Literature Index

Displaying 2301 - 2310 of 3326
  • Author(s):
    Reading, C.
    Year:
    2004
    Abstract:
    Variation is a key concept in the study of statistics and its understanding is a crucial aspect of most statistically related tasks. This study aimed to extend and apply a hierarchy for describing students' understanding of variation that was developed in a sampling context to the context of a natural event in which variation occurs. Students aged 13 to 17 engaged in an inference task that necessitated the description of both rainfall and temperature data. The SOLO Taxonomy was used as a framework for analyzing student responses. Two cycles of Unistructural-Multistructural-Relational levels, one for qualitative descriptions and the other for quantitative descriptions, were identified in responses. Implications of the extended hierarchy for describing understanding of variation for research, teaching and assessment are outlined.
  • Author(s):
    Nelson, C.
    Year:
    1996
    Abstract:
    It now appears that all traditionally taught college courses are markedly (though unintentionally) biased against many non-traditional students, and, indeed, against most students who have not attended elite preparatory schools. Thus, when we teach merely in traditional ways we probably discriminate strongly on grounds quite different from those we intend (assuming that we intend only effort and merit). Easily accessible changes in how we teach have been shown repeatedly to foster dramatic changes in student performance with no change in standards - in some cases, no students now earn failing grades. Similarly dramatic improvements have been shown in the uniformity of outcomes. For example, the gap between Black performance and the performance of other groups can be entirely eliminated, even in "hard" courses such as calculus.
  • Author(s):
    O'Connell, A. A., & Corter, J. E.
    Year:
    1993
    Abstract:
    For this study, the probability problem-solving processes of 104 graduate students enrolled in different sections of an introductory probability and statistics course at an urban college of education were analyzed for the presence and type of errors occurring in their work.
  • Author(s):
    O'Connell, A. A.
    Year:
    2002
    Abstract:
    The purposes of this paper are to illustrate the use of several assessment strategies in an advanced course in statistics, and to present the results of student ratings for each assessment strategy in terms of difficulty, appropriateness, level of learning achieved, and preference. The assessment strategies used include structured data analysis assignments, open-ended data analysis assignments, reviews of applied research articles, and annotating computer output from multivariate software procedures. Findings indicate that students "prefer" instructor-directed or structured assignments overall, but feel they learn the most when the assessment is unstructured and requires greater self-direction. Suggestions for incorporating these assessment strategies into the multivariate classroom, as well as examples of each strategy, are included in this study.
  • Author(s):
    Reading, C.
    Year:
    2003
    Abstract:
    Variation is a key concept in the study of statistics and the understanding of variation is a crucial aspect of most statistically related tasks. To express this understanding students need to be able to describe variation. Students aged 13 to 17 engaged in an inference task set in a real world context that necessitated the description of both rainfall and temperature data. This research qualitatively analysed the student responses with respect to the descriptions of variation that were incorporated. A Data Description hierarchy, previously developed for describing variation in a sampling task, was found to be appropriate to code the better responses and was extended to accommodate a range of less statistically sophisticated responses identified. The SOLO Taxonomy was used as a framework for the hierarchy. Two cycles of U-M-R levels, one for more qualitatively descriptions and the other for more quantitative descriptions, were identified in the responses. Task and implementation issues that may have affected the descriptions, as well as implications for research, teaching and assessment, are outlined.
  • Author(s):
    Mary Shotwell and Charles H. Apigian
    Year:
    2015
    Abstract:
    This study aimed to quantify the influence of student attributes, coursework resources, and online assessments on student learning in business statistics. Surveys were administered to students at the completion of both online and on-ground classes, covering student perception and utilization of internal and external academic resources, as well as intrinsic motivating factors for success in the course. Student performance as defined by quality points, various assignment points, and time spent on assignments, was not significantly different between on-ground and online students. However, use of resources and tools to complete homework and learn new topics differed. As a whole, students predominantly utilized homework as the first tool to learn new topics and complete homework, suggesting a paradigm shift in the way instructors should cater to student’s learning habits.
  • Author(s):
    Beth Chance, Jimmy Wong & Nathan Tintle
    Year:
    2017
    Abstract:
    “Simulation-based inference” (e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the first year of data from a multi-institution assessment effort by instructors using such an approach in a college-level introductory statistics course, some for the first time. We examine several pre-/post-measures of student attitudes and conceptual understanding of several topics in the introductory course. We highlight some patterns in the data, focusing on student level and instructor level variables and the application of hierarchical modeling to these data. One observation of interest is that the newer instructors see very similar gains to more experienced instructors, but we also look to how the data collection and analysis can be improved for future years, especially the need for more data on “nonusers.”
  • Author(s):
    Gelman, A. Nolan, D., Men, A., Warmerdam, S., & Bautista, M.
    Year:
    1998
    Abstract:
    An important theme in an introductory statistics course is the connection between statistics and the outside world. This article describes some assignments that have been useful in getting students to learn how to gather and process information presented in the newspaper articles and scientific reports they read. We discuss two related assignments. For the first kind of assignment, students work through prepared instructional packets. Each packet contains a newspaper article that reports on a scientific study or statistical analysis, the original report on which the article was based, a worksheet with guidelines for summarizing the reported study, and a series of questions. In the second kind of assignment, each student is required to find a newspaper article themselves, track down the original report, summarize the study using our guidelines, and write a critique of the article. Here, we describe the guidelines we developed to help the student in reading the newspaper article and orginal source, and the procedures we used for each type of assignment. Examples of handouts and assignments appear as appendixes.
  • Author(s):
    Sylwester, D. L., & Mee, R. W.
    Year:
    1992
    Abstract:
    In this talk we will briefly present our philosophy regarding student projects and then concentrate on organizational issues associate with having students in large lecture section courses do projects.
    Location:
  • Author(s):
    Garfield, J. B., & Ahlgren, A.
    Year:
    1994
    Abstract:
    The NCTM "Curriculum and Evaluation Standards for School Mathematics" (1989) reflect the current movement to introduce probability and statistics in the precollege curriculum. These standards include topics and principles for instruction in probability and statistics which are included in the Quantitative Literacy Project (QLP) curriculum materials. This paper presents results of a survey which explored the success of the QLP materials in terms of student reactions to instruction in probability and statistics.

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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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