首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Predicting student satisfaction and perceived learning within online learning environments
Authors:Emtinan Alqurashi
Institution:Center for the Advancement of Teaching, Temple University, Philadelphia, PA, USA
Abstract: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.
Keywords:Self-efficacy  interaction  student satisfaction  perceived learning  online learning
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号