Literature Index

Displaying 231 - 240 of 3326

  • ACQUISITION OF NOTIONS OF STATISTICAL VARIATION BY IN-SERVICE TEACHERS

    Author(s):
    Ernesto Sánchez and Jaime García
    Year:
    2008
    Abstract:
    A study with six middle school teachers on the notion of variation in the task of prediction is hereby presented. The SOLO hierarchy in which notions like randomness, structure and variation are included is applied. Variation related activities used in this study arise from the questions used in research on statistical variation but were also adapted to include computer simulation. The notion of no singular event emerged as a key for evaluation of the transition from multi-structural to relational thinking.
    Location:
    http://www.ugr.es/~icmi/iase_study/Files/Contents.htm

  • Action research as a research methodology for the study of the teaching and learning of science

    Author(s):
    Feldman, A., Minstrell, J.
    Editors:
    Kelly, A., Lesh, R.
    Year:
    2000
    Abstract:
    This chapter addresses issues of action research from three perspectives. In the first section, what it means to engage in action research as a methodology for investigating teaching and learning in science education is overviewed and various conceptions of action research are explicitly made. The second perspective is that of an individual engaged in action research in the classroom to improve teaching, students' learning, and advance knowledge of the teaching and learning of physics. The third perspective is that of a facilitator of action research done by others. By providing views from these three perspectives, the concerns and issues of action research are addressed and helps readers develop their own understanding of what action research is and can be so that it can be used as a methodology for the study of teaching and learning in science.

  • Activities to Promote Understanding of Variability

    Author(s):
    delMas, R.
    Year:
    2005
    Abstract:
    Variability is a complex concept with many facets.<br>Students build up their understanding of variability over time.<br>Variability is used for descriptive purposes, but is also an essential concept for understanding inference (sampling distributions, confidence intervals, p-values, etc.)<br>Therefore, helping students develop an understanding of variability (how it is measured, what it represents, how it is represented, how to use it to make comparisons) may require revisiting the concept throughout the course.

  • Activities: Problem Solving with Computers

    Author(s):
    Channell, D. E.
    Year:
    1984
    Abstract:
    This activity consists of two problem situations, each illustrating how a computer can be used as a tool to assist students in solving mathematical problems. In one, numerous calculations are performed by the computer; the second uses a Monte Carlo model to simulate a physical action. (MNS)

  • Activity-Based Statistics, Computer Simulation, And Formal Mathematics

    Author(s):
    Engel, J.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    Instructional methods involving students in activities for exploring statistical concepts have proven to be highly effective. Formal mathematics, on the other hand, constitutes the basis of inductive reasoning. This paper reports on an "ActivStats" class for college math majors that teaches statistical concepts as well as mathematical foundations. Its basis is a four-step procedure comprising problem analysis, student activities, computer simulation, and formal mathematical analysis.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/5a3_enge.pdf

  • Adapting the Survey of Attitudes towards Statistics (SATS-36) for Estonian Secondary School Students

    Author(s):
    Carita Hommik and Piret Luik
    Year:
    2017
    Abstract:
    The purpose of this study is to adapt the Survey of Attitudes Towards Statistics (SATS-36) for Estonian secondary school students in order to develop a valid instrument to measure students’ attitudes within the Estonian educational context. The SATS-36 was administered to Estonian-speaking secondary school students before their compulsory statistics course. Because the fit indices for confirmatory factor analysis did not indicate a good fit, an exploratory factor analysis was conducted to find a new model. It validated a four-factor structure of the scale, excluding nine items. Good indices for both reliability and validity were obtained. Trends in secondary school students’ attitudes were also examined to investigate the effects of gender and gender combined with the level of education. Results showed that students tended to feel rather positively about statistics at the beginning of the course. All four factors displayed differences between boys and girls. Comparison of lower and upper secondary level students showed that students from the upper secondary level value statistics more highly. The authors recommend SATS with some small proposed changes to make it even more suitable for the secondary level.
    Location:
    http://iase-web.org/documents/SERJ/SERJ16(1)_Hommik.pdf

  • Addressing Cognitive And Situational Complexity In The Instruction And Assessment Of Statistical Reasoning

    Author(s):
    Derry, S. J., Levin, J. R., &amp; Spiro, R. J.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    The cognitive-theoretic instructional and assessment approaches described here represent our efforts to develop and measure students' abilities to reason spontaneously and flexibly with statistics in the context of complex real-world activity. We report results from two instructional projects based on situated cognition, in which students were taught statistical reasoning through guided participation in simulations of authentic professional activities requiring presentation and critique of statistical arguments. Although students' statistical reasoning improved in selected ways, the approach was costly and difficult to implement and sustain. In search of more practical and powerful approaches, current experiments are investigating whether instruction based on video technologies and Cognitive Flexibility Theory can speed development of ability to think flexibly with statistics while seeing interacting themes in real-world situations.
    Location:
    http://www.stat.auckland.ac.nz/~iase/publications/1/6d1_derr.pdf

  • Addressing Misconceptions in Learning Power Analysis

    Author(s):
    Yu Chong Ho, Pensabene, T., &amp; Behrens, J.
    Year:
    1993
    Abstract:
    The goal of this paper is to report on the development of a dynamic computer-based simulation of the concept of statistical power and the misconceptions students have regarding this concept. The paper will include three sections briefly summarized below: (1) considerations in constructing a dynamic computer-based simulation for statistical instruction; (2) discerning misconceptions and addressing their remediation and (3) plans for future development.
    Location:
    RISE

  • Adolescents' thinking about the risks of sexual behaviors.

    Author(s):
    de Bruin, W. B., Downs, J., &amp; Fischhoff, B.
    Editors:
    Lovett, M. C., &amp; Shah, P.
    Year:
    2007

  • Adults' statistical literacy: Meanings, components, responsibilities

    Author(s):
    Gal, I.
    Year:
    2002
    Abstract:
    Statistical literacy is a key ability expected of citizens in information-laden societies, and is often touted as an expected outcome of schooling and as a necessary component of adults' numeracy and literacy. Yet, its meaning and building blocks have received little explicit attention. This chapter proposes a conceptualization of statistical literacy and describes its key components. Statistical literacy is portrayed as the ability to interpret, critically evaluate, and communicate about statistical information and messages. It is argued that statistically literate behavior is predicated on the joint activation of five interrelated knowledge bases (literacy, statistical, mathematical, context, and critical), together with a cluster of supporting dispositions and enabling beliefs. Educational and research implications are discussed, and responsibilities facing educators, statisticians, and other stakeholders are outlined.

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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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