Skip to main content

Advertisement

SpringerLink
Log in

A longitudinal study to understand students’ acceptance of technological reform. When experiences exceed expectations

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • 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.

    Article  Google Scholar 

  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25, 351–370.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Burton-Jones, A., & Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model. Information & Management, 43(6), 706–717.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(1), 319–340.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: And introduction to theory and research. MA: Addsion-Wesley Reading.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Fullan, M. (2007). The new meaning of educational change (4th ed.). New York: Teachers College Press.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Jaffee, D. (1998). Institutionalized resistance to asychronous learning networks. Journal of Asychronous Learning Networks, 2(2), 21–32.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Laurillard, D. (2002). Rethinking University teaching. A conversational framework for the effective use of learning technologies. London: Routledge.

    Book  Google Scholar 

  • Lavrakas, P. J. (2008). Encyclopedia of survey research methods. Thousand Oaks: Sage Publications, Inc.. https://doi.org/10.4135/9781412963947.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Linn, M. C., & Eylon, B.-S. (2011). Science learning and instruction. Taking advantage of technology to promote knowledge integration. New York: Routledge.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Pegrum, M. (2015). Mobile learning: What is it and what are its possibilities (p. 142). Teaching and Digital Technologies: Big Issues and Critical Questions.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

Download references

Funding

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.

Author information

Authors and Affiliations

  1. Faculty of Psychology and Educational Sciences, Centre for Instructional Psychology and Technology, KU Leuven Campus Kulak Kortrijk, Etienne Sabbelaan 51, 8500, Kortrijk, Belgium

    Annelies Raes & Fien Depaepe

  2. ITEC, imec research group at KU Leuven, imec, Kapeldreef 75, 3001, Leuven, Belgium

    Annelies Raes & Fien Depaepe

Authors
  1. Annelies Raes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fien Depaepe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Annelies Raes.

Ethics declarations

Conflict of interest

The authors of this manuscript, i.e. Annelies Raes and Fien Depaepe, declare no to have any conflict of interest.

Ethical approval & informed consent

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.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-019-09975-3

Keywords

Search

Navigation