Journal Article•
A model of classroom research in action: Developing simulation activities to improve students’ statistical reasoning
About: This article is published in Journal of Statistics Education.The article was published on 1999-01-01 and is currently open access. It has received 230 citations till now. The article focuses on the topics: Action (philosophy).
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01 Jan 2004
TL;DR: This chapter discusses the development of Instructional Design for Supporting the Development of Students' Statistical Reasoning and research on Statistical Literacy, Reasoning, and Thinking.
Abstract: Statistical Literacy, Reasoning, and Thinking: Goals, Definitions, and Challenges.- Towards an Understanding of Statistical Thinking.- Statistical Literacy.- A Comparison of Mathematical and Statistical Reasoning.- Models of Development in Statistical Reasoning.- Reasoning about Data Analysis.- Learning to Reason About Distribution.- Conceptualizing an Average as a Stable Feature of a Noisy Process.- Reasoning About Variation.- Reasoning about Covariation.- Students' Reasoning about the Normal Distribution.- Developing Reasoning about Samples.- Reasoning about Sampling Distribitions.- Primary Teachers' Statistical Reasoning about Data.- Secondary Teachers' Statistical Reasoning in Comparing Two Groups.- Principles of Instructional Design for Supporting the Development of Students' Statistical Reasoning.- Research on Statistical Literacy, Reasoning, and Thinking: Issues, Challenges, and Implications.
477 citations
TL;DR: The authors provide an overview of current research on teaching and learning statistics, summarizing studies that have been conducted by researchers from different disciplines and focused on students at all levels, and suggest what can be learned from the results of each of these questions.
Abstract: Summary
This paper provides an overview of current research on teaching and learning statistics, summarizing studies that have been conducted by researchers from different disciplines and focused on students at all levels. The review is organized by general research questions addressed, and suggests what can be learned from the results of each of these questions. The implications of the research are described in terms of eight principles for learning statistics from Garfield (1995) which are revisited in the light of results from current studies.
418 citations
TL;DR: This paper defines statistical reasoning and reviews research on this topic, and a model of statistical reasoning is presented, and suggestions are offered for assessing statistical reasoning.
Abstract: This paper defines statistical reasoning and reviews research on this topic. Types of correct and incorrect reasoning are summarized, and statistical reasoning about sampling distributions is exami...
300 citations
TL;DR: Suggestions are given for direct instruction aimed at developing “habits of mind” for statistical thinking in students, and suggestions for assessing students' ability to think statistically.
Abstract: This paper focuses on a third arm of statistical development: statistical thinking. After surveying recent definitions of statistical thinking, implications for teaching beginning students (includi...
267 citations
Journal Article•
TL;DR: The CAOS test as discussed by the authors is designed to measure students' conceptual understanding of important statistical ideas across three years of revision and testing, content validation, and realiability analysis, and results reported from a large scale class testing and item responses are compared from pretest to posttest in order to learn more about areas in which students demonstrated improved performance from beginning to end of the course, as well as areas that showed no improvement or decreased performance.
Abstract: This paper describes the development of the CAOS test, designed to measure students’ conceptual understanding of important statistical ideas, across three years of revision and testing, content validation, and realiability analysis. Results are reported from a large scale class testing and item responses are compared from pretest to posttest in order to learn more about areas in which students demonstrated improved performance from beginning to end of the course, as well as areas that showed no improvement or decreased performance. Items that showed an increase in students’ misconceptions about particular statistical concepts were also examined. The paper concludes with a discussion of implications for students’ understanding of different statistical topics, followed by suggestions for further research.
251 citations
References
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TL;DR: In this paper, a general model of conceptual change is proposed, which is largely derived from current philosophy of science, but which they believe can illuminate * This model is partly based on a paper entitled "Learning Special Relativity: A Study of Intellectual Problems Faced by College Students,” presented at the International Conference Celebrating the 100th Anniversary of Albert Einstein, November 8-10, 1979 at Hofstra University.
Abstract: It has become a commonplace belief that learning is the result of the interaction between what the student is taught and his current ideas or concepts.’ This is by no means a new view of learning. Its roots can be traced back to early Gestalt psychologists. However, Piaget’s (1929, 1930) early studies of children’s explanations of natural phenomena and his more recent studies of causality (Piaget, 1974) have perhaps had the greatest impact on the study of the interpretive frameworks students bring to learning situations. This research has led to the widespread study of students’ scientific misconceptions.2 From these studies and, particularly, from recent work by researchers such as Viennot ( 1979) and Driver (1 973), we have developed a more detailed understanding of some of these misconceptions and, more importantly, why they are so “highly robust” and typically outlive teaching which contradicts them (Viennot, 1979, p. 205). But identifying misconceptions or, more broadly speaking, “alternative frameworks” (Driver & Easley, 1978), and understanding some reasons for their persistence, falls short of developing a reasonable view of how a student’s current ideas interact with new, incompatible ideas. Although Piaget (1974) developed one such theory, there appears to be a need for work which focuses “more on the actual content of the pupil’s ideas and less on the supposed underlying logical structures” (Driver & Easley, 1978, p. 76). Several research studies have been performed (Nussbaum, 1979; Nussbaum & Novak, 1976; Driver, 1973; Erickson, 1979) which have investigated “the substance of the actual beliefs and concepts held by children” (Erickson, 1979, p. 221). However, there has been no well-articulated theory explaining or describing the substantive dimensions of the process by which people’s central, organizing concepts change from one set of concepts to another set, incompatible with the first. We believe that a major source of hypotheses concerning this issue is contemporary philosophy of science, since a central question of recent philosophy of science is how concepts change under the impact of new ideas or new information. In this article we first sketch a general model of conceptual change which is largely derived from current philosophy of science, but which we believe can illuminate * This article is partly based on a paper entitled “Learning Special Relativity: A Study of Intellectual Problems Faced by College Students,” presented at the International Conference Celebrating the 100th Anniversary of Albert Einstein, November 8-10, 1979 at Hofstra University.
5,052 citations
TL;DR: In this paper, subjects supporting and opposing capital punishment were exposed to two purported studies, one seemingly confirming and one seemingly disconfirming their existing beliefs about the deterrent efficacy of the death penalty.
Abstract: People who hold strong opinions on complex social issues are likely to examine relevant empirical evidence in a biased manner. They are apt to accept "confirming" evidence at face value while subjecting "discontinuing" evidence to critical evaluation, and as a result to draw undue support for their initial positions from mixed or random empirical findings. Thus, the result of exposing contending factions in a social dispute to an identical body of relevant empirical evidence may be not a narrowing of disagreement but rather an increase in polarization. To test these assumptions and predictions, subjects supporting and opposing capital punishment were exposed to two purported studies, one seemingly confirming and one seemingly disconfirming their existing beliefs about the deterrent efficacy of the death penalty. As predicted, both proponents and opponents of capital punishment rated those results and procedures that confirmed their own beliefs to be the more convincing and probative ones, and they reported corresponding shifts in their beliefs as the various results and procedures were presented. The net effect of such evaluations and opinion shifts was the postulated increase in attitude polarization. The human understanding when it has once adopted an opinion draws all things else to support and agree with it. And though there be a greater number and weight of instances to be found on the other side, yet these it either neglects and despises, or else by some distinction sets aside and rejects, in order that by this great and pernicious predetermination the authority of its former conclusion may remain inviolate. (Bacon, 1620/1960)
3,808 citations
Book•
01 Jan 1985
TL;DR: A teacher's guide to classroom research is given in the fifth edition of the book as mentioned in this paper, with a focus on the importance of classroom observation and teaching and learning as the heartland of classroom research.
Abstract: Preface to the fifth edition Acknowledgements A teacher's guide to classroom research Classroom research in action Why classroom research by teachers? Action research and classroom research by teachers Developing a focus Principles of classroom observation Methods of observation in classroom research Data gathering Analysing classroom research data Reporting classroom research Teaching and learning as the heartland of classroom research Teacher research, school improvement and system reform Bibliography Index
1,164 citations
01 Apr 1982
TL;DR: In this paper, Nisbett et al. pose the question: "How proficient are we, as laypeople, at assessing the empirical covariations presented by experiential evidence?" The answer to the proficiency question is apt to be far from a simple one.
Abstract: The flow of social experience frequently challenges us to recognize empirical covariations. Sometimes, these covariations are merely another test of our powers of observation and are of no immediate practical concern to us. At other times – for example, when those covariations involve early symptoms of problems and later manifestations, or behavioral strategies employed and outcomes obtained, or relatively overt characteristics of people or situations and relatively covert ones – such detection abilities may help to determine our success in adapting to the demands of everyday social life. More generally, covariation detection will play a large role in our continuing struggle as “intuitive scientists” (see Nisbett & Ross, 1980; Ross, 1977, 1978) to evaluate and update the hypotheses we hold about ourselves, our peers, and our society. An obvious question therefore presents itself: How proficient are we, as laypeople, at assessing the empirical covariations presented by experiential evidence? Before proceeding to discuss past or present research, we should note that everyday observation provides a great deal of relevant evidence; and it hints that the answer to the proficiency question is apt to be far from a simple one. On the one hand, both the generally adaptive nature of social behavior and the generally harmonious quality of social interaction leave little doubt that the participants in our culture possess many profound insights about behavioral causes and consequences.
301 citations
TL;DR: A way computer simulations can be used to address the problem of teaching for conceptual change and understanding by embedding the relevant physical laws directly into the program code and allowing for genuine discoveries.
Abstract: In this paper, we consider a way computer simulations can be used to address the problem of teaching for conceptual change and understanding. After identifying three levels of understanding of a natural phenomenon (concrete, conceptual, and metaconceptual) that need to be addressed in school science, and classifying computer model systems and simulations more generally in terms of the design choices facing the programmer, we argue that there are ways to design computer simulations that can make them more powerful than laboratory models. In particular, computer simulations that provide an explicit representation for a set of interrelated concepts allow students to perceive what cannot be directly observed in laboratory experiments: representations for the concepts and ideas used for interpreting the experiment. Further, by embedding the relevant physical laws directly into the program code, these simulations allow for genuine discoveries. We describe how we applied these ideas in developing a computer simulation for a particular set of purposes: to help students grasp the distinction between mass and density and to understand the phenomenon of flotation in terms of these concepts. Finally, we reflect on the kinds of activities such conceptually enhanced simulations allow that may be important in bringing about the desired conceptual change.
84 citations