Literature Index

Displaying 3101 - 3110 of 3326
  • Author(s):
    Oded Meyer
    Year:
    2007
    Abstract:
    Carnegie Mellon University was funded to develop a "stand-alone" web-based introductory statistics course, and for the last several semesters we've been studying different ways in which the course can be used to support instruction. In this presentation I'll discuss some of the challenges in developing such a learning environment and ways in which the course tries to address them, as well as describe the design and results of our studies.
  • Author(s):
    Fast, G. R.
    Year:
    1997
    Abstract:
    Anchoring probability situations which are conceptually analogous to misconception-prone/target probability situations were generated and tested with secondary mathematics students. The testing showed that probability misconceptions were common but also that anchors for overcoming these misconceptions could be generated. Anchoring situations were effectively utilized in overcoming students' probability misconceptions in the short term. A follow-up study showed that short term effects were retained at the rate of 0.65 over a six month period thereby establishing the long term effectiveness of the approach.
  • Author(s):
    Brad Smith
    Year:
    2003
    Abstract:
    The power of computing technology has increased at an astounding rate in the last decade. Today, the personal computer plays a key role in most introductory statistics courses, freeing students from "computational drudgery" as well as enabling a sharper instructional focus on data analysis and the interpretation of statistical results. Computers have also come to play an important role in teaching statistical concepts through simulations. Despite the increased popularity of computer-based statistical simulations, there have been few empirical evaluations of their effectiveness. In this paper, I describe and evaluate three computer-assisted simulations developed for use with SPSS and Microsoft Excel. The simulations are designed to reinforce and enhance students' understanding of sampling distributions, confidence intervals, and significance tests. Results of the evaluation reveal that these simulations can help improve students' comprehension of some of the most difficult material they encounter in the introductory social statistics course.
  • Author(s):
    Busk, P.
    Year:
    1998
    Abstract:
    What can we as instructors do to improve the quality of student learning and our own teaching? A great deal of research findings that were compiled in the 1980s are available to inform teaching in the 1990s. These research findings can be used by statistics teachers to improve the quality of student learning and their own teaching. The purpose of this paper is to illustrate assessment methods that can be used by the instructor to improve student learning and hence our teaching. Principles of good teaching based on research and ways to implement these principles in statistics classes are presented, which, in turn, will assist a faculty member in gathering information about the learning of his or her students and about his or her teaching. This paper is divided into four sections. The first section addresses the question as to why assess the statistics course. In the second section, the topic is what to assess in the statistics course, whereas how to assess the statistics course follows in the third section. After all of the data are gathered, what you do with the assessment information is the focus of the last section.
  • Author(s):
    delMas, R. C., Garfield, J., and Chance, B.
    Year:
    2004
    Abstract:
    In order to investigate the impact of simulation software on students' understanding of sampling distributions, the Sampling Sim program (delMas, 2001) was developed. The use of this software with students has been the subject of several classroom research studies conducted in a variety of settings (see Chance, delMas, and Garfield, in press). This paper examines the effect of several versions of a structured activity on students' understanding of sampling distributions. The first version of the activity was created to guide the students' interaction with the simulation software based on ideas from previous studies as well as the research literature. Two subsequent versions introduced a sticker and scrapbook activity that allowed students to keep a visual record of the effects of change in population shape and sample size on the resulting distributions of sample means. Four questions guided the studies reported in this paper: how can the simulations be utilized most effectively, how can we best integrate the technology into instruction, which particular techniques appear to be most effective, and how is student reasoning of sampling distributions impacted by use of the program and activities. A variety of assessment tasks were used to determine the extent of students' conceptual understanding of sampling distributions. As classroom researchers, a main goal was to document student learning while providing feedback for further development and improvement of the software and the learning activity. Ongoing collection and analysis of assessment data indicated that despite students' engagement in the activity and apparent understanding of sampling distributions and the Central Limit Theorem,<br>they were unable to apply this knowledge to solve novel problems. In particular, they had<br>difficulty solving graphical items that resembled tasks in the activity as well as well as applying the Central Limit Theorem to different situations. We comment on the lessons we have learned from this research, our explanations for why so many students continue to have difficulties, and our plans for revising the activity.
  • Author(s):
    Valaitis, E., &amp; Gray, M.
    Editors:
    Rossman, A., &amp; Chance, B.
    Year:
    2006
    Abstract:
    Most institutions of higher learning in the United States offer introductory statistics courses in a variety of flavors. Integration of the subject-specific concepts with the basic applied statistical techniques should be the primary goal of these flavored courses. Solely lecture-based traditional instruction method is not suitable to satisfying this objective. We argue for the incorporation of business-style cases into the introductory statistics curriculum using Constructivist learning theory and the notion of the "liberal arts" education. A typical business case setup is presented and its compatibility with an introductory statistics course is assessed. Finally, a sample business-style case for the application of the simple linear regression is provided.
  • Author(s):
    Jennifer Hall
    Year:
    2008
    Abstract:
    This paper outlines the successful professional development workshops provided by Canada's National Statistical Agency, Statistics Canada, for the Census at School program. Workshops for this international in-class online survey program help teachers develop statistical knowledge and teaching competencies. Workshop participants develop more positive attitudes toward statistics teaching and learning through hands-on exploration. Furthermore, by analyzing the Census at School data with TinkerPlots&trade; dynamic statistical software, participants learn to use technology to maximize statistical learning.
  • Author(s):
    McIntyre, L.
    Year:
    1994
    Abstract:
    The CIGARETTE dataset contains measurements of weight and tar, nicotine, and carbon monoxide content for 25 brands of domestic cigarettes. The dataset is useful for introducing the ideas of multiple regression and provides examples of an outlier and a pair of collinear variables.
  • Author(s):
    Mills, J. D.
    Year:
    2002
    Abstract:
    The teaching and learning of statistics has impacted the curriculum in elementary, secondary, and post-secondary education. Because of this growing movement to expand and include statistics into all levels of education, there is also a considerable interest in employing effective instructional methods, especially for statistics concepts that tend to be very difficult or abstract. Researchers have recommended using computer simulation methods (CSMs) to teach these concepts; however, a review of the literature reveals very little empirical research to support the recommendations. The purpose of this paper is to summarize and critically evaluate the literature on how CSMs are used in the statistics classroom and their potential impact on student achievement. The recommendation is that more empirically and theoretically grounded research studies are needed to determine if these methods improve student learning.
  • Author(s):
    Green, D. R.
    Year:
    1990
    Abstract:
    My personal dissatisfaction with the grounds I had for believing that software which I had produced was efficacious in developing probabilistic understanding led to a small research investigation which is reported in this paper.
    Location:

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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