Abstract
Nowadays, it has been a significant problem to recommend learning strategy for different learners in programming learning projects. This paper discusses a personalized learning strategy recommendation approach to aid programming learning. In this paper, an improved design method of model learner strategies and programming learning strategy recommendation approach are presented. A reward factor is adopted to help to construct a learning strategy recommendation mechanism adaptively. The programming learning strategy recommendation system (ZZULI-PLS) is proposed based on those models to help learners learning in programming according to the actual progresses of learners. Usability tests are conducted to validate the recommendation efficiency in ZZULI-PLS system.
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Acknowledgments
This work was supported by the Educational Commission of Henan Province of China (grant no. 15A520030), the 3rd Young teachers teaching reform and research project of Zhengzhou University of Light Industry (project no. 31), and 11th teachers teaching reform and research project of Zhengzhou University of Light Industry (project no. 3).
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Gu, P., Ma, J., Chen, W., Deng, L., Jiang, L. (2017). A Personalized Learning Strategy Recommendation Approach for Programming Learning. In: Bao, Z., Trajcevski, G., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10179. Springer, Cham. https://doi.org/10.1007/978-3-319-55705-2_21
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DOI: https://doi.org/10.1007/978-3-319-55705-2_21
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