Learning Performance in Adaptive Learning Systems: A Case Study of Web Programming Learning Recommendations.

ABSTRACT: Students often face challenges while learning computer programming because programming languages' logic and visual presentations differ from human thought processes. If the course content does not closely match learners' skill level, the learner cannot follow the learning process, resulting in frustration, low learning motivation, or abandonment. This research proposes a web programming learning recommendation system to provide students with personalized guidance and step-by-step learning planning. The system contains front-end and back-end web development instructions. It can create personalized learning paths to help learners achieve a sense of accomplishment. The system can help learners build self-confidence and improve learning effectiveness. In study 1, the recommendation system was

SUBMITTER: Ling HC 

PROVIDER: S-EPMC8831801 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature