Abstract
This study investigates technology acceptance over time of two specific technologies in a university setting, namely interactive quizzes and screen sharing. This topic is investigated in the framework of the Technology Acceptance Model (TAM) that includes the perceived usefulness, perceived ease of use and behavioural intention as main concepts. This study also add experience or actual use to this framework. Although previous research investigated the relation between technology acceptance and actual use, no longitudinal study of TAM variables has been previously conducted in the context of interactive quizzes and screen sharing from a student perspective. This study aims to meet this research gap and investigated students’ expectations towards educational technology at the start of the project and students’ experiences with educational technology throughout the academic year. Results reveal that students started out with a positive predisposition to the usefulness, ease of use, and behavioural intention of using educational technology in university settings. The TAM perceptions after experiencing the technology were significantly higher than before using the technology. This was the case for both interactive quizzes and screen sharing technology. The longitudinal results even counter a novelty effect. Although educational reform is also related to organizational processes, students’ acceptance is critical to make sure that technologies might contribute to improve learning and teaching.






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Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453–474.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25, 351–370.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28, 229–254.
Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43(6), 706–717.
Cheng, E. W. L. (2018). Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM ). Educational Technology Research and Development., 67, 21–37. https://doi.org/10.1007/s11423-018-9598-6.
Chung, C. W., Lee, C. C., & Liu, C. C. (2013). Investigating face-to-face peer interaction patterns in a collaborative web discovery task: The benefits of a shared display. Journal of Computer Assisted Learning, 29(2), 188–206. https://doi.org/10.1111/j.1365-2729.2012.00493.x.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(1), 319–340.
Dobbins, C., & Denton, P. (2017). MyWallMate: An investigation into the use of Mobile Technology in Enhancing Student Engagement. TechTrends, 61(6), 541–549. https://doi.org/10.1007/s11528-017-0188-y.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: And introduction to theory and research. MA: Addsion-Wesley Reading.
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059.
Fullan, M. (2007). The new meaning of educational change (4th ed.). New York: Teachers College Press.
Griffin, P., Care, E., & McGaw, B. (2011). The changing role of education and schools. In P. Griffin, B. McGaw, & E. Care (Eds.), Assessment and teaching 21st century skills. Heidelberg: Springer.
Hattie, J. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement. Taylor & Francis.
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.
Islam, A. K. M. N. (2013). Investigating e-learning system usage outcomes in the university context. Computers and Education, 69, 387–399. https://doi.org/10.1016/j.compedu.2013.07.037.
Jaffee, D. (1998). Institutionalized resistance to asychronous learning networks. Journal of Asychronous Learning Networks, 2(2), 21–32.
Jahnke, I. (2016). Digital didactical designs: Teaching and learning in CrossActionSpaces. Routledge.
Kay, R. H., & LeSage, A. (2009). A strategic assessment of audience response systems used in higher education. Australasian Journal of Educational Technology, 25(2), 235–249. https://doi.org/10.1016/j.compedu.2009.05.001.
Kerne, A., Koh, E., Smith, S., Choi, H., Graeber, R., & Webb, A. (2007). Promoting emergence in information discovery by representing collections with composition. In Proceedings of the 6th ACM SIGCHI conference on Creativity & cognition - C&C ‘07 (p. 117). New York, New York, USA: ACM Press. https://doi.org/10.1145/1254960.1254977.
Klem, A. M., & Connell, J. P. (2004). Relationships matter: Linking teacher support to student engagement and achievement. Journal of School Health, 74(7), 262–273. https://doi.org/10.1111/j.1746-1561.2004.tb08283.x.
Lantz, M. E., & Stawiski, A. (2014). Effectiveness of clickers: Effect of feedback and the timing of questions on learning. Computers in Human Behavior, 31, 280–286. https://doi.org/10.1016/J.CHB.2013.10.009.
Laurillard, D. (2002). Rethinking University teaching. A conversational framework for the effective use of learning technologies. London: Routledge.
Lavrakas, P. J. (2008). Encyclopedia of survey research methods. Thousand Oaks: Sage Publications, Inc.. https://doi.org/10.4135/9781412963947.
Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204. https://doi.org/10.1016/S0378-7206(01)00143-4.
Linn, M. C., & Eylon, B.-S. (2011). Science learning and instruction. Taking advantage of technology to promote knowledge integration. New York: Routledge.
Lust, G., Elen, J., & Clarebout, G. (2013). Students’ tool-use within a web enhanced course: Explanatory mechanisms of students’ tool-use pattern. Computers in Human Behavior, 29(5), 2013–2021. https://doi.org/10.1016/j.chb.2013.03.014.
Mayer, R. E., Stull, A., DeLeeuw, K., Almeroth, K., Bimber, B., Chun, D., Bulger, M., Campbell, J., Knight, A., & Zhang, H. (2009). Clickers in college classrooms: Fostering learning with questioning methods in large lecture classes. Contemporary Educational Psychology, 34(1), 51–57. https://doi.org/10.1016/j.cedpsych.2008.04.002.
Nulty, D. D. (2008). The adequacy of response rates to online and paper surveys: What can be done? Assessment and Evaluation in Higher Education, 33(3), 301–314. https://doi.org/10.1080/02602930701293231.
Pegrum, M. (2015). Mobile learning: What is it and what are its possibilities (p. 142). Teaching and Digital Technologies: Big Issues and Critical Questions.
Raes A., Vens C., Vanneste P., Depaepe F. (2018). Teaching for versus through problem solving: Impact on teaching and learning. In: Rethinking learning in the digital age: Making the learning sciences count: vol. 1 (408-415). Presented at the International Conference of the Learning Sciences (ICLS) 2018, London, UK. ISBN: 978-1-7324672-0-0.
Raes, A., Vanderhoven, E., & Schellens, T. (2013). Increasing anonymity in peer assessment by using classroom response technology within face-to-face higher education. Studies in Higher Education, 40(1), 178–193. https://doi.org/10.1080/03075079.2013.823930.
Raes, A., Vanneste, P., Windey, I., Van den Noortgate, W. & Depaepe, F. (2019). Monitoring student engagement through multimodal analytics to improve learning across spaces. To be presented at the Research Community W000519N – First meeting Workshop Leuven, October 16-18, 2019.
Roschelle, J., Rafanan, K., Bhanot, R., Estrella, G., Penuel, B., Nussbaum, M., & Claro, S. (2010). Scaffolding group explanation and feedback with handheld technology: Impact on students’ mathematics learning. Educational Technology Research and Development, 58(4), 399–419.
Scott, S. D., Grant, K. D., & Mandryk, R. L. (2003). System guidelines for co-located, collaborative work on a tabletop display. In ECSCW 2003 (pp. 159–178). Dordrecht: Springer Netherlands. https://doi.org/10.1007/978-94-010-0068-0_9.
Sheeran, P. (2002). Intention—Behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003.
Spanjers, I. A. E., Könings, K. D., Leppink, J., Verstegen, D. M. L., de Jong, N., Czabanowska, K., & van Merriënboer, J. J. G. (2015). The promised land of blended learning: Quizzes as a moderator. Educational Research Review, 15, 59–74. https://doi.org/10.1016/j.edurev.2015.05.001.
Stahl, G., Koschmann, T., & Suthers, D. D. (2006). Computer-supported collaborative learning: An historical perspective. Cambridge Handbook of the Learning Sciences, 409–426. https://doi.org/10.1017/CBO9781139519526.029.
Straub, E. T. (2017). Understanding Technology Adoption: Theory and Future Directions for Informal Learning. Review of Educational Research 79 (2):625-649
Šumak, B., Hericko, M., & Pušnik, M. (2011). A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types. Computers in Human Behavior, 27, 2067–2077. https://doi.org/10.1016/j.chb.2011.08.005.
Sung, Y.-T., Yang, J.-M., & Lee, H.-Y. (2017). The effects of Mobile-computer-supported collaborative learning: Meta-analysis and critical synthesis. Review of Educational Research, 87(4), 768–805. https://doi.org/10.3102/0034654317704307.
Teo, T. (2009). Is there an attitude problem? Reconsidering the role of attitude in the TAM. British Journal of Educational Technology, 40(6), 1139–1141. https://doi.org/10.1111/j.1467-8535.2008.00913.x.
Turner, M., Kitchenham, B., Brereton, P., Charters, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 463–479. https://doi.org/10.1016/j.infsof.2009.11.005.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926.
Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision making processes. Organizational Behavior and Human Decision Processes, 83(1), 33–60.
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User acceptance enablers in individual decision making about technology: Toward an integrated model. Decision Sciences, 33(2), 297–316.
Yang, J., Schneller, C., & Roche, S. (2015). The Role of Higher Education in Promoting Lifelong Learning The Role of Higher Education in Promoting Lifelong Learning. Retrieved January 2019 from http://unesdoc.unesco.org/images/0023/002335/233592e.pdf
Yun, G. W., & Trumbo, C. W. (2006). Comparative response to a survey executed by post, E-mail, & web form. Journal of Computer-Mediated Communication, 6(1). https://doi.org/10.1111/j.1083-6101.2000.tb00112.x.
Zurita, G., & Nussbaum, M. (2007). A conceptual framework based on activity theory for mobile CSCL. British Journal of Educational Technology, 38(2), 211–235. https://doi.org/10.1111/j.1467-8535.2006.00580.x.
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This study was carried out within imec’s Smart Education research programme, with support from the Flemish government and funding from KU Leuven University. No specific grant number can be mentioned.
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The authors of this manuscript, i.e. Annelies Raes and Fien Depaepe, declare no to have any conflict of interest.
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This research involves human participants, but this research project has been reviewed and approved by the Social and Societal Ethics Committee (https://ppw.kuleuven.be/home/onderzoek/SMEC). Informed consent was obtained from all individual participants included in the study.
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Raes, A., Depaepe, F. A longitudinal study to understand students’ acceptance of technological reform. When experiences exceed expectations. Educ Inf Technol 25, 533–552 (2020). https://doi.org/10.1007/s10639-019-09975-3
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DOI: https://doi.org/10.1007/s10639-019-09975-3