Journal Article

  • This paper starts by assessing deficiencies in teaching statistics before summarizing research<br>that has focused on pupils' misconceptions of probability. In contrast, in previous research has explored what<br>pupils of age 11-12 years do know and can construct, given access to a carefully designed environment.<br>These pupils judged randomness according to unpredictability, lack of pattern in results, lack of control over<br>outcomes and fairness, as indeed would experts. However, it was only through interaction with a virtual<br>environment, ChanceMaker that the pupils began to express situated meanings for aggregated long-term<br>randomness. That data is then re-analyzed in order to reflect upon the design decisions that shaped the<br>environment itself. Four main design heuristics are identified and elaborated: testing personal conjectures,<br>building on pupil knowledge, linking purpose and utility, fusing control and representation. It is conjectured<br>that these heuristics are of wider relevance to teachers and lecturers, who aspire to shape the experience of<br>young and na&iuml;ve probabilists through their actions as designers of tasks and pedagogical settings.

  • This paper addresses a question identified by Graham Jones: what are the connections made by<br>students in the middle years of schooling between classical and frequentist orientations to probability? It does<br>so based on two extended lessons with a class of Grade 5/6 students and in-depth interviews with eight<br>students from the class. The Model 1 version of the software TinkerPlots was used in both settings to simulate<br>increasingly large samples of random events. The aim was to document the students' understanding of<br>probability on a continuum from experimental to theoretical, including consideration of the interaction of<br>manipulatives, the simulator, and the law of large numbers. A cognitive developmental model was used to<br>assess students' understanding and recommendations are made for classroom interventions.

  • This paper considers how probability is now taught in England and the way that the curriculum<br>reflects key research ideas from the last few decades. Links are made to work undertaken in probability<br>education and the way that challenges in the book, Chance Encounters, have been met. This is based on the<br>current curriculum and also the performance of children in tests. The key question considered is the extent to<br>which the teaching of probability has changed over the last twenty years. The conclusion notes that there is<br>some way to go in ensuring children are well versed in probability.

  • There is evidence that students have prior conceptions about fairness and these conceptions appear to have the potential to interfere with the learning of statistics topics such as simulation with physical manipulatives, surveys, randomized experiments, and expected value, as well as the understanding of words such as bias or discrimination. Because of this, it is strongly recommended that statistics instructors explicitly acknowledge and take into account the role that student views of fairness play. Related to equity and fairness beliefs is the possible interaction of cultural background with the learning of specific topics, and empirical evidence (p &lt; .01) suggests that this can happen with certain populations when using the common courtroom metaphor to illustrate hypothesis testing

  • Qualitative methods have become common in statistics education research, but<br><br>questions linger about their role in scholarship. Currently, influential policy<br><br>documents lend credence to the notion that qualitative methods are inherently inferior<br><br>to quantitative ones. In this paper, several of the questions about qualitative research<br><br>raised in recent policy documents in the U.S. are examined. Each question is<br><br>addressed by drawing upon examples from existing statistics education research. The<br><br>examples illustrate that qualitative methods can be used profitably to study statistical<br><br>teaching and learning, and that in some cases qualitative methods are preferable to<br><br>quantitative ones. By using the examples presented, qualitative researchers in<br><br>statistics education can begin to more strongly situate their work within scholarly<br><br>discourse about empirical research

  • Our research in statistical cognition uses both qualitative and quantitative methods. A mixed method approach makes our research more comprehensive, and provides us with new directions, unexpected insights, and alternative explanations for previously established concepts. In this paper, we review four statistical cognition studies that used mixed methods and explain the contributions of both the quantitative and qualitative components. The four studies investigated concern statistical reporting practices in medical journals, an intervention aimed at improving psychologists' interpretations of statistical tests, the extent to which interpretations improve when results are presented with confidence intervals (CIs) rather than p-values, and graduate students' misconceptions about CIs. Finally, we discuss the concept of scientific rigour and outline guidelines for maintaining rigour that should apply equally to qualitative and quantitative research.

  • This paper presents a qualitative case study of statistical practice in a universitybased statistical consulting centre. Naturally occurring conversations and activities<br><br>in the consulting sessions provided opportunities to observe questions, problems, and<br><br>decisions related to selecting, using, and reporting statistics and statistical techniques<br><br>in research. The consulting sessions provided simultaneous opportunities for<br><br>consultants and clients to learn about using statistics in research. Consistent with<br><br>contemporary theories that emphasize social dimensions of learning, major themes<br><br>relate to (a) types of clients and consulting interactions, (b) disciplinary and<br><br>statistical expertise, and (c) the role of material objects and representations.<br><br>Evidence shows that consultants and clients learned during the consulting sessions<br><br>and that the statistical consulting centre contributed positively to teaching and<br><br>research at the university.

  • This study seeks to describe the subject matter knowledge needed for teaching<br><br>statistical association at the secondary level. Taking a practice-based qualitative<br><br>approach, three experienced teachers were observed as they taught statistical<br><br>association and interviewed immediately following each observation. Records of<br><br>practice were assembled to create a compilation document to recreate each of the<br><br>fifty observed class sessions along with related materials including textbook pages<br><br>and student work. Analysis of the compilation documents focused on the demands<br><br>upon teachers' subject matter knowledge involved in the practice of teaching.<br><br>Findings regarding the knowledge required for teaching correlation coefficient are<br><br>highlighted, including its computation, interpretation, sensitivity, estimation, and<br><br>related terminology.

  • To capture aspects of pedagogical content knowledge (PCK) not illuminated in an<br><br>earlier written survey, an interview protocol was used with 40 middle school teachers.<br><br>The scenarios were intended to elicit teachers' understanding of the big ideas, ability<br><br>to anticipate students' answers, and intervention strategies for the classroom. This<br><br>was expected to be a straight-forward journey based on teachers' responses to three<br><br>context-based scenarios regarding students' answers to questions. Instead we were<br><br>surprised by teachers' responses that revealed their perceptions that their experiences<br><br>teaching mathematics and teaching statistics are very different. This led to further<br><br>analysis of the PCK tasks and a suggestion that the mathematics embedded in the<br><br>tasks was sometimes an impediment for the teachers, especially in relation to<br><br>intervention strategies in the classroom.

  • For over thirty years, statistical education has fought for a "pedagogy of proximity."<br><br>But if this seems to bring greater success, it does not guarantee the understanding of<br><br>statistical concepts. An analysis of an experiment by Gattuso &amp; Mary (2003, 2005),<br><br>and an observational study made by the author, highlight the phenomenon of<br><br>"cognitive isolation." This underlines the importance of the learners' views of<br><br>statistics. The work of Reid and Petocz (2002) corroborates this and provides more<br><br>insight into the necessity of an exogenous disturbance to learning so that it is fully<br><br>realized. Methodologically, it emerges that qualitative methods have their full place in<br><br>statistical education research, including as an opportunity to reassess the research<br><br>objectives.

Pages

register