Designing open questions for the assessment of conceptual understanding

N. Broers
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Abstract

The theory of statistics is composed of highly abstract propositions that are linked in multiple ways. Both the abstraction level and the cumulative nature of the subject make statistics a difficult subject. A diversity of didactic methods has been devised to aid the student in the effort to master statistics, one of which is the method of propositional manipulation (MPM). Based on this didactic method, a corresponding assessment method has been developed. Basically, in using MPM for assessment purposes, the student is instructed to construct arguments using subsets of elementary propositions. In effect, the assessment procedure demands the student to display knowledge of the interrelationships between the propositions in a particular subset. Analysis of the student responses allows for scoring purely propositional knowledge, as well as conceptual understanding. In this paper we discuss research on the effectiveness of this assessment method, relative to assessment of conceptual understanding using concept mapping.
设计开放性问题以评估概念理解能力
统计理论是由高度抽象的命题组成的,这些命题以多种方式联系在一起。这门学科的抽象性和累积性都使统计学成为一门困难的学科。为了帮助学生努力掌握统计学,已经设计了多种教学方法,其中一种是命题操作(MPM)方法。在这种教学方法的基础上,开发了相应的评价方法。基本上,在使用MPM进行评估时,学生被指示使用基本命题的子集来构建论点。实际上,评估过程要求学生展示特定子集中命题之间相互关系的知识。对学生回答的分析允许对纯粹的命题知识以及概念理解进行评分。在本文中,我们讨论了这种评估方法的有效性研究,相对于使用概念映射来评估概念理解。
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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