A Predictive Study of Learner Attitudes Toward Open Learning in a Robotics Class

作者：Avsec Stanislav^*; Rihtarsic David; Kocijancic Slavko

来源：Journal of Science Education and Technology, 2014, 23(5): 692-704.

DOI：10.1007/s10956-014-9496-6

• Open learning
• Expectations in open learning
• Student satisfaction
• Direct manipulation environment of robotics
• Regression model

Open learning (OL) strives to transform teaching and learning by applying learning science and emerging technologies to increase student success, improve learning productivity, and lower barriers to access. OL of robotics has a significant growth rate in secondary and/or high schools, but failures exist. Little is known about why many users stop their OL after their initial experience. Previous research done under different task environments has suggested a variety of factors affecting user satisfaction with different types of OL. In this study, we tested a regression model for student satisfaction involving students' attitudes toward OL usage. A survey was conducted to investigate the critical factors affecting students' achievements and satisfaction in OL of robotics with use of own developed direct manipulation learning environment as learning context. A multiple regression analyses were carried out to investigate how different facets of students' expectations and experiences are related to perceived learning achievements and course satisfaction. Descriptive statistics and analysis of variance was performed to determine the effect of predictor variables to student satisfaction. The results demonstrate that students have significantly positive perceptions toward using OL of robotics as a learning-assisted tool. Furthermore, behavioral intention to use OL is influenced by perceived usefulness and self-efficacy. The following five major categories of satisfaction factors with OL course were revealed during analysis of the studies (effect sizes in parentheses): organization (0.69); implementation (0.61); professional content (0.53); interaction (0.43); self-efficacy (0.14). All these effect sizes were judged to be significant and large. The results also showed that learner-mentor/instructor interaction, learner-professional content interaction, and online and offline self-efficacy were good predictors of student satisfaction and course quality. Peer interactions and self-regulated learning have to be considered carefully. A learner-mentor/instructor and learner-professional content interaction are indicated as most significant interactions.

• 出版日期2014-10