Applying learning analytics to explore the effects of programming learning process on computational thinking ability

Abstract

Computational thinking (CT) ability is becoming increasingly critical Training students to integrate computational thinking ability is also a significant issue facing our current education system The concepts and principles of computational thinking are very abstract and difficult to understand; besides traditional programming has a high initial learning threshold; many students find it difficult to learn and it can easily cause fear and disinterest In addition current computational thinking practices generally use quantitative methods to evaluate effectiveness and impact such as computational thinking tests scales questionnaires and project evaluations and thus measure students' computational thinking After our investigation we found that current research is less focused on qualitative research methods such as the learning process or case studies in applied behavior analysis Therefore this study aims to explore the effects of the programming learning process on computational thinking ability To this end this study builds a visual programming computational thinking learning platform and designs an 18-week computational thinking programming learning course to train learners' computational thinking ability In addition we developed a real-time behavior tracking record module to collect learners' programming learning processes and behaviors in learning activities; meanwhile we applied different learning analytics to analyze the collected data and thus the learning behavior patterns of diverse learners

Date of Award	2020
Original language	English
Supervisor	Yueh-Min Huang (Supervisor)