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Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model
ARTICLE

Computers & Education Volume 134, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd

Abstract

The purpose of this study was to investigate the relationship between self-regulated learning and planned behavior of students participating in massive open online courses (MOOCs) at universities.This was a questionnaire study in which all of the respondents in the survey are undergraduate students in Taiwan. A total of 222 (114 male and 108 female) students were selected as survey subjects. Researchers used partial least squares (PLS) regression and confirmatory factor analysis (CFA) to evaluate the measurement model and the quality of measures. Data collection tools were the Self-Regulated Learning at Work Questionnaire and the Theory of Planned Behavior Questionnaire.Structural equation modeling was used to test research hypotheses. All the hypotheses tests showed that there was a positive and significant relationship between forethought of SRL and TPB. But, the relationship between attitude toward the behavior and behavioral intention was not significant. Additionally, the salient role of self-efficacy, goal setting, and task interest in generating planned behavior for participating in MOOCs was identified. Overall, self-efficacy, goal setting, and task interest were strong prediction variables for the proposed theoretical model.Results of the structural model comparisons revealed that the prediction power of the integrated model was superior to that of the theory of planned behavior or the self-regulated learning model in the MOOCs online learning context.

Citation

Lung-Guang, N. (2019). Decision-making determinants of students participating in MOOCs: Merging the theory of planned behavior and self-regulated learning model. Computers & Education, 134(1), 50-62. Elsevier Ltd. Retrieved May 24, 2019 from .

This record was imported from Computers & Education on March 15, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.compedu.2019.02.004

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