 

  • John, P., & Sutherland, R. (2005). Affordance, opportunity and the pedagogical implications of ICT. Educational Review, 57(4), 405–413.

    Article  Google Scholar 

  • Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2015). NMC Horizon Report: 2015 Higher (Education ed.). Austin: The New Media Consortium.

    Google Scholar 

  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information Management, 43(6), 740–755.

    Article  Google Scholar 

  • Kirschner, P. A. (2002). Can we support CSCL? Educational, social and technological affordances for learning. In P. A. Kirschner (Ed.), Three Worlds of CSCL: Can We Support CSCL (pp. 7–47). Heerlen: Open University of The Netherlands.

    Google Scholar 

  • Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling. New York: Guilford press.

    MATH  Google Scholar 

  • Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge. Contemporary Issues in Technology and Teacher Education, 9(1), 60–70.

    Google Scholar 

  • Kreijns, K., Vermeulen, M., Kirschner, P. A., Buuren, H. v., & Acker, F. V. (2013). Adopting the Integrative Model of Behaviour Prediction to explain teachers’ willingness to use ICT: a perspective for research on teachers’ ICT usage in pedagogical practices. Technology, Pedagogy and Education, 22, 55-71.

  • Law, N. (2009). Technology-Supported Pedagogical Innovations: The Challenge of Sustainability and Transferability in the Information Age. In C. Ng & P. D. Renshaw (Eds.), Reforming Learning, Education in the Asia-Pacific Region: Issues, Concerns and Prospects (pp. 319–343). Dordrecht: Springer Netherlands.

    Chapter  Google Scholar 

  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information Management, 40(3), 191–204.

    Article  Google Scholar 

  • Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2010). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies.

  • Norman, D. A. (1999). Affordance, Conventions, and Design. Interactions, 6(3), 38–43.

    Article  Google Scholar 

  • Nunally, J. C. (1978). Psychometric Theory. New York: McGraw-Hill.

    Google Scholar 

  • OECD. (2015). Students, Computers and Learning. Making the Connection (PISA). Paris: OECD Publisher.

    Book  Google Scholar 

  • Overbaugh, R., & Lu, R. (2008). The impact of a NCLB-EETT funded professional development program on teacher self-efficacy and resultant implementation. Journal of Research on Technology in Education, 41(1), 43–61.

    Article  Google Scholar 

  • Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning. Educational Technology & Society, 12(3), 150–162.

    MathSciNet  Google Scholar 

  • Plomp, T., & Nieveen, N. (2009). Educational design research: An introduction to educational design research. Enschede: SLO - Netherlands Institute for Curriculum Development.

    Google Scholar 

  • Pynoo, B., Devolder, P., Tondeur, J., Van Braak, J., Duyck, W., & Duyck, P. (2011). Predicting secondary school teachers’ acceptance and use of a digital learning environment: A cross-sectional study. Computers in Human Behavior, 27(1), 568–575.

    Article  Google Scholar 

  • Rogers, E. M. (2003). Diffusion of Innovations (5th ed.). New York: Free Press.

    Google Scholar 

  • Ross, J., & Collier, A. (2016). Complexity, Mess, and Not-Yetness. In G. Veletsianos (Ed.), Emergence and innovation in digital learning: Foundations and applications. Athabasca: AU Press.

    Google Scholar 

  • Schneckenberg, D. (2009). Understanding the real barriers to technology-enhanced innovation in higher education. Educational Research, 51(4), 411–424. https://doi.org/10.1080/00131880903354741.

    Article  Google Scholar 

  • Schumacker, R. E., & Lomax, R. G. (2012). A beginner's Guide to Structural Equation Modeling (6ed.). New York London: Routledge.

    MATH  Google Scholar 

  • Somekh, B. (2007). Pedagogy and learning with ICT: Researching the art of innovation. New York, Taylor & Francis.

  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston: Pearson Education.

    Google Scholar 

  • Tondeur, J., van Braak, J., Sang, G., Voogt, J., Fisser, P., & Ottenbreit-Leftwich, A. (2012). Preparing pre-service teachers to integrate technology in education: A synthesis of qualitative evidence. Computers & Education, 59(1), 134–144.

    Article  Google Scholar 

  • UNESCO (2008). UNESCO's ICT Competency Standards for Teachers. Retrieved from http://cst.unesco-ci.org/sites/projects/cst/default.aspx. Accessed 25 June 2015.

  • Van Raaij, E. M., & Schepers, J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3), 838–852.

    Article  Google Scholar 

  • Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204.

    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, 425-478.

  • Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5–23.

    Article  Google Scholar 

  • Wastiau, P., Blamire, R., Kearney, C., Quittre, V., Van de Gaer, E., & Monseur, C. (2013). The Use of ICT in Education: a survey of schools in Europe. European Journal of Education, 48(1), 11–27.

    Article  Google Scholar 

  • Wright, C. R., Lopes, V., Montgomerie, C. T., Reju, S., & Schmoller, S. (2014). Selecting a Learning Management System: Advice from an Academic Perspective. Retrieved from http://www.educause.edu/ero/article/selecting-learning-management-system-advice-academic-perspective. Accessed 14 Sept 2015.

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Correspondence to Alain Stockless.

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Stockless, A. Acceptance of learning management system: The case of secondary school teachers. Educ Inf Technol 23, 1101–1121 (2018). https://doi.org/10.1007/s10639-017-9654-6

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  • DOI: https://doi.org/10.1007/s10639-017-9654-6

Keywords

  • Learning management system (LMS)
  • Technology acceptance
  • Teacher
  • Secondary schools
  • Information and communication technologies (ICTs)