KAP: Knowledge-Graph Based Auxiliary Platform for Outcome-Based Python Education

Outcome Based Education (OBE) is currently a popular approach, but quantifying students' learning outcomes remains a challenge. To address this issue, this paper proposes the development of a Knowledge-graph based Auxiliary Platform (KAP) for outcome-based Python education. KAP facilitates manual organization of knowledge points by teachers according to the expected learning outcomes and associates relevant questions with each point. This feature allows for automatic qualification of students' mastery of knowledge by monitoring their progress within the question bank in KAP. Moreover, the discrepancy between the targeted and achieved levels of knowledge mastery can guide teachers in adjusting their teaching process in a timely manner. To implement KAP, we utilized the model-view-controller design pattern and incorporated it into the Python programming course for sophomores at Central South University in China. Results from one semester demonstrate that KAP is a valuable tool for both teaching and learning. Objective and subjective evaluations confirm that KAP is a suitable platform for outcome-based Python education.