Abstracts
Résumé
La formation à distance (FAD) a été implantée « à marche forcée » et de façon massive dans les universités au cours de la pandémie. Cet article montre que des perceptions sur les instruments mobilisés en FAD ont été passablement affectées. En effet, si les enseignants et enseignantes semblent se reconnaître une plus grande compétence à mettre en pratique la FAD, il reste que leur acceptation des technologies et la valeur accordée à leur usage, notamment, se sont affaissées à l’occasion du retour en présentiel. Si cela ne se traduit pas par un rejet pur et simple du distanciel, un rééquilibrage semble toutefois demandé par les enseignants et enseignantes.
Mots-clés :
- Formation à distance,
- acceptation des technologies,
- valeur accordée à la tâche,
- sentiment d’autoefficacité,
- résistance au changement,
- technologies éducatives,
- enseignement universitaire
Abstract
By necessity, distance learning (DL) was implemented broadly and rapidly in universities during the pandemic crisis. This article shows that this had a significant impact on how distance-learning tools were perceived. Although teachers now feel somewhat more competent in implementing DL, their acceptance of DL technology and the value they place on its use have subsided with the return to the classroom. While this does not mean that teachers are simply rejecting distance learning, they seem to be seeking a new balance.
Keywords:
- Distance education,
- technology acceptance,
- task value,
- self-efficacy,
- resistance to change,
- educational technologies,
- university teaching
Appendices
Références
- Akdeni̇z, R. K. et Konakli, T. (2022). The emergence, reasons and results of resistance to change in teachers. International Journal on Lifelong Education and Leadership, 8(1), 49-67. https://doi.org/10.25233/ijlel.1107137
- Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
- Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M. et Abrami, P. C. (2014). A Meta-Analysis of Blended Learning and Technology Use in Higher Education: From the General to the Applied. Journal of Computing in Higher Education, 26(1), 87-122. https://doi.org/10.1007/s12528-013-9077-3
- Chen, J.-L. (2011). the effects of education compatibility and technological expectancy on E-learning acceptance. Computers & Education, 57(2), 1501-1511. https://doi.org/10.1016/j.compedu.2011.02.009
- Cohen, L., Manion, L. et Morrison, K. (2018). Research methods in education (8e éd.). Routledge.
- Coutinho, S. A. et Neuman, G. (2008). A model of metacognition, achievement goal orientation, learning style and self-efficacy. Learning Environments Research, 11(2), 131‑151. https://doi.org/10.1007/s10984-008-9042-7
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319‑340. https://doi.org/10.2307/249008
- Davis, F. D., Bagozzi, R. P. et Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982‑1003. https://doi.org/10.1287/mnsc.35.8.982
- Demidenko, E. (2016). The p-value you can’t buy. The American Statistician, 70(1), 33-38. https://doi.org/10/f8hvc7
- Eccles, J. S. et Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109-132. https://doi.org/10/dhmnvv
- Flake, J. K., Barron, K. E., Hulleman, C., McCoach, B. D. et Welsh, M. E. (2015). Measuring cost: The forgotten component of expectancy-value theory. Contemporary Educational Psychology, 41, 232-244. https://doi.org/10.1016/j.cedpsych.2015.03.002
- Gratz, E. et Looney, L. (2020). Faculty resistance to change: An examination of motivators and barriers to teaching online in Higher Education. International Journal of Online Pedagogy and Course Design, 10(1), 1-14. https://doi.org/10/grmmbg
- Jaoua, F., Almurad, H. M., Elshaer, I. A. et Mohamed, E. S. (2022). E-learning success model in the context of COVID-19 pandemic in higher educational institutions. International Journal of Environmental Research and Public Health, 19(5), article 2865. https://doi.org/10.3390/ijerph19052865
- Means, B., Toyama, Y., Murphy, R. et Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1-47. https://doi.org/10/gnj6x2
- Michelot, F. (2022). Obstacles et opportunités stratégiques de l’avenir de la formation à distance. Une contribution à la planification stratégique de l’Université de Moncton. Distances et médiations des savoirs, (39). https://doi.org/10.4000/dms.8359
- Michelot, F. et Poellhuber, B. (2022, 9 mai). Développer l’autoefficacité des enseignant·es en formation à distance, une stratégie payante pour l’enseignement présentiel, hybride et comodal [résumé de communication]. Congrès 2022 de l’ACFAS – Colloque 521, Montréal, Canada. http://acfas.ca/...
- Michelot, F., Poellhuber, B., Bérubé, B. et Béland, S. (2021). Retour d’expérience sur l’évaluation d’une formation des enseignants à la FAD dans le cadre de la crise de la COVID-19. Revue internationale des technologies en pédagogie universitaire, 18(1), 21‑31. https://doi.org/10.18162/ritpu-2021-v18n1-04
- Michelot, F., Poellhuber, B., Charette, E. et Gazerani, F. (2021). Accompagner les enseignant·es dans le développement de leurs compétences en FAD. Dans P. Plante, M. Alexandre, C. Papi, A. Stockless et R. Grégoire (dir.), Actes du colloque ROC 2021 – Solidarités numériques en éducation : une culture en émergence (p. 179-182). https://rlibre.teluq.ca/2590
- Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of Applied Psychology, 88(4), 680-693. https://doi.org/10.1037/0021-9010.88.4.680
- Pfleging, A. et Cunningham, K. E. (2021). Efficacy in the face of adversity. Educational Leadership, 79(3), 71‑75. http://ascd.org/...
- Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667-686. https://doi.org/10.1037/0022-0663.95.4.667
- Pintrich, P. R. et de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33‑40. https://doi.org/10.1037/0022-0663.82.1.33
- Poellhuber, B. et Michelot, F. (2019). L’engagement et les stratégies d’autorégulation des apprenants adultes en e-Formation. Dans A. Jézégou (dir.), Traité de la e-formation des adultes (p. 233-262). De Boeck Supérieur. http://hdl.handle.net/1866/24894
- Ranellucci, J., Rosenberg, J. M. et Poitras, E. G. (2020). Exploring pre-service teachers’ use of technology: The Technology Acceptance Model and expectancy–value theory. Journal of Computer Assisted Learning, 36(6), 810-824. https://doi.org/10.1111/jcal.12459
- Talsma, K., Schüz, B., Schwarzer, R. et Norris, K. (2018). I believe, therefore I achieve (and vice versa): A meta-analytic cross-lagged panel analysis of self-efficacy and academic performance. Learning and Individual Differences, 61(2018), 136‑150. https://doi.org/10.1016/j.lindif.2017.11.015
- Tarhini, A., Masa’deh, R., Al-Busaidi, K. A., Mohammed, A. B. et Maqableh, M. (2017). Factors influencing students’ adoption of E-learning: A structural equation modeling approach. Journal of International Education in Business, 10(2), 164-182. https://doi.org/10.1108/JIEB-09-2016-0032
- Vallerand, R. J. (1989). Vers une méthodologie de validation trans-culturelle de questionnaires psychologiques : implications pour la recherche en langue française. Psychologie canadienne, 30(4), 662‑680. https://doi.org/10.1037/h0079856
- Venkatesh, V. et Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273‑315. https://doi.org/10/bpkdfj
- Vo, H. M., Zhu, C. et Diep, N. A. (2017). The effect of blended learning on student performance at course-level in higher education: A meta-analysis. Studies in Educational Evaluation, 53, 17‑28. https://doi.org/10.1016/j.stueduc.2017.01.002
- Wigfield, A. et Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81. https://doi.org/10.1006/ceps.1999.1015
- Xian, X. (2019). Empirical investigation of E-learning adoption of university teachers: A PLS-SEM approach. Dans S. K. S. Cheung, J. Jiao, L.-K. Lee, X. Zhang, K. C. Li et Z. Zhan (dir.), Technology in education: Pedagogical innovations (p. 169-178). Springer. https://doi.org/10/gr5z9c
- Zhao, S. et Song, J. (2021). What kind of support do teachers really need in a blended learning context? Australasian Journal of Educational Technology, 37(4), 116-129. https://doi.org/10.14742/ajet.6592