An exploration of institutional and personal barriers to online academic engagement at a Brazilian university
DOI:
https://doi.org/10.5944/educxx1.36095Keywords:
online learning, student engagement, facilitators and barriers to engagement, higher educationAbstract
The recent global pandemic has raised institutional awareness around the world concerning the importance of having high quality online learning options for students. Learner engagement is often correlated with quality outcomes such as student academic success and student satisfaction. Learner engagement is commonly thought of as having three important dimensions: affective engagement, behavioral engagement, and cognitive engagement (ACE framework). Engagement is also enabled or limited by facilitators/barriers. Three important categories of facilitators/barriers are learner characteristics, personal environment, and course environment. Elements in each of these three areas enable or are barriers to students fully engaging in a course. This research explored what the barriers are to students fully engaging in their online courses at a Brazilian university to determine which areas will be most productive for the university program administrators and designers to focus on increase student academic engagement. A survey was applied to students from the Brazilian university under graduation online programs. It included items related to engagement facilitators barriers in the three areas described in the ACE framework and received 429 valid responses. The affective and behavioral dimensions were perceived by students as the lower engagement indicators in the ACE framework. Among facilitators or barriers for engagement, the ones under the course environment category were predominantly perceived as barriers, while learner characteristics and student environment were perceived as facilitators. However, all three categories were more barrier than facilitator for over 40% of the students. Although course environment is the barrier most under control of the institutions, understanding students´ personal environment and characteristics of learning can help them to provide support and facilitate full engagement in online courses.
Downloads
References
Attride-Stirling, J. (2001). Thematic networks: An analytic tool for qualitative research. Qualitative Research, 1(3), 385–405. https://doi.org/10.1177/146879410100100307
Borup, J., Graham, C. R., West, R. E., Archambault, L., & Spring, K. J. (2020). Academic communities of engagement: An expansive lens for examining support structures in blended and online learning. Educational Technology Research and Development, 68(2), 807–832. https://doi.org/10.1007/s11423-020-09744-x
Chen, B., Bastedo, K., & Howard, W. (2018). Exploring design elements for online STEM courses: Active learning, engagement & assessment design. Online Learning Journal, 22(2), 59–76. https://doi.org/10.24059/olj.v22i2.1369
Cho, M.H., & Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3), 290-301. http://dx.doi.org/10.1080/01587919.2013.835770
Christenson, S. L., Reschly, A. L., & Wylie, C. (2012). Handbook of research on student engagement. Springer.
Cleary, T. J., & Zimmerman, B. J. (2004). Self-regulation empowerment program: A school-based program to enhance self-regulated and self-motivated cycles of student learning. Psychology in the Schools, 4(15), 537–550. https://doi.org/10.1002/pits.10177
Dennen, V.P. Darabi, A.A., & Smith, L.J. (2007). Instructor-learner interaction in online courses: The relative perceived importance of particular instructor actions on performance and satisfaction. Distance Education, 28(1), 65-79. https://doi.org/10.1080/01587910701305319
Fayer, L. (2014). A multi-case study of student perceptions of online course design elements and success. International Journal for the Scholarship of Teaching & Learning, 8(1), Artículo 13. https://doi.org/10.20429/ijsotl.2014.080113
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.
Guo, P., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of mooc videos. Proceedings of the First ACM Conference on Learning at Scale Conference, 41–50. https://doi.org/10.1145/2556325.2566239
Halverson, L. R., & Graham, C. R. (2019). Learner engagement in blended learning environments: A conceptual framework. Online Learning, 23(2), 145–178. https://doi.org/10.24059/olj.v23i2.1481
Han, I., & Shin, W. S. (2016). The use of a mobile learning management system and academic achievement of online students. Computers & Education, 102 (Noviembre 2016), 79-89. https://doi.org/10.1016/j.compedu.2016.07.003
Jung, Y., & Lee, J. (2018). Learning engagement and persistence in massive open online courses (MOOCS). Computers & Education, 122(Julio 2018), 9–22. https://doi.org/10.1016/j.compedu.2018.02.013
Kalyuga, S., & Liu, T. C. (2015). Guest editorial: managing cognitive load in technology-based learning environments. Educational Technology & Society, 18(4), 1-8.
Kaymak, Z. D., & Horzum, M. B. (2022). Student barriers to online learning as predictors of perceived academic learning and academic achievement. Turkish Online Journal of Distance Education, 23 (2), Artículo 7. https://doi.org/10.17718/tojde.1096250
Kim, K. R., & Seo, E. H. (2015). The relationship between procrastination and academic performance: A meta-analysis. Personality and Individual Differences, 82, 26-33. https://doi.org/10.1016/j.paid.2015.02.038
Klingsieck, K. B., Fries, S., Horz, C., & Hofer, M. (2012). Procrastination in a distance university setting. Distance Education, 33(3), 295-310. http://dx.doi.org/10.1080/01587919.2012.723165
Klingsieck, K. B., Grund, A., Schmid, S., & Fries, S. (2013) Why students procrastinate: A qualitative approach. Journal of College Student Development, 54(4), 397-412. https://doi.org/10.1353/csd.2013.0060
Koçdar, S., Karadeniz, A., Bozkurt, A., & Buyuk, K. (2018). Measuring self-regulation in self-paced open and distance learning environments. International Review of Research in Open and Distributed Learning, 19(1), 25–42. https://doi.org/10.19173/irrodl.v19i1.3255
Kumar, S., Martin, F., Budhrani, K., & Ritzhaupt, A. (2019). Award-winning faculty online teaching practices: Elements of award-winning courses. Online Learning, 23(4), 160-180. http://dx.doi.org/10.24059/olj.v23i4.2077
Lowenthal, P. R., West, R. E., Archambault, L., Borup, J., & Belt, E. S. (2021). Faculty perceptions of using synchronous video-based communication technology. Online Learning Journal, 25(4), 49–78. https://doi.org/10.24059/olj.v25i4.2890
Martin, F., & Bolliger, D. U. (2018). Engagement matters: Student perceptions on the importance of engagement strategies in the online learning environment. Online Learning, 22(1), 205-222. https://doi.org/10.24059/olj.v22i1.1092
Martin, F., Ritzhaupt, A., Kumar, S., & Budhrani, K. (2019). Award-winning faculty online teaching practices: Course design, assessment and evaluation, and facilitation. Internet and Higher Education, 42(Julio 2019), 34–43. https://doi.org/10.1016/j.iheduc.2019.04.001
Martin, F., Kumar, S., Ritzhaupt, A. D., & Polly, D. (2023). Bichronous online learning: Award-winning online instructor practices of blending asynchronous and synchronous online modalities. Internet and Higher Education, 56, Artículo 100879. https://doi.org/10.1016/j.iheduc.2022.100879
Martin, F., & Borup, J. (2022). Online learner engagement: Conceptual definitions, research themes, and supportive practices. Educational Psychologist, 57(3), 162–177. https://doi.org/10.1080/00461520.2022.2089147
Mayer, R. (2019). Thirty years of research on online learning. Applied Cognitive Psychology, 33(2), 152–159. https://doi.org/10.1002/acp.3482
Mayer, R. E. (2014). Cognitive theory of multimedia learning. En R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2ª ed.) (pp. 43–71). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.005
Mayer, R. E., & Fiorella, L. (2014). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity. En R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (2ª ed.) (pp. 279–315). Cambridge University Press. https://doi.org/10.1017/CBO9781139547369.015
Muilenburg, L. Y., & Berge, Z. L. (2005). Student barriers to online learning: A factor analytic study. Distance Education, 26(1), 29-48. https://doi.org/10.1080/01587910500081269
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 1–28. https://doi.org/10.3389/fpsyg.2017.00422
Panigrahi, R., Srivastava, P. R., & Sharma, D. (2018). Online learning: Adoption, continuance, and learning outcome—A review of literature. International Journal of Information Management, 43, 1–14. https://doi.org/10.1016/j.ijinfomgt.2018.05.005
Pelikan E. R., Korlat S., Reiter J., Holzer J., Mayerhofer M., Schober B., …, & Lüftenegger, M. (2021) Distance learning in higher education during COVID-19: The role of basic psychological needs and intrinsic motivation for persistence and procrastination–a multi-country study. Plos One, 16(10), 1-23. https://doi.org/10.1371/journal.pone.0257346
Rajabalee, Y. B., & Santally, M. I. (2021). Learner satisfaction, engagement and performances in an online module: Implications for institutional e-learning policy. Education and Information Technologies, 26(3), 2623–2656. https://doi.org/10.1007/s10639-020-10375-1
Shin, S., & Cheon, J. (2019). Assuring student satisfaction of online education: A search for core course design elements. En G. Marks (Ed.), Proceedings of International Journal on E-Learning 2019 (pp. 147-164). Association for the Advancement of Computing in Education (AACE).
Shin, W., & Kang, M. (2015). The use of a mobile learning management system at an online university and its effect on learning satisfaction and achievement. International Review of Research in Open and Distributed Learning, 16(3), 110–130. https://doi.org/10.19173/irrodl.v16i3.1984
Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100(4), 765–781. https://doi.org/10.1037/a0012840
Soffer, T., & Cohen, A. (2019). Students’ engagement characteristics predict success and completion of online courses. Journal of Computer Assisted Learning, 35(3), 378–389. https://doi.org/10.1111/jcal.12340
Tate, T., & Warschauer, M. (2022). Equity in online learning. Educational Psychologist, 57(3), 192–206. https://doi.org/10.1080/00461520.2022.2062597
Tuiloma, S., Graham, C. R., Martinez Arias, A. M., & Parra Caicedo, D. M. (2022). Providing institutional support for academic engagement in online and blended learning programs. Education Sciences, 12(10), Artículo 641. https://doi.org/10.3390/educsci12100641
Young, A., & Norgard, C. (2006). Assessing the quality of online courses from the students' perspective. The Internet and Higher Education, 9(2), 107-115. https://doi.org/10.1016/j.iheduc.2006.03.001.

Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Cinthia Bittencourt Spricigo, Bárbara Maria Camilotti, Charles R. Graham, Ruth Baptista

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Educación XX1 is published under a Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)