基于编程行为的学习者人格特质识别及应用探索
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四川大学软件学院

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TP3

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Recognizing learners' personality traits based on programming behaviors and its application explorations
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College of Software Engineering,Sichuan University

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    摘要:

    如何进行个性化的编程教学是教学实践面临的重要问题,其中,如何有效地识别编程学习者的个性是一个关键. 本文提出了一种基于学习者编程行为的人格特质识别方法.具体来说,首先从多角度提取学习者编程行为特征,基于支持向量机建立分类模型,并采用多任务投票的策略来综合识别学习者的人格特质. 研究表明,该方法能够较好地识别学习者的大五人格特质,在一定程度上验证了采用编程行为来识别学习者个性的可行性. 此外,本文还探讨了基于编程行为的人格特质识别方法在未来编程学习、教学中的应用.

    Abstract:

    How to perform individualized programming teaching is an important issue in educational practice, and how to recognize the personality of learners is the key for this issue. In this paper, the method of recognizing personality is proposed based on the programming behaviors of learners. Specifically, the programming behavior features of learners are first extracted from multiple aspects; then the classification models are established using the support vector machine; finally, the multi-task voting strategy is used to comprehensively identify learners' personality traits. The results show that the traits in the Big Five Model can be predicted using the proposed method, verifying the feasibility of using programming behaviors to identify learners’ personality to a certain extent; in addition, this paper also discusses the applications of the proposed method in future programming education.

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引用本文格式: 林涛,周小涵,吴芝明,洪玫,王建,唐宁九. 基于编程行为的学习者人格特质识别及应用探索[J]. 四川大学学报: 自然科学版, 2021, 58: 057002.

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历史
  • 收稿日期:2021-08-10
  • 最后修改日期:2021-09-03
  • 录用日期:2021-09-08
  • 在线发布日期: 2021-10-18
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