PREPARING PRESERVICE TEACHERS TO TEACH PROBABILITY AND STATISTICS TO EARLY LEARNERS: A SYSTEMATIC REVIEW

Q3 Social Sciences
D. Denton
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引用次数: 0

Abstract

Various sources suggest preparing teachers of early- or primary-age students to teach probability and statistics involves various challenges. Some of the approaches researchers take for resolving these challenges include developing preservice teacher content knowledge, pedagogical knowledge, as well as providing other opportunities to learn. Various sources also suggest that research in this area is missing or underemphasizing some components. The systematic review undertaken here considers this question by comparing extant literature to teacher preparation standards. Results show that studies emphasize development of probability and statistics concepts and procedures, and an underrepresentation of development of pedagogical knowledge, learning from school experiences, such as student teaching, and reflection on practice.
职前教师向早期学习者教授概率和统计学的准备工作:系统综述
各种来源表明,让幼儿或小学生的老师教授概率和统计学涉及到各种挑战。研究人员解决这些挑战的一些方法包括开发职前教师内容知识、教学知识,以及提供其他学习机会。各种来源也表明,这一领域的研究缺少或没有充分重视某些组成部分。这里进行的系统综述通过将现有文献与教师准备标准进行比较来考虑这个问题。结果表明,研究强调概率和统计学概念和程序的发展,而在教学知识的发展、从学校经验中学习(如学生教学)和实践反思方面的代表性不足。
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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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