大规模评估中过程数据的使用:文献综述

IF 2.6 Q1 EDUCATION & EDUCATIONAL RESEARCH Large-Scale Assessments in Education Pub Date : 2024-05-06 DOI:10.1186/s40536-024-00202-1
Ella Anghel, Lale Khorramdel, Matthias von Davier
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引用次数: 0

摘要

随着过程数据在大规模教育评估中的使用越来越普遍,有关考生考试行为的数据显然可以揭示他们的表现,并对评估的有效性产生至关重要的影响。对这一领域的文献进行全面回顾,可以让研究人员和从业人员了解共同的发现以及现有的差距。本文献综述采用主题建模的方法,在 221 项使用大规模评估过程数据的实证研究中确定了主题。我们确定了六个重复出现的主题:反应时间模型、一般反应时间、异常应试行为、动作序列、复杂问题解决和数字写作。我们还讨论了每一类研究中使用的主要理论。基于这些发现,我们提出了未来应用大规模评估过程数据的研究方向。
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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The use of process data in large-scale assessments: a literature review

As the use of process data in large-scale educational assessments is becoming more common, it is clear that data on examinees’ test-taking behaviors can illuminate their performance, and can have crucial ramifications concerning assessments’ validity. A thorough review of the literature in the field may inform researchers and practitioners of common findings as well as existing gaps. This literature review used topic modeling to identify themes in 221 empirical studies using process data in large-scale assessments. We identified six recurring topics: response time models, response time-general, aberrant test-taking behavior, action sequences, complex problem-solving, and digital writing. We also discuss the prominent theories used by studies in each category. Based on these findings, we suggest directions for future research applying process data from large-scale assessments.

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来源期刊
Large-Scale Assessments in Education
Large-Scale Assessments in Education Social Sciences-Education
CiteScore
4.30
自引率
6.50%
发文量
16
审稿时长
13 weeks
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