Monitoring Student Frustration Level Using Blackbox Logs

P. Kurtiker, R. Wagh
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引用次数: 1

Abstract

we use the worldwide source code repository Blackbox to detect frustration among the learners. This study measures frustration by calculating individual student Error Quotient (EQ) score per laboratory session. So higher the EQ score higher is the frustration, similarly lower the EQ score lower is the frustration. The threshold of 0.5 is set, so if the score is greater than or equal to 0.5 the student is said to be frustrated. Similarly, the average score across each laboratory session for each individual student is calculated. The result shows that 13 out of 20 students were frustrated for Object Oriented Programming (OOP) laboratory sessions. The validation was carried out by human observers with the inter rater reliability of Cohens' Kappa as exceptionally high.
使用黑匣子日志监测学生的沮丧程度
我们使用全球源代码库Blackbox来检测学习者的挫败感。本研究通过计算每个实验阶段学生的错误商数(EQ)得分来衡量挫败感。所以情商越高,挫折感越高,同样,情商越低,挫折感越低。设置了0.5的阈值,所以如果分数大于或等于0.5,学生就被认为是沮丧的。同样,计算每个学生每次实验的平均分数。结果显示,20名学生中有13名对面向对象编程(OOP)的实验课程感到沮丧。验证是由人类观察员进行的,科恩斯卡帕的内部信度异常高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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