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ERIC Number: EJ1206863
Record Type: Journal
Publication Date: 2019
Pages: 16
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0158-7919
EISSN: N/A
Predicting Student Satisfaction and Perceived Learning within Online Learning Environments
Alqurashi, Emtinan
Distance Education, v40 n1 p133-148 2019
Student satisfaction is used as one of the key elements to evaluate online courses, while perceived learning is considered as an indicator of learning. This study aimed to explore how online learning self-efficacy (OLSE), learner--content interaction (LCI), learner--instructor interaction (LII), and learner--learner interaction (LLI) can predict student satisfaction and perceived learning. A total of 167 students participated in this study. Regression results revealed that the overall model with all four predictor variables (OLSE, LCI, LII, and LLI) was significantly predictive of satisfaction and perceived learning. The study found that LCI was the strongest and most significant predictor of student satisfaction, while OLSE was the strongest and most significant predictor of perceived learning. However, LLI was not predictive of student satisfaction and perceived learning. This study suggests that instructors employ strategies that enhance students' OLSE, LCI, and LII. Research is needed to understand how LLI fosters student learning and satisfaction.
Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research; Tests/Questionnaires
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Pennsylvania
Grant or Contract Numbers: N/A