Critères de qualité d’un MOOC basés sur l’évaluation des étudiants
Barre latérale de l'article
Contenu principal de l'article
Résumé
INTRODUCTION. Au cours des dernières années, l’intérêt croissant pour l’enseignement ouvert et à distance a facilité aux étudiants du monde entier l’accès à des cours en ligne gratuits proposés par des universités de prestige en promouvant l’apprentissage. Cependant, malgré les avantages potentiels des MOOC, le taux d’abandon universitaire est très élevé et la qualité globale des enseignements est discutable, ce qui fait actuellement l’objet d’un débat intense. L’objectif de cette étude est de savoir ce que les étudiants pensent des MOOC après les avoir terminés et de détecter les améliorations qui permettront d’améliorer la qualité des cours. MÉTHODE. Sur la base de l’analyse de différents outils de mesure de la qualité des systèmes d’information, tels que le modèle de DeLone et McLean, une enquête a été conçue contenant 16 questions fermées basées sur une échelle de Likert en 5 points et une question ouverte. Un total de 309 réponses d’étudiants a été obtenu. Une méthodologie d’analyse mixte utilisant la modélisation par équations structurelles (SEM) a été utilisée pour interpréter les données quantitatives et comme méthode qualitative l’analyse de contenu a été mobilisé. RÉSULTATS. L’évaluation met en évidence l’importance des facteurs qui influent directement sur la perception de l’étudiant sur la qualité du service et de l’information fournis. L’analyse qualitative a révélé l’importance que les étudiants attachent aux contenus de type pratique. DISCUSSION. Ces résultats corroborent les conclusions d’une grande partie des travaux antérieurs identifiant la nécessité de développer et de diffuser des modèles méthodologiques plus actifs basés sur la pratique et le développement professionnel. En outre, il est nécessaire de renforcer l’efficacité et la qualité de l’information en fournissant des ressources supplémentaires pour les cours et en proposant des activités pratiques où des exemples d’application des contenus soient présentés.
Téléchargements
Renseignements sur l'article
Références
Abdi, S., Khosravi, H., Sadiq, S. y Darvishi, A. (2021). Open learner models for multi-activity educational systems. Lecture Notes in Computer Science, 11-17. https://doi.org/10.1007/978-3-030-78270-2_2
Al-Azawei, A., Parslow, P. y Lundqvist, K. (2017). The effect of Universal Design for Learning (UDL) application on e-learning acceptance: a structural equation model. International Review of Research in Open and Distributed Learning, 18(8), 54-87. https://cutt.ly/dy9Hz1w
Aldholay, A., Isaac, O., Abdullah, Z., Abdulsalam, R. y Al-Shibami, A. H. (2018). An extension of DeLone and McLean IS success model with self-efficacy. The International Journal of Information and Learning Technology, 35(4), 285-304. https://doi.org/10.1108/ijilt-11-2017-0116
Al-Fraihat, D., Joy, M., Masa’deh, R. y Sinclair, J. (2020). Evaluating e-learning systems success: an empirical study. Computers in Human Behavior, 102, 67-86. https://doi.org/10.1016/j.chb.2019.08.004
Al-Samarraie, H., Teng, B. K., Alzahrani, A. I. y Alalwan, N. (2017). E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Studies in Higher Education, 43(11), 2003-2019. https://doi.org/10.1080/03075079.2017.1298088
Aparicio, M., Bacao, F. y Oliveira, T. (2016). An e-learning theoretical framework. Educational Technology & Society, 19(1), 292-307. https://www.jstor.org/stable/jeductechsoci.19.1.292
Asociación Española de Normalización y Certificación (2012). Norma UNE 66181:2012 Gestión de la calidad. Calidad de la Formación Virtual. AENOR.
Baldomero, M., Vázquez-Cano, E. y Belando-Montoro, M. (2018). Diseño de un modelo de evaluación de la calidad de los cursos MOOC mediante lógica difusa. Revista Electrónica de Investigación Educativa, 20(4), 72-85. https://doi.org/10.24320/redie.2018.20.4.1663
Bartolomé-Pina, A. R. y Steffens, K. (2015). Are MOOCs promising learning environments? Comunicar, 22(44), 91-99. https://doi.org/10.3916/c44-2015-10
Bezerra, L. N. M. y Da Silva, M. T. (2017). A review of literature on the reasons that cause the high dropout rates in the MOOCS. Espacios, 38(5), 11-25. https://cutt.ly/qEOaUoQ
Brooker, A., Corrin, L., De Barba, P. G., Lodge, J. y Kennedy, G. (2018). A tale of two MOOCs: how student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology, 34(1), 73-87. https://doi-org.ezproxy.uned.es/10.14742/ajet.3237
Chai, Y., Lei, C. U., Hu, X. y Kwok, Y. K. (2018). WPSS. Proceedings of the Fifth Annual ACM Conference on Learning at Scale. https://doi.org/10.1145/3231644.3231687
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M. y Shi, L. (2018). Earliest predictor of dropout in MOOCs: a longitudinal study of futureLearn courses. 27th International Conference on Information Systems Development (ISD).
DeLone, W. H. y McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60-95. https://doi.org/10.1287/isre.3.1.60
DeLone, W. H. y McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9-30. https://doi.org/10.1080/07421222.2003.11045748
Dillahunt, T., Wang, Z. y Teasley, S. D. (2015). Democratizing Higher Education: exploring MOOC use among those who cannot afford a formal education. The International Review of Research in Open and Distance Learning, 15(5), 177-196. https://files.eric.ed.gov/fulltext/EJ1045991.pdf
European Foundation for Quality in E-Learning (EFQUEL) (2011). European Universities Quality in e-Learning. UNIQUe. http://bit.ly/2vNrRNG
Henderikx, M. A., Kreijns, K. y Kalz, M. (2017). Refining success and dropout in massive open online courses based on the intention-behavior gap. Distance Education, 38(3), 353-368. https://doi.org/10.1080/01587919.2017.1369006
Hernández, R., Fernández, C. y Baptista, P. (2003). Metodología de la investigación. McGraw-Hill.
Howarth, J. P., D’Alessandro, S., Johnson, L. y White, L. (2016). Learner motivation for MOOC registration and the role of MOOCs as a university “taster”. International Journal of Lifelong Education, 35(1), 74-85. https://doi-org.ezproxy.uned.es/10.1080/02601370.2015.1122667
Jacobsen, D. Y. (2019). Dropping out or dropping in? A connectivist approach to understanding participants’ strategies in an e-learning MOOC pilot. Technology, Knowledge and Learning, 24(1), 1-21. https://doi.org/10.1007/s10758-017-9298-z
Jansen, R. S., Van Leeuwen, A., Janssen, J., Conijn, R. y Kester, L. (2020). Supporting learners’ selfregulated learning in Massive Open Online Courses. Computers & Education, 146, 103771.
Kang, I. G. (2020). Heterogeneity of learners’ behavioral patterns of watching videos and completing assessments in Massive Open Online Courses (MOOCs): a latent class analysis. The International Review of Research in Open and Distributed Learning, 21(4), 222-237. https://doi.org/10.19173/irrodl.v21i4.4645
Lan, M. y Hew, K. F. (2020). Examining learning engagement in MOOCs: a self-determination theoretical perspective using mixed method. International Journal of Educational Technology in Higher Education, 17(1), 1-24. https://doi.org/10.1186/s41239-020-0179-5
Liu, M., Zou, W., Shi, Y., Pan, Z. y Li, C. (2019). What do participants think of today’s MOOCs: an updated look at the benefits and challenges of MOOCs designed for working professionals. Journal of Computing in Higher Education, 32(2), 307-329. https://doi.org/10.1007/s12528-019-09234-x
Luque, T. (2012). Técnicas de análisis de datos en investigación de mercados. Pirámide.
Marcinkowski, M. y Fonseca, F. (2015). Understanding concepts and values for the future of online education through the practice of design. En Conference 2015 Proceedings. http://hdl.handle.net/2142/73660
Maya-Jariego, I., Holgado, D., González-Tinoco, E., Castaño-Muñoz, Y. y Punie, Y. (2020). Typology of motivation and learning intentions of users in MOOCs: the MOOCKNOWLEDGE study.
Educational Technology Research and Development, 68(1), 203-224. https://doi-org.ezproxy.uned.es/10.1007/s11423-019-09682-3
Mayring, P. (2000). Qualitative content analysis. Forum Qualitative Social Research, 1, 1-10. https://doi.org/10.17169/fqs-1.2.1089
Moore, R. L. y Wang, C. (2020). Influence of learner motivational dispositions on MOOC completion. Journal of Computing in Higher Education, 1-14. https://doi.org/10.1007/s12528-020-09258-8
Morris, R. (1994). Computerized content analysis in management research: a demonstration of advantages & limitations. Journal of Management, 20(4), 903-931. https://doi.org/10.1016/0149-2063(94)90035-3
Mustafá, S. Z., Kar, A. K. y Janssen, M. F. W. H. A. (2020). Understanding the impact of digital service failure on users: integrating Tan’s failure and DeLone and McLean’s success model. International Journal of Information Management, 53, 102-119. https://doi.org/10.1016/j.ijinfomgt.2020.102119
Niu, Z., Li, W., Yan, X. y Wu, N. (2018). Exploring causes for the dropout on Massive Open Online Courses. Proceedings of ACM Turing Celebration Conference, 47-52.
Oh, E. G., Chang, Y. y Park, S. W. (2019). Design review of MOOCs: application of e-learning design principles. Journal of Computing in Higher Education, 32(3), 455-475. https://doi.org/10.1007/s12528-019-09243-w
Online Learning Consortium (s. f.). Quality Framework - OLC. http://bit.ly/2uYDotb
Osuna-Acedo, S., Marta-Lazo, C. y Frau-Meigs, D. (2018). From sMOOC to tMOOC, learning towards professional transference. ECO European Project. Comunicar, 26(55), 105-114. https://doi.org/10.3916/c55-2018-10.
Ruiz, M. A., Pardo, A. y San Martín, R. (2010). Modelos de ecuaciones estructurales. Papeles del Psicólogo, 3(1), 34-45. https://cutt.ly/Iy9c9k7
Salam, M. y Farooq, M. S. (2020). Does sociability quality of web-based collaborative learning information system influence students’ satisfaction and system usage? International Journal of Educational Technology in Higher Education, 17(1), 1-39. https://doi.org/10.1186/s41239-020-00189-z
Segovia-García, N. y Orellana, D. (2020). Calidad de diseño instruccional de cursos MOOC: principales retos. En Docencia 2.0 y 3.0. Tirant.
Segovia-García, N. y Said-Hung, E. M. (2021). Factores de satisfacción de los alumnos en e-learning en Colombia. Revista Mexicana de Investigación Educativa, 26(89), 595-621. https://cutt.ly/LbUPghi
Shah, D. (2021). The second year of the MOOC: a review of MOOC stats and trends in 2020. Class Central. https://www.classcentral.com/report/the-second-year-of-the-mooc/
Singh, A., Brooks, C., Lin, Y. y Li, W. (2021). What’s in it for the learners? Evidence from a randomized field experiment on learnersourcing questions in a MOOC. Proceedings of the Eighth ACM Conference on Learning @ Scale. https://doi.org/10.1145/3430895.3460142
Van Rosmalen, P., Kasch, J., Kalz, M., Firssova, O. y Brouns, F. (2017). Towards “MOOCs with a purpose”: crowdsourcing and analysing scalable design solutions with MOOC learners. Data Driven Approaches in Digital Education, 486-491. https://doi.org/10.1007/978-3-319-66610-5_47
Wan-Ab-Rahman, W. N., Zulzalil, H., Ishak, I. y Selamat, A. W. (2020). Quality model for Massive Open Online Course (MOOC) web content. International Journal on Advanced Science, Engineering and Information Technology, 10(1), 24. https://doi.org/10.18517/ijaseit.10.1.10192
Watts, J. (2019). Assessing an online student orientation: impacts on retention, satisfaction, and student learning. Technical Communication Quarterly, 28(3), 254-270. https://doi.org/10.1080/10572252.2019.1607905
Young, S. (2018). From disruption to innovation: thoughts on the future of MOOCs. Voprosy obrazovaniya / Educational Studies Moscow, 4, 21-43. https://doi.org/10.17323/1814-9545-2018-4-21-43
Zhu, M., Sari, A. y Lee, M. M. (2018). A systematic review of research methods and topics of the empirical MOOC literature (2014-2016). The Internet and Higher Education, 37, 31-39. https://doi.org/110.1016/j.iheduc.2018.01.002
Zou, W., Hu, X., Pan, Z., Li, C., Cai, Y. y Liu, M. (2021). Exploring the relationship between social presence and learners’ prestige in MOOC discussion forums using automated content analysis and social network analysis. Computers in Human Behavior, 115. https://doi.org/10.1016/j.chb.2020.106582