Students' Characteristics, Self-Regulated Learning, Technology Self-Efficacy, and Course Outcomes in Online Learning
ARTICLE
Chih-Hsuan Wang, David M. Shannon, Margaret E. Ross
Distance Education Volume 34, Number 3, ISSN 0158-7919
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.
Citation
Wang, C.H., Shannon, D.M. & Ross, M.E. (2013). Students' Characteristics, Self-Regulated Learning, Technology Self-Efficacy, and Course Outcomes in Online Learning. Distance Education, 34(3), 302-323. Retrieved December 12, 2019 from https://www.learntechlib.org/p/157411/.

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Keywords
- academic achievement
- College Students
- computer literacy
- Correlation
- educational technology
- electronic learning
- Goodness of Fit
- Likert Scales
- Measures (Individuals)
- models
- Online Surveys
- Outcomes of Education
- Predictor Variables
- PRIOR LEARNING
- Questionnaires
- Regression (Statistics)
- Reliability
- Self Efficacy
- Self Management
- Statistical Analysis
- Structural Equation Models
- student attitudes
- Student Characteristics
- student motivation
- Student Surveys
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