Arjen de Vetten, R. Keijzer, J. Schoonenboom, B. van Oers
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PRE-SERVICE PRIMARY SCHOOL TEACHERS' KNOWLEDGE DURING TEACHING INFORMAL STATISTICAL INFERENCE
The study reported in this article investigated the appropriateness of Mathematical Knowledge in Teaching of three pre-service primary school teachers (PSTs), teaching an informal statistical inference (ISI) lesson to primary school students. Using an ISI framework and the Knowledge Quartet framework., the presence and appropriateness of the PSTs’ teaching actions were coded and categorized. The results showed that PSTs were consciously engaged in making inferences based on sample data. The PSTs struggled to correctly interpret students’ conceptual input and to explain ISI, in particular, how generalizing from a sample is possible. Teacher education should focus on how PSTs can foster students’ understanding of the logic of drawing conclusions about a population based on a sample.
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.