Computer Science and Engineering Students' Self-Directed Learning Strategies and Satisfaction in Online Learning

• In Event: Computational Thinking and Cognition

Abstract

This sequential mixed study aims to examine Computer Science and Engineering students’ SDL strategies and satisfaction in online courses. The researchers surveyed 225 students and conducted semi-structured interviews with 15 online students in higher education. The quantitative survey data and the qualitative data were analyzed using descriptive analysis and thematic analysis, respectively. The findings indicated that: (1) both extrinsic motivation and intrinsic motivation strategies were used; (2) diverse metacognition and cognitive strategies were used to monitor learning; (3) time-management and resources management strategies were leveraged; (4) the specific design or instruction that helped students’ SDL skills were identified, such as access to documented learning materials; and (5) students’ satisfaction depended on the design of the course.

Authors

• Meina Zhu, Wayne State University

• Sara Berri, Wayne State University

• Yaoxian Huang, Wayne State University

• Sara Masoud, Wayne State University