利用指数、最优直方图思想和李克特分析加强概念清单分析

Dode Prenga, Elmira Kushta, Fatjon Musli
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引用次数: 0

摘要

自1992年引入“力量概念清单”以来,“力量概念清单”测试已被广泛用于测量概念知识和研究几乎所有学科和学习水平的教学问题。标准的概念清单分析包括定性测试的设计、测试的充分实现、校准程序和结果的综合分析。通常,CI测试的校准是通过Rasch社会计量技术进行的,该技术也用于计算知识的关键指标,如项目难度,学生能力等。虽然可以通过使用经过认证的专业CI测试来保证测试设计的质量,但在进入分析的最后一步之前,测试的统计充分性值得重点关注。此外,CI结果的分析可以通过考虑辅助工具和补充技术来推进。在这个框架中,我们建议强制执行测试索引有效性要求,以将CI结果限定为本地或全局。具体来说,如果检验指标符合指标理论提出的效度要求,则CI分析的结论对于抽取样本的整个总体是可以接受的。当测试指标超出效度范围,由于某些客观情况或研究细节而无法重新进行测试时,我们建议在现有的记录中注入一些新的记录,或者将不同样本的数据混合,直到新的指标在期望的范围内。使用这一方法,我们回顾了之前的FCI测试,这些测试最初旨在证明大流行结束期间在线学习引发的物理学科学习障碍。通过这一规范化程序,我们对大流行结束期间参加在线讲座的高中生对力学和电磁学的理解进行了可信的评估。此外,通过使用指标效度作为辅助工具,我们发现对于以物理为基础学科的分支机构入学学生的电磁学知识,缩短版的BEMA测试比相应的缩短版EMCI测试更好。接下来,我们使用从分布拟合过程中借鉴的最优直方图思想来确定学生解决某个CI测试的能力的自然水平。这项工作中提出的另一个有趣的建议是,将物理考试中常见错误的特设李克特量表分配与力学中基本常识混淆的FCI指定相结合,以确定它们在常见考试中的配对特征。我们相信本文提出的方法可以在更广泛的意义上改进CI分析。Doi: 10.28991/HEF-2023-04-01-08全文:PDF
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing Concept Inventory Analysis by Using Indexes, Optimal Histogram Idea, and the Likert Analysis
Since the introduction of the Force Concept Inventory (FCI) in 1992, the CI tests have been widely used for measuring conceptual knowledge and for studying teaching issues in almost all disciplines and levels of study. A standard concept inventory analysis includes the design of a qualitative test, adequate realization of testing, calibration procedure, and comprehensive analysis of its findings. Usually, the CI test calibration is carried out through the Rasch sociometric technique, which is also used for calculating crucial indicators of knowledge such as item difficulties, students’ abilities, and many more. Whereas the quality of the tests’ design can be guaranteed by using certified and professional CI tests, the statistical adequacy of the testing merits critical attention before going on to the final step of the analysis. Also, the analysis of CI outcomes can be advanced by contemplating auxiliary tools and complementary techniques. In this framework, we propose to enforce the test index validity requirement for qualifying the CI outcomes as local or global. Specifically, the conclusions of CI analysis are acceptable for the whole population from which the sample has been extracted if the test's indexes comply with the validity requirements provided by the index theory. In the case when test indexes are out of validity range and re-conducting them is impractical for some objective circumstances or research specifics, we suggest injecting some new records into the existing one or mixing the data gathered from different samples until the new indexes are in the desired range. Using this methodology, we have reviewed our previous FCI tests, which were initially intended to demonstrate the impairment of learning in the physics discipline triggered by online learning during the pandemic closure. Through this renormalization procedure, we obtained a credible assessment of the understanding of mechanics and electromagnetism in high school students who followed online lectures during the pandemic closure. Also, by using indexes’ validity as an auxiliary tool, we identified that for measuring the knowledge of electromagnetism in students enrolled in branches where physics is a basic discipline, a shortened version of the BEMA test was a better instrument than the corresponding shortened EMCI test. Next, we used the optimal histogram idea borrowed from distribution fitting procedures to identify the natural levels of students’ abilities for solving a certain CI test. Another intriguing proposal presented in this work consists of combining an ad-hoc Likert scale assignment for usual errors in physics exams with the FCI designation of the basic commonsense confusion in mechanics for identifying their pairing features in common exams. We believe that the methods proposed herein can improve CI analysis in more general senses. Doi: 10.28991/HEF-2023-04-01-08 Full Text: PDF
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