How do test-takers rate their effort? A comparative analysis of self-report and log file data

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2023-08-01 DOI:10.1016/j.lindif.2023.102340
Róbert Csányi , Gyöngyvér Molnár
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Abstract

The present study investigates students' test-taking effort by integrating and comparing traditional self-report questionnaire data and students' test-taking behavior, based on log data analyses. Previous studies have shown that different methods often lead to different results. A computer-based measure of complex problem-solving in uncertain situations was used to minimize the influence of factual knowledge on test performance. K-means cluster analysis was used to build groups of students differing in test-taking effort, resulting in 3 distinct groups. The correlation between students' test-taking effort and test performance proved to be weaker based on the self-reported questionnaire data than on their actual test-taking behavior. Both the self-report questionnaire and the log data showed a decrease in test-taking effort during the test. The number of clicks played the largest role in predicting performance. Results suggest that (1) self-report questionnaire data are not consistent with students' actual test-taking behavior and (2) it's not necessary to make the maximum effort to obtain valid test results, but a certain level of effort is needed.

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考生如何评价他们的努力?自我报告和日志文件数据的比较分析
本研究基于日志数据分析,通过整合和比较传统的自我报告问卷数据和学生的考试行为,调查学生的考试努力。先前的研究表明,不同的方法往往会导致不同的结果。在不确定的情况下,使用基于计算机的复杂问题解决措施来最大限度地减少事实知识对考试成绩的影响。K-means聚类分析用于建立不同考生努力程度的学生群体,产生3个不同的群体。根据自我报告的问卷数据,学生的考试努力与考试成绩之间的相关性弱于他们的实际考试行为。自我报告问卷和日志数据都显示,在测试期间,参加测试的努力有所减少。点击量在预测性能方面发挥了最大作用。结果表明:(1)自我报告的问卷数据与学生的实际考试行为不一致;(2)没有必要尽最大努力获得有效的考试结果,但需要一定程度的努力。
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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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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