The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning
Abstract
The purpose of this study was to examine the relationship among students’ characteristics, self-regulated learning, technology self-efficacy, and course outcomes in online learning settings. Two hundred and fifty-six students participated in this study. All participants completed an online survey that included demographic information, the modified motivation strategies learning questionnaire, the online technology self-efficacy scale, the course satisfaction questionnaire, and the final grades. The researchers used structural equation modeling to examine relationships among student characteristics, self-regulated learning, technology self-efficacy, and course outcomes. Based on the results from the final model, students with previous online learning experiences tended to have more effective learning strategies when taking online courses, and hence, had higher levels of motivation in their online courses. In addition, when students had higher levels of motivation in their online courses, their levels of technology self-efficacy and course satisfaction increased. Finally, students with higher levels of technology self-efficacy and course satisfaction also earned better final grades. Based on the findings, we recommend that instructors design courses in a way that can promote students’ self-regulated learning behaviors in online learning settings and that students in online classes, as in traditional classes, set aside a regular time to concentrate on the course. Also, institutions should provide user-friendly online learning platforms and workshops for instructors and students to facilitate the teaching and learning experiences.
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Cites
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A Conceptual Framework for Assessing Motivation and Self-Regulated Learning in College Students
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Understanding self‐regulated learning
Pintrich, P. R. (1995) · New Directions for Teaching and Learning · doi:10.1002/tl.37219956304 · Cited by 633
McLoughlin, C. (2002) · Distance Education · doi:10.1080/0158791022000009178 · Cited by 220
Learning to learn online: A study of perceptual changes between multiple online course experiences
Arbaugh, J. B. (2004) · The Internet and Higher Education · doi:10.1016/j.iheduc.2004.06.001 · Cited by 156
Cited by
Broadbent, J., & Poon, W. L. (2015) · The Internet and Higher Education · doi:10.1016/j.iheduc.2015.04.007 · Cited by 1,692
College students’ use and acceptance of emergency online learning due to COVID-19
Patricia Aguilera-Hermida, A. (2020) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2020.100011 · Cited by 1,286
“The interaction between students and teachers is mediated by technology, and the design of learning environments (e.g., space where learning occurs) can have considerable influence on learning outcomes ( Bower, 2019 ; Gonzalez et al., 2020 ; Wang et al., 2013 ).”
Kizilcec, R. F., Pérez-Sanagustín, M., & Maldonado, J. J. (2017) · Computers & Education · doi:10.1016/j.compedu.2016.10.001 · Cited by 1,003
Roddy, C., Amiet, D. L., Chung, J., Holt, C., Shaw, L., McKenzie, S., Garivaldis, F., Lodge, J. M., & Mundy, M. E. (2017) · Frontiers in Education · doi:10.3389/feduc.2017.00059 · Cited by 334
Jansen, R. S., van Leeuwen, A., Janssen, J., Jak, S., & Kester, L. (2019) · Educational Research Review · doi:10.1016/j.edurev.2019.100292 · Cited by 310
Metadata
- Authors
- Wang, C.-H., Shannon, D. M., & Ross, M. E.
- Venue
- Distance Education
- Publisher
- Informa UK Limited
- Published
- 2013-10-31
- Volume
- 34
- Issue
- 3
- Pages
- 302-323
- ISSN
- 0158-7919 (ISSN-L)
- 1475-0198
- OpenAlex
- W2005075389
- Cited by
- 778
- References
- 7
- FWCI
- 87.80
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.