Practice exams make perfect: incorporating course resource use into an early warning system

R. J. Waddington, Sungjin Nam
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引用次数: 14

Abstract

Early Warning Systems (EWSs) are being developed and used more frequently to aggregate multiple sources of data and provide timely information to stakeholders about students in need of academic support. As these systems grow more complex, there is an increasing need to incorporate relevant and real-time course-related information that could be predictors of a student's success or failure. This paper presents an investigation of how to incorporate students' use of course resources from a Learning Management System (LMS) into an existing EWS. Specifically, we focus our efforts on understanding the relationship between course resource use and a student's final course grade. Using ten semesters of LMS data from a requisite Chemistry course, we categorized course resources into four categories. We used a multinomial logistic regression model with semester fixed-effects to estimate the relationship between course resource use and the likelihood that a student receives an "A" or "B" in the course versus a "C." Results suggest that students who use Exam Preparation or Lecture resources to a greater degree than their peers are more likely to receive an "A" or "B" as a final grade. We discuss the implications of our results for the further development of this EWS and EWSs in general.
实践考试是完美的:将课程资源的使用纳入预警系统
早期预警系统(ews)正在被开发和更频繁地用于汇总多个数据来源,并向利益相关者提供有关需要学术支持的学生的及时信息。随着这些系统变得越来越复杂,越来越需要整合相关的和实时的课程相关信息,这些信息可以预测学生的成功或失败。本文研究了如何将学生对学习管理系统(LMS)课程资源的使用整合到现有的EWS中。具体来说,我们的重点是理解课程资源使用与学生最终课程成绩之间的关系。利用一门必修化学课程的十个学期LMS数据,我们将课程资源分为四类。我们使用具有学期固定效应的多项逻辑回归模型来估计课程资源使用与学生在课程中获得“a”或“B”与“c”的可能性之间的关系。结果表明,使用考试准备或讲座资源的学生比同龄人更有可能获得“a”或“B”作为最终成绩。我们讨论了我们的结果对该EWS和一般EWS的进一步发展的影响。
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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