Literature Index

Displaying 1551 - 1560 of 3326
  • Author(s):
    Shaughnessy, J. M.
    Editors:
    A.P. Shulte
    Year:
    1981
    Abstract:
    Some of our misconceptions of probability may occur just because we haven't studied much probability. However, there is considerable recent evidence to suggest that some misconceptions of probability are of a psychological sort. Mere exposure to the theoretical laws of probability may not be sufficient to overcome misconceptions of probability. Cohen and Hansel [20], Edwards [29], and Kahneman and Tversky [63-66] are among those psychologists who have investigated the understanding of probability from a psychological point of view. The work of Daniel Kahneman and Amos Tversky is especially fascinating, for the attempt to categorize certain types of misconceptions of probability which they believe are systematic and even predictable. Kahneman and Tversky claim that people estimate complicated probabilities by relying on certain simplifying techniques. Two of the techniques they have identified are called representativeness and availability. We shall explore these two techniques in more detail and discuss some implications for teaching probability and statistics in the schools.
  • Author(s):
    Falk, R.
    Year:
    1986
    Abstract:
    The purpose of the present paper is to further clarify the misunderstandings concerning the meaning of significant test results, and to reassess the value of this statistical procedure for the teaching of scientific reasoning and for the analysis of research results.
  • Author(s):
    Haller, H., & Krauss, S.
    Year:
    2002
    Abstract:
    The use of significance tests in science has been debated from the invention of thesetests until the present time. Apart from theoretical critiques on their appropriateness forevaluating scientific hypotheses, significance tests also receive criticism for inviting mi-sinterpretations. We presented six common misinterpretations to psychologists whowork in German universities and found out that they are still surprisingly widespread -even among instructors who teach statistics to psychology students. Although these mi-sinterpretations are well documented among students, until now there has been littleresearch on pedagogical methods to remove them. Rather, they are considered "hardfacts" that are impervious to correction. We discuss the roots of these misinterpretationsand propose a pedagogical concept to teach significance tests, which involves explainingthe meaning of statistical significance in an appropriate way
  • Author(s):
    Shaughnessy, J. M.
    Editors:
    Biddulph, F. & Carr , K.
    Year:
    1997
    Abstract:
    Reflecting on a body of research work can sometimes lead to the recognition of areas of opportunity for research that have gone largely unnoticed. In this paper we consider three such opportunities in the area of research on the teaching and learnig of probability and statistics: i) Following up on students' initial thinking to watch for future transitions; ii) Investigating students' thinking on variability; and iii) Posing research questions that begin with what students can do rather than pointing out what they cannot do. Situations from research tasks, past and future, are used as starting points for the discussion.
  • Author(s):
    Oviedo, M. C. N., Clement, J.
    Year:
    2003
    Abstract:
    The purpose of this study is to develop a theoretical framework for describing different teaching strategies that can foster student model construction in large group discussions. Such a framework is necessary for developing new instructional principles about how to build mental models in large classroom settings. This particular paper focuses on a mode of interaction call model competition as one possible strategy. The teacher has an opportunity to promote model competition when the students contribute to a discussion with ideas that are contradictory to each other. The presence of these different kinds of ideas fosters dissatisfaction in the students' minds that can be productive. We follow the strategies a teacher uses to support this and other important modes of learning, such as model evolution, in a case study of classroom learning in the area of respiration.<br>We believe that the teacher played a key role during the teacher/student co-construction process described in the present study. The teacher particpated by constantly diagnosing the students' ideas and attemping to introduce dissatisfaction by suggesting constraints that led the students to evaluate and modify their ideas, producing cycles of model construction and criticism. In this way she was able to guide students toward targeted content goals. The learning model we develop includes nested teacher-student interaction organization patterns that the teacher used in order to encourage the students to disconfirm, recombine, restructure, or tune their ideas and to generate successive intermediate mental models. These patterns have been analyzed from the perspective of a theoretical framework of model construction theory. We believe that this framework can provide a set of lenses that complements other cognitive and sociological frameworks for analyzing classroom discussions.
  • Author(s):
    Brigitte Chaput, Jean Claude Girard and Michel Henry
    Year:
    2008
    Abstract:
    In France, recent mathematics curricula reinforce the teaching of statistics and probability. They recommend starting with an experimental approach introducing the observation of sampling fluctuations and the construction of random experiment simulations in order to prepare students for theory. This approach raises the problem of the didactical practice of random experiment modeling and simulations.
  • Author(s):
    Wisenbaker, J. M., &amp; Scott, J. S.
    Year:
    1997
    Abstract:
    This report presents a path model of students' attitudes and achievement in statistics; it also presents correlations among attitudinal measures and correlations between attitudinal measures and test performance for both graduate students and undergraduate students.
  • Author(s):
    Scott, J. S.
    Editors:
    Wisenbaker, J.
    Year:
    2001
    Abstract:
    This study examined the role of attitudes toward statistics, mathematics anxiety, mathematics attitude, mathematics background, demographic variables, and performance for students in an undergraduate introductory statistics course. The study participants were 155 students enrolled in five classes of introductory statistics at a four year college in metropolitan Atlanta. Using a self-selected ID to assure anonymity, the students completed the Survey of Attitudes Toward Statistics (SATS) at the beginning and end of the term. The SATS provides scale scores for Affect, Cognitive Competence, Value, and Difficulty. They also completed a mathematics attitude and anxiety measure, a demographic questionnaire, and a mathematics history. Students revealed their ID's after completion of the study. This allowed performance data from the course and prerequisite mathematics information to be linked with other student data. Students participating in this study had fairly positive attitudes concerning their Cognitive Competence and the Value of statistics at the beginning of the course. Their feeling of Affect was almost neutral and they expected the course to be somewhat difficult. Statistics attitudes were slightly less positive at the end of course. There were no statistically significant differences in attitudes between first time enrollees and those who were repeating the course or between students who did and did not complete the course. Pre-course SATS attitudes were generally not related to gender or age of the students nor to the years of high school mathematics or number of college mathematics courses. All of the SATS subscales were correlated with student grades in the prerequisite course. Pre-course Affect and Cognitive Competence scales were highly correlated to mathematics attitude, math self-concept and statistics self-confidence and moderately correlated with mathematics anxiety. Path analysis was used to develop a conceptual model for statistics attitude and performance in the course using mathematics attitude, mathematics anxiety, and prequisite grade as the exogeneous variables. In the path model, performance in the course was not influenced by either the pretest or posttest SATS. Performance during the statistics course did affect the posttest SATS scores.
  • Author(s):
    Lehrer, R. &amp; Schauble, L.
    Year:
    2004
    Abstract:
    This design study tracks the development of student thinking about natural variation as late elementary grade students learned about distribution in the context of modeling plant growth at the population level. The data-modeling approach assisted children in coordinating their understanding of particular cases with an evolving notion of data as an aggregate of cases. Students learned to "read" shapes of distributions as signatures of prospective mechanisms of plant growth and conducted sampling investigations to represent repeated growth. These investigations, in turn, supported students' interpretations of the effects of added light and fertilizer. The authors argue for both the feasibility and importance of tools such as distribution and inference for supporting education that builds on children's own investigations of the world. (Fall 2004)
  • Author(s):
    Joachim Engel, Peter Sedlmeier and Claudia W&ouml;rn
    Year:
    2008
    Abstract:
    The idea of data being a mixture of signal and noise is perhaps one of the most fruitful and fundamental ideas of statistics. To enable future mathematics teachers to educate students to become statistically literate, we propose an integrative approach connecting central topics of school mathematics with the signal-noise idea. A course on modeling functional relationships-a core topic in any mathematics curriculum-confronts students with the signal-noise idea when looking at the deviation between model and data. We provide empirical evidence that students of such a course acquire implicitly important statistical thinking skills.

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