Literature Index

Displaying 3041 - 3050 of 3326
  • Author(s):
    Cliff Konold , Anthony Harradine and Sibel Kazak
    Year:
    2007
    Abstract:
    In current curriculum materials for middle school students in the US, data and chance are considered as separate topics. They are then ideally brought together in the minds of high school or university students when they learn about statistical inference. In recent studies we have been attempting to build connections between data and chance in the middle school by using a modeling approach made possible by new software capabilities that will be part of TinkerPlots 2.0 (TinkerPlots is published by Key Curriculum Press and has been developed with grants from the National Science Foundation (ESI-9818946, REC-0337675, ESI-0454754). Opinions expressed here are our own and not necessarily those of the Foundation.). Using a new Sampler object, students build "factories" to model not only prototypical chance events, but also distributions of measurement errors and of heights of people. We provide the rationale for having students model a wide range of phenomena using a single software tool and describe how we are using this capability to help young students develop a robust, statistical perspective.
  • Author(s):
    Miura, I. T.
    Year:
    1986
    Abstract:
    A 3-year study was conducted to document individual differences in computer interest and use among middle school students and the psychological and social processes that may contribute to these differences. A questionnaire was used to assess the computer interest and use of a sample of approximately 400 middle school students at the end of each of the 3 years. The dependent measures--interest in learning about computers, plans to take elective computer classes, willingness to consider a computer career, and non-school computer use--and outcome measures were combined into a computer interest and use composite score. Eight independent variables were selected: mathematics interest, current goals for computer use, mathematics achievement, perceived parental encouragement for computing activities, perceived peer reactions to computer involvement, perceived relevance of computing skills for the future, perceived self-efficacy for computer-related tasks, and affective responses to the computer. These variables were organized using a newly developed version of "living systems" theory and students were asked to rate them on a scale of 1 to 5. Regression analysis of the data from the questionnaires and additional demographic and descriptive data showed that: (1) the gender of the subject appears to be an important social characteristic to consider in predicting computer interest and use since there were significant differences in favor of males; (2) boys may be more involved in computers as the result of more opportunities for mastery, more role models to emulate, greater verbal encouragement, and less fear of the machines; and (3) boys express a more positive attitude about the benefits of computers to society than do girls. Although there was a decline within grade levels from year to year over the 3-year period the variables showed consistent gender differences in favor of males. (DJR)
  • Author(s):
    Wainer, H.
    Year:
    1992
    Abstract:
    This article states that there are two considerations for learning to graph data: 1) the structure of the phenomenon, and 2) the limitations of the format of graphical representation used. This paper provides historical examples of how graphic data has been used, highlights aspects of a display theory, and identifies concrete steps to improve the tabular quality of graphs. According to the author, a graph has the power to answer most commonly asked questions about data, and invite deeper questions as long as it is properly drawn. Bertin's (1973) levels of questions that can be asked from a graph are described. The first level deals with elementary questions which involve simple extractions of data from the graphs. The second level deals with intermediate questions. These refer to trends among multiple points in the data, and the identification of outliers. The third level involves overall questions which requires an understanding of the deep structure of the data in its totality, often comparing trends or groups in the data, and the overall message of what is being said in the picture. Questions that involve retrieving data from tables are almost always elementary questions. These only require that students understand discrete units of data. Wainer states that most tables do a disservice by confusing the kinds of data presented. Columns are often placed without much thought to the relevancy of their order. The order within the columns is similarly vulnerable to irrelevance. For example, criterion variables (like countries) are often presented in alphabetical order when they should be arranged on a concept that is more useful (like size of GNP or population). The author therefore recommends that rows and columns are ordered in a way that makes sense and that numbers be rounded off as much as possible.
  • Author(s):
    Sharma, S.
    Editors:
    Rossman, A., & Chance, B.
    Year:
    2006
    Abstract:
    This paper reports on data from a large study which explored form five (14 to 16-year-olds) students' ideas in statistics (probability, descriptive statistics, graphical representations, investigations). This paper discusses the ways in which students made sense of probability tasks obtained from the individual interviews. The findings revealed that many of the students used strategies based on beliefs, prior experiences and intuitive strategies. Additionally, in some cases the meaning intended by myself on the interview tasks was not that constructed by the students. As a result, students constructed responses based on these unintended interpretations. While students showed more competence on the formal item, they were less competent on the question involving an everyday context. This inconsistency could be due to contextual or linguistic issues. The paper concludes by suggesting some implications for further research.
  • Author(s):
    Truran, J.
    Editors:
    Biddulph, F. & Carr, K.
    Year:
    1997
    Abstract:
    This paper addressed the broad issue of relating research findings with pedagogical practices by analysing the responses to questions set in an undergraduate statistics examination using Eisner's connoisseurship and crticism approach, supported by general pedagagical and psychological principles. Comparisons are made between responses to the same course given in two different countries to assess similarities, differences, and weaknesses in order to indicate possible ways in which future courses might be modified to improve student learning.
  • Author(s):
    Carolyn Ridgway, Derry Ridgway
    Year:
    2010
    Abstract:
    Using sequences of coin flips as a model of serial independent events, we asked schoolchildren in grades 1 through 5 to estimate the likelihood of the next flip. Most children in each grade expected short patterns to continue.
  • Author(s):
    Glencross, M. J., & Laridon, P. E.
    Year:
    1994
    Abstract:
    During the period 1991 to 1993 a new junior high school curriculum was introduced in many South African schools. This curriculum is fairly strongly constructivist in design. A study of probability was included for the first time in any ordinary South African curriculum, this being at the Standard 7 (Grade 9) level. The approach is initially experimental but continues into the more formal presentation in terms of sample spaces. This situation presented the researchers with an opportunity of looking at the unschooled understanding of probability concepts amongst South African children before the curriculum was actually implemented. Data were also collected once some of the children had been taught about probability according to the new curriculum. It was anticipated that analysis of results would enable the researchers to identify prevalent misconceptions; to ascertain the effects of the reaching of probability according to the new curriculum; to compare the intuitive understanding of various groups (male and female, urban and rural); to offer suggestions for teaching on the basis of the findings and to compare the intuitive understanding of South African children with that of children from other countries such as Britain, Canada and Brazil. In this paper we look at the pre- and post-testing done in a selection of schools in the Johannesburg region and, for the Johannesburg and Umtata samples, present an innovative analysis of data from a selection of items from the instrument used.
  • Author(s):
    Konold, C.
    Editors:
    Brunelli, L., & Cicchitelli, G.
    Year:
    1993
    Abstract:
    Rather than elaborate Simon's argument here, I briefly describe two software tools we've developed, highlighting aspects that emphasize the relation between probability and data analysis. I also report some results from our primary test site, a high school in Holyoke, Massachusetts.
  • Author(s):
    Traub, R. E., & Rowley, G. L.
    Year:
    1991
    Abstract:
    The topic of test reliability is about the relative consistency of test scores and other educational and psychological measurements. In this module, the idea of consistency is illustrated with reference to two sets of test scores. A mathematical model is developed to explain both relative consistency and relative inconsistency of measurements. A means of indexing reliability is derived using the model. Practical methods of estimating reliability indices are considered, together with factors that influence the reliability index of a set of measurements and the interpretation that can be made of that index.
    Location:
  • Author(s):
    Gal, I., & Baron, J.
    Abstract:
    Assessed understanding of decision making about repeated uncertain events, using hypothetical and in-vivo prediction tasks modeled after those used in probabilitiy-learning research. Previous studies have been unclear on whether suboptimal choices reflected reasoning errors and lack of strategic thinking, or confounding factors. Quantitative and qualitative analyses of subjects' choices and strategy explanation showed that up to 50% of college students did not fully understand the relative value of different strategies. Only 5 % of subjects preferred a "true" probability matching strategy, included on an in-vivo task. High-school students showed greater misunderstandings. Large gender differences in prediction strategies and in related computational skills were observed. Understanding was discussed in terms of subjects' inferences from knowledge of independence of events, (lack of) computational skills, and correlates of the quantitative nature of prediction tasks. Implications for research on decision making, including need to address individual differences, are discussed.

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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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