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Machine Learning Model for Analyzing Learning Situations in Programming Learning

机译:用于分析编程学习的学习情况的机器学习模型

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In programming learning, students have individual difficulties, and teachers need to grasp those difficulties and provide appropriate support for the students. However, since it is a heavy burden for teachers, a method to automatically estimate the learning situations of students is required. In this research, we developed a method that adopts the development of a machine learning model as an approach to achieve this purpose. This machine learning model outputs the estimated learning situation when the source code editing history of new students is input. As a result of evaluating the developed method, it was possible to estimate the correct learning situations with high accuracy of 98%. The applicability of this learning situation estimation method in practical lessons was shown.
机译:在编程学习中,学生有个人困难,教师需要掌握这些困难并为学生提供适当的支持。然而,由于教师是一个沉重的负担,因此需要自动估计学生学习情况的方法。在这项研究中,我们开发了一种采用机器学习模型的开发作为实现此目的的方法的方法。当输入新学生的源代码编辑历史时,该机器学习模型输出估计的学习情况。由于评估了开发方法,可以高精度估计98%的高精度。显示了在实践课程中的这种学习情况估算方法的适用性。

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