Developing a Learning Data Collection Platform for Learning Analytics in Online Education
Source abstract
Abstract
During the COVID-19 pandemic, most education has been conducted through online classes. While feedback and interaction between students and instructors are significant in programming education or engineering practice, online education today cannot satisfy these aspects of learning. Therefore, this study proposes a learning support system for programming education and presents the results of designing and implementing this system. The proposed system consists of an online development environment module, a learning monitoring module, and a learning support module. It also provides a web-based programming environment, real-time chat and code mirroring, error guide messages and related lectures, e-learning quizzes, and learning activity analysis features. The system standardizes the development environment between the instructor and students, helps students take the initiative in solving errors, and enables code-oriented interactions between the instructor and students. It also collects data from all learning situations in the database. Conducting a big data analysis with the collected data will enable individual guidance for students by finding errors that frequently occur in programming and recommending learning materials to solve them.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Online Learning and Analytics · Teaching and Learning Programming · Educational Technology and Assessment
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Tabula Rasa College, Keimyung University, Daegu 42601, Korea
Department of Computer Engineering, Keimyung University, Daegu 42601, Korea
Funding
National Research Foundation of Korea
References (19)
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