Literature Index

Displaying 731 - 740 of 3326
  • Author(s):
    Gil, E., Ben-Zvi, D., & Apel, N.
    Editors:
    R. Leikin
    Year:
    2008
  • Author(s):
    Ben-Zvi, D., Gil#, E., & Apel#, N.
    Editors:
    R. Leikin, A. Berman & B. Koichu
    Year:
    2009
    Abstract:
    Statistics is a discipline in its own right rather than a branch of mathematics, and the knowledge needed to solve statistical problems is likely to differ from the knowledge needed to solve mathematical problems. Therefore, a framework that characterizes creative performance in learning to reason about informal statistical inference is essential. In this paper we present an initial framework to assess creative praxis of primary school students involved in learning informal statistical inference in statistical inquiry settings. In building the suggested framework, we adapt the three common characteristics of creativity in the mathematics education literature, namely, fluency, flexibility, and novelty, to the specifics of learning statistics. We use this framework to capture creative praxis of three sixth grade students in a 60-min statistical inquiry episode. The episode analysis illustrates the strengths and limitations of the suggested framework. We finally consider briefly research and practical issues in assessing and fostering creativity in statistics learning.
  • Author(s):
    GAL, Iddo
    Year:
    2007
    Abstract:
    What is important to assess in statistics education? Usually the answer is derived from course content, i.e., teachers assess key elements of what they have taught. This talk focuses on critical statistical skills needed by adults as part of general everyday or workplace functioning. The talk is motivated by emerging plans by the Organisation for Economic Cooperation and Development (OECD) for a new Program for International Assessment of Adult Competencies (PIAAC) in coming years. PIAAC will be somewhat similar in general terms to the PISA assessment program of high-school students which is now implemented in dozens of countries on a cyclical basis, but will focus on the skills of adults who are outside formal schooling, and on their economic and social participation.<br>One of the several domains assessed in PIAAC will be numeracy, and one of the strands in it will be knowledge of statistics (data and chance). We need to identify core knowledge areas expected of adults in data/chance which are valued enough to spend precious assessment time on in multiple countries, using realistic stimuli or authentic tasks which are likely to arise in the lives of many adults. The talk will present some of the design principles of the numeracy assessment in PIAAC, and solicit suggestions for possible assessment tasks. The discussion will emphasize the need for linking class assessments and real-life demands, in order to enhance learners' ability to transfer learned skills and cope effectively with functional statistical demands in the real world.
  • Author(s):
    Lesser, L. M.
    Year:
    2007
    Abstract:
    Despite the dearth of literature specifically on teaching statistics using social justice, there is precedent in the more general realm of teaching using social justice, or even in teaching mathematics using social justice. This article offers an overview of content examples, resources, and references that can be used in the specific area of statistics education. Philosophical and pedagogical references are given, definitional issues are discussed, potential implementation challenges are addressed, and a substantial bibliography of print and electronic resources is provided.
  • Author(s):
    Lavigne, N. C., &amp; Lajoie, S. P.
    Year:
    1998
    Abstract:
    This paper describes an educational tool, Critiquing Statistics, that is designed to foster and facilitate reasoning about statistical investigations involving descriptive statistics (e.g., measures of central tendency and variability) in middle school. This tool is being developed as part of a large scale research project emphasizing statistical investigation where students generate a research question; collect, analyze, interpret, and represent data; and communicate results to peers. However, the objective of this particular tool is to provide students with a critiquing activity that enhances students reflection on their own statistical investigations and those of others. In this way, Critiquing Statistics is intended to promote self-assessment and learning as well as reasoning. Students are given opportunities to enhance their reasoning skills by critiquing statistical investigations performed by former students, after having conducted their own research. Discussions about what could be done better in the statistics projects is facilitated through technology that allows students to view digitized videotapes as well as appropriate data and graphics files. These discussions are guided by an understanding of assessment criteria for investigations, which the Critiquing Statistics environment opens up for public viewing. Students engage in small group discussions of these criteria and apply them to the projects they are required to assess. This activity thereby promotes dialogue about the appropriateness of statistical methods, data collection procedures, graphical representations, analyses, and interpretation of data. Such discussions can be used to build a community of scientific reasoners who share their knowledge, reasoning, and argumentation.
  • Author(s):
    Haseman, A. L.
    Year:
    1999
    Abstract:
    This qualitative study examined students' experiences with the constructivist approach to learning in an introductory statistics university course. An overview of students' difficulties and frustrations were addressed for three pedagogical aspects. Findings suggested that students' difficulties were related to their epistemological beliefs of the nature of statistical knowledge, the simplicity of knowledge, and the source of knowledge. Therefore, students' frustrations seems to be connected to the agreement between their epistemological beliefs and those of the professor.
  • Author(s):
    Lehrer, R., Schauble, L.
    Editors:
    Sawyer, R. K.
    Year:
    2006
    Abstract:
    Because we focus on modeling in school students, rather than in professional scientists, we devote considerable effort to understanding the development of model-based reasoning and to forms of practice that support this form of reasoning. When thinking about the developmental roots for modeling, we find it useful to recall that at its most basic level, a model is an analogy.
  • Author(s):
    Wright, G. N., &amp; Phillips, L. D.
    Year:
    1980
    Abstract:
    This study reviews research on cultural differences in "probabilistic thinking" and presents some intra- and inter-cultural findings. Strong differences are shown to exist between people raised under Asian and British cultures on measures of this ability. These differences were found to out-weigh any influence of subculture, religion, occupation, arts/science orientation and sex. Generally, Asians were found to adopt a less finely differentiated view of uncertainty both numerically and verbally than did the British sample. Possible antecedents of these differences are outlined, and cultural differences in probabilistic thinking are shown to be compatible with descriptions of cultural differences in business decision making. It is argued that there are qualitative cultural differences in ways of dealing with uncertainty.
  • Author(s):
    Gal, I., &amp; Garfield, J. B.
    Editors:
    Gal, I., &amp; Garfield, J. B.
    Year:
    1997
    Abstract:
    This chapter frames the main issues with which this volume deals. The chapter examines common goals for statistics education at both precollege (school) and college levels, describes the resulting challenges for assessment in statistics education, and outlines the main issues addressed by each of the chapters in this volume. Finally, needs for future research and development are discussed.
  • Author(s):
    Borovcnik, M. G.
    Editors:
    Vere-Jones, D., Carlyle, S., &amp; Dawkins, B. P.
    Year:
    1991
    Abstract:
    Data analysis can play an important role in bridging the gab between the world of mathematics and the student's world experience. Students study functions in class, but seldom have the opportunity to see these functions and their interactions exhibited in the world around them. As the students study the behavior of functions in calculus and precalculus courses, they learn how things should happen in theory. Through data analysis, the theory can be motivated and realised in the actual. The principles of curve fitting, re-expression, and residual analysis, offer a very exciting and enlightening basis for the motivation and derivation of many of the functions and functional concepts taught in high school algebra and in calculus. The Mathematics Department at the North Carolina School of Science and Mathematics has created, tested, and published an innovative data-driven precalculus text and is presently writing a calculus course involving many laboratory experiences from which the examples in this article are taken.

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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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