A contextualized assessment of reliability and validity of student-initiated momentary self-reports during lectures

Pankaj Chavan, Ritayan Mitra, Abhinav Sarkar, Aditya Panwar
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Abstract

The use of Experience Sampling Methods (ESM) to assess students’ experiences, motivation, and emotions by sending signals to students at random or fixed time points has grown due to recent technological advances. Such methods offer several advantages, such as capturing the construct in the moment (i.e., when the events are fresh on respondents’ minds) or providing a better understanding of the temporal and dynamic nature of the construct, and are often considered to be more valid than retrospective self-reports. This article investigates the validity and reliability of a variant of the ESM, the DEBE (an acronym for difficult, easy, boring and engaging, and pronounced ‘Debbie’) feedback, which captures student-driven (as and when the student wants to report) momentary self-reports of cognitive-affective states during a lecture. The DEBE feedback is collected through four buttons on mobile phones/laptops used by students. We collected DEBE feedback from several video lectures (N = 722, 8 lectures) in different courses and examined the threats to validity and reliability. Our analysis revealed variables such as student motivation, learning strategies, academic performance, and prior knowledge did not affect the feedback-giving behavior. Monte Carlo simulations showed that for a class size of 50 to 120, on average, 30 students can provide representative and actionable feedback, and the feedback was tolerant up to 20% of the students giving erroneous or biased feedback. The article discusses in detail the aforementioned and other validity and reliability threats that need to be considered when working with such data. These findings, although specific to the DEBE feedback, are intended to supplement the momentary self-report literature, and the study is expected to provide a roadmap for establishing validity and reliability of such novel data types.

Abstract Image

课堂上学生自我报告的信度和效度的情境化评估
由于最近的技术进步,使用经验抽样方法(ESM)通过在随机或固定的时间点向学生发送信号来评估学生的经历、动机和情绪,这种方法越来越多。这样的方法有几个优点,比如捕捉到当下的结构(即,当事件在被调查者的脑海中是新鲜的),或者提供对结构的时间和动态性质的更好理解,并且通常被认为比回顾性自我报告更有效。本文研究了ESM的一种变体——DEBE反馈的有效性和可靠性(DEBE是“困难”、“容易”、“无聊”和“吸引人”的首字母缩写,发音为“黛比”),它捕捉了学生驱动的(当学生想要报告时)课堂上认知情感状态的瞬间自我报告。DEBE反馈是通过学生使用的手机/笔记本电脑上的四个按钮收集的。我们收集了不同课程的几个视频讲座(N = 722, 8个讲座)的DEBE反馈,并检验了效度和信度的威胁。我们的分析显示,学生动机、学习策略、学习成绩和先验知识等变量对反馈行为没有影响。蒙特卡罗模拟表明,对于50至120人的班级,平均30名学生可以提供具有代表性和可操作的反馈,并且反馈可以容忍高达20%的学生给出错误或有偏见的反馈。本文详细讨论了在处理此类数据时需要考虑的上述以及其他有效性和可靠性威胁。这些发现虽然是针对DEBE反馈的,但旨在补充瞬时自我报告文献,预计该研究将为建立这种新数据类型的有效性和可靠性提供路线图。
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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