Literature Index

Displaying 2651 - 2660 of 3326

  • The case for randomized experiments

    Author(s):
    Cook, T. D., Means, B., Haertel, G. D., & Michalchik, V.
    Year:
    2003
    Abstract:
    This chapter seeks to show how randomized experiments can be productively used to learn about the effects of important aspects of educational technology and even about the effects of important aspects of educational technology and even about technology writ large. To achieve this, we first work through a hypothetical example and then later present an abstract analysis of the example. The point is to elucidate the conditions under which random assignment is desirable and feasible in studies of educational technology.

  • The case for rules in reasoning

    Author(s):
    Smith, E. E., Langston, C., & Nisbett, R. E.
    Year:
    1992
    Abstract:
    A number of theoretical positions in psychology - including variants of case-based reasoning, instance-based analogy, and connectionist models - maintain that abstract rules are not involved in human reasoning, or at best play a minor role. Other views hold that the use of abstract rules is a core aspect of human reasoning. We propose eight criteria for determining whether or not people use abstract rules in reasoning, and examine evidence relevant to each criterion for several rule systems. We argue that there is substantial evidence that several different inferential rules, including modus ponens, contractual rules, causal rules, and the law of large numbers, are used in solving everyday problems. We discuss the implications for various theoretical positions and consider hybrid mechanisms that combine aspects of instance and rule models.

  • The case for using computers in teaching statistics

    Author(s):
    Joiner, B. L.
    Editors:
    Grey, D. R., Holmes, P., Barnett, V., & Constable, G. M.
    Year:
    1983
    Abstract:
    The teaching of basic statistics course can be greatly enhanced with the use of widely available statistical software. Pocket calculators can relieve some of the computational drudgery of statistics but are of little help with data plotting, one of the key steps in the statistical analysis process. By using computers in basic statistics courses, we can present students with real data sets and problems and teach them how to approach and analyze data. In this paper, the basic steps in the statistical analysis process are listed, and this paper, the basic steps in the statistical analysis process are listed, and the important role that computers can play in some of these steps is emphasized.

  • The case of the wayward data collector (How projects can be used in our statistics class)

    Author(s):
    Krevisky, S.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    Projects can be a good way for students to apply what they've learned in class. I have my students pick a topic of interest to them; they gather and collect the data; present it via a research report which is due at the end of the semester. It definitely helps their grades and provides some meaning and perspective to the semester's work. The students picked some very interesting subjects as well. All of this was explored in the workshop.

  • The CASE Project: Evaluation of Case-Based Approaches to Learning and Teaching in Statistics Service Courses

    Author(s):
    Lee Fawcett
    Year:
    2017
    Abstract:
    The CASE project (Case-based Approaches to Statistics Education; see www.mas.ncl.ac.uk/∼nlf8/innovation) was established to investigate how the use of real-life, discipline-specific case study material in Statistics service courses could improve student engagement, motivation, and confidence. Ultimately, the project aims to promote deep learning of course material, with students from other disciplines being equipped with the skills to undertake independent quantitative analyses (for example, in their final year dissertations). In this article, I describe the case-based materials and associated activities, developed as part of this project, for first year Business undergraduates taking a compulsory course in quantitative methods. I also attempt to evaluate the success of the CASE project through a trial in which a randomly selected subgroup of students was exposed to case-based learning and teaching activities. After adjusting for nuisance factors, I found that students in this subgroup outperformed their peers who were not selected for case-based learning and teaching, in terms of their grades in both routine algorithmic homework exercises and more open-ended projects requiring problem-solving and interpretative skills.  
    Location:
    http://tandfonline.com/doi/full/10.1080/10691898.2017.1341286

  • The central role of the PC in teaching statistics at school

    Author(s):
    Engel, A.
    Editors:
    Vere-Jones, D., Carlyle, S., & Dawkins, B. P.
    Year:
    1991
    Abstract:
    Usually the PC is used in statistics to do quickly and conveniently what we have always been doing. This is a misuse of the PC since it has the potential to change statistical practice fundamentally. Historically, statistics was developed when computation was hard and expensive. To avoid massive computation a lot of sophisticated theory based on asymptotics was developed. Now computation is cheap and easy. The PC should replace sophisticated theory by simple computations, and make statistics more comprehensible. We should strive for understanding. Sophisticated statistical software is pedagogically harmful. We do not want to solve a dozen problems a day by using recipes. We want to solve a few paradigmatic examples in a few weeks. School statistics should solve a small number of fundamental problems, not quickly, but leisurely. We should derive programs for the solutions, which are general enough, so that they solve a whole class of problems. I do not advocate much deep programming, which is quite difficult. On the other hand, statistical software is for professionals. To learn its use requires an effort comparable to the effort of learning a new programming language. Design of a program is an important part of the learning process. A problem is solved if you have an efficient algorithm for its solution, which you understand.

  • The challenge of computers in today's statistical education

    Author(s):
    Kanji, G. K., & Harris, R. R.
    Editors:
    Davidson, R., & Swift, J.
    Year:
    1986
    Abstract:
    This paper begins with a brief discussion of the role of the statistician and how this is changing, particularly in view of the microcomputer revolution. Historically the training of the professional statistician has been undertaken within academic institutions and has often incorporated little practical training. The advent of relatively cheap and accessible computer power has allowed more applied elements to be incorporated into statistical education, in particular larger and more realistic data sets may be used, models fitted (and compared) with greater ease, and so on. There are numerous ways in which this computing power may be exploited in the education of statisticians and this paper outlines a number of these and discusses their usefulness.

  • The Challenge of Developing Statistical Literacy, Reasoning, and Thinking

    Editors:
    Ben-Zvi, D. & Garfield, J.
    Year:
    2004
    Abstract:
    Over the past decade there has been an increasingly strong call for statistics<br>education to focus on statistical literacy, statistical reasoning, and statistical<br>thinking. Our goal in creating this book is to provide a useful resource for educators<br>and researchers interested in helping students at all educational levels to develop<br>these cognitive processes and learning outcomes. This book includes cutting-edge<br>research on teaching and learning statistics, along with specific pedagogical<br>implications. We designed the book for academic audiences interested in statistics<br>education as well as for teachers, curriculum writers, and technology developers. (From preface)

  • The challenge of developing statistical literacy, reasoning, and thinking

    Editors:
    Garfield, J., & Ben-Zvi, D.
    Year:
    2004

  • The Challenge of Developing Statistical Reasoning

    Author(s):
    Garfield, J. B.
    Year:
    2002
    Abstract:
    This paper defines statistical reasoning and reviews research on this topic. Types of correct and incorrect reasoning are summarized, and statistical reasoning about sampling distributions is examined in more detail. A model of statistical reasoning is presented, and suggestions are offered for assessing statistical reasoning. The paper concludes with implications for teaching students in ways that will facilitate the development of their statistical reasoning.
    Location:
    http://www.amstat.org/publications/jse/v10n3/garfield.html

Pages

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