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Distance education, 2019-01, Vol.40 (1), p.133-148
2019

Details

Autor(en) / Beteiligte
Titel
Predicting student satisfaction and perceived learning within online learning environments
Ist Teil von
  • Distance education, 2019-01, Vol.40 (1), p.133-148
Ort / Verlag
Melbourne: Routledge
Erscheinungsjahr
2019
Link zum Volltext
Quelle
ERIC
Beschreibungen/Notizen
  • 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.
Sprache
Englisch
Identifikatoren
ISSN: 0158-7919
eISSN: 1475-0198
DOI: 10.1080/01587919.2018.1553562
Titel-ID: cdi_informaworld_taylorfrancis_310_1080_01587919_2018_1553562

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