Abstract
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.
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Acknowledgement
The authors sincerely thank the reviewers for their helpful comments on this paper. This work is partially supported by the key research and development project of Hunan province under grant No. 2022SK2107 and the academic research project on education of central south university. In addition, this work was also carried out in part using computing resources at the High Performance Computing Center of Central South University.
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Jiang, W., Sun, Z., Hu, J., Zhong, P., Lu, M. (2023). KAP: Knowledge-Graph Based Auxiliary Platform for Outcome-Based Python Education. In: Hong, W., Weng, Y. (eds) Computer Science and Education. ICCSE 2022. Communications in Computer and Information Science, vol 1813. Springer, Singapore. https://doi.org/10.1007/978-981-99-2449-3_10
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DOI: https://doi.org/10.1007/978-981-99-2449-3_10
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