A CONCEPTUAL FRAMEWORK FOR FORMATIVE ASSESSMENT IN LARGE-ENROLLMENT INTRODUCTORY STATISTICS

Q3 Social Sciences Statistics Education Research Journal Pub Date : 2023-05-16 DOI:10.52041/serj.v22i1.99
KimberLeigh Felix Hadfield
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Abstract

Implementing formative assessment in large-enrollment statistics courses is recommended by mathematics and statistics education communities. Yet research maintains that large-enrollment courses employ few, if any, formative assessments, exacerbating negative attitudes toward statistics and low student achievement. This conceptual essay applies an andragogical approach to the theories of self-efficacy, self-regulation, and formative assessment. A literature review explicates the associations between formative assessment with feedback and reassessment with student attitudes and achievement. Resulting from the review, a conceptual framework is proposed that illustrates the relations between the elements of formative assessment cycles and student attitudes and achievement. The implications of this conceptual framework suggest a comprehensive transformation of assessment practices to provide pathways for student success in statistics courses.
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大招生入门统计中形成性评估的概念框架
在大招生统计课程中实施形成性评价是数学界和统计教育界所推荐的。然而,研究表明,招生人数众多的课程很少(如果有的话)采用形成性评估,这加剧了对统计数据的负面态度和学生成绩低下的问题。这篇概念性文章应用了一种心理学的方法来研究自我效能、自我调节和形成性评估。一篇文献综述阐明了反馈形成性评价和再评价与学生态度和成绩之间的关系。根据审查结果,提出了一个概念性框架,说明形成性评估周期要素与学生态度和成绩之间的关系。这一概念框架的含义建议全面转变评估实践,为学生在统计学课程中取得成功提供途径。
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来源期刊
Statistics Education Research Journal
Statistics Education Research Journal Social Sciences-Education
CiteScore
1.30
自引率
0.00%
发文量
46
期刊介绍: SERJ is a peer-reviewed electronic journal of the International Association for Statistical Education (IASE) and the International Statistical Institute (ISI). SERJ is published twice a year and is free. SERJ aims to advance research-based knowledge that can help to improve the teaching, learning, and understanding of statistics or probability at all educational levels and in both formal (classroom-based) and informal (out-of-classroom) contexts. Such research may examine, for example, cognitive, motivational, attitudinal, curricular, teaching-related, technology-related, organizational, or societal factors and processes that are related to the development and understanding of stochastic knowledge. In addition, research may focus on how people use or apply statistical and probabilistic information and ideas, broadly viewed. The Journal encourages the submission of quality papers related to the above goals, such as reports of original research (both quantitative and qualitative), integrative and critical reviews of research literature, analyses of research-based theoretical and methodological models, and other types of papers described in full in the Guidelines for Authors. All papers are reviewed internally by an Associate Editor or Editor, and are blind-reviewed by at least two external referees. Contributions in English are recommended. Contributions in French and Spanish will also be considered. A submitted paper must not have been published before or be under consideration for publication elsewhere.
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