Student affect during learning with a MOOC

John Dillon, G. Ambrose, N. Wanigasekara, Malolan Chetlur, Prasenjit Dey, Bikram Sengupta, S. D’Mello
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引用次数: 10

Abstract

This paper presents affect data collected from periodic emotion detection surveys throughout an introductory Statistics MOOC called "I Heart Stats." This is the first MOOC, to our knowledge, to capture valuable student affect data through self-reported surveys. To collect student affect, we used two self-reporting methods: (1) The Self-Assessment Manikin and (2) A discrete emotion list. We found that the most common reported MOOC emotion was Hope followed by Enjoyment and Contentment. There were substantial shifts in affective states over the course, notably with Anxiety and Pride. The most valuable result of our study is a preliminary description of the methods for collecting self-reported student affect at scale in a MOOC setting.
学生在MOOC学习过程中的影响
本文介绍了在一个名为“I Heart Stats”的入门统计学MOOC中,从定期情绪检测调查中收集的情绪数据。据我们所知,这是第一个通过自我报告的调查来获取有价值的学生影响数据的MOOC。为了收集学生的情感,我们使用了两种自我报告方法:(1)自我评估模型和(2)离散情绪列表。我们发现,在MOOC课程中最常见的情绪是“希望”,其次是“享受”和“满足”。在整个过程中,情感状态发生了实质性的变化,尤其是焦虑和骄傲。我们的研究最有价值的结果是初步描述了在MOOC环境下大规模收集自我报告的学生影响的方法。
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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