Curriculum

  • August 12, 2008 Teaching and Learning webinar presented by Kathryn Plank, The Ohio State University; and Michele DiPietro, Carnegie Mellon University and hosted by Jackie Miller, The Ohio State University. There are many good reasons to incorporate thinking about diversity into a course, not the least of which is that it can have a real impact on student learning and cognitive development. This webinar explores both how the tools of statistics can help students better understand complex and controversial issues, and, in the other direction, how using these complex and controversial issues can help facilitate deeper learning of statistics.
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  • October 14, 2008 Teaching and Learning webinar presented by Daniel Kaplan, Macalester College and hosted by Jackie Miller, The Ohio State University. George Cobb describes the core logic of statistical inference in terms of the three Rs: Randomize, Repeat, Reject. Note that all three Rs involve process or action. Teaching this core logic is more effective when students are able to carry out these actions on real data. This webinar shows how to use computers effectively with introductory-level students to teach them the three Rs of inference. This is done with another R: the statistical software package. The simulations that are carried out involve constructing confidence intervals, demonstrating the idea of "coverage," hypothesis testing, and confounding and covariation.
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  • November 18, 2008 Teaching and Learning webinar presented by Xiao-Li Meng, Harvard University and hosted by Jackie Miller, The Ohio State University. Statistics 105 is a team-designed course that has received local media attention (e.g., www.news.harvard.edu/gazette/2008/02.14/11-stats.html). Its course description promises the following: Discover an appreciation of statistical principles and reasoning via "Real-Life Modules" that can make you rich or poor (financial investments), loved or lonely (on-line dating), healthy or ill (clinical trials), satisfied or frustrated (chocolate/wine tasting) and more. Guaranteed to bring happiness (or misery) both to students who have never taken a previous statistics course, and to those who have taken statistics and want to see how statistical thinking applies to so many areas of life. This webinar reveals its history, pedagogical motivation, innovations, and challenges along the way
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  • December 9, 2008 Teaching and Learning webinar presented by John H. Walker, California Polytechnic State University and hosted by Jackie Miller, The Ohio State University. Ethics play an important role in statistical practice. How can we educate our students about statistical ethics--especially when our courses are already packed with so much...statistics? At the Joint Statistical Meetings in August, 2008 Dr. Walker was the discussant in a session on "Teaching Ethics in Statistics Class." The webinar first briefly reviews the points raised by the speakers in that session. George McCabe (Purdue) contrasted the "old" introductory statistics course with its emphasis on methodology to the "new" course. Patricia Humphrey (Georgia Southern) spoke about how she covers ethical data collection in her introductory classes. Paul Velleman (Cornell) talked about the role of judgment in statistical model building and how it makes students (and sometimes us) uncomfortable. The webinar presentation discusses each of these points in the context of the American Statistical Association's "Ethical Guidelines for Statistical Practice" as well as discussing experiences in teaching statistical ethics in an undergraduate capstone course for statistics majors. It closes with an example of statistical ethics in the use of multiple comparison procedures.
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  • January 13, 2009 Teaching and Learning webinar presented by Jo Hardin, Pomona College and hosted by Jackie Miller, The Ohio State University. This webinar discusses the development and teaching of a freshman seminar course. In this course, students investigate the practical, ethical, and philosophical issues raised by the use of statistics and probabilistic thinking in realms such as politics, medicine, sports, the law, and genetics. Students explore issues from fiction, the mainstream media, and scientific articles in peer-reviewed journals. To do all of this, they must consider a wide range of statistical topics as well as encountering a range of uses and abuses of statistics in the world today.
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  • February 10, 2009 Teaching and Learning webinar presented by Andrew Zieffler, Bob delMas, and Joan Garfield, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar presents an overview of the materials and research-based pedagogical approach to helping students reason about important statistical concepts. The materials presented were developed by the NSF-funded AIMS (adapting and Implementing Innovative Materials in Statistics) project at the University of Minnesota (www.tc.umn.edu/~aims).

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  • webinar illustrates how personal response systems (clickers) can be used to address the realization of these three recommendations in large lecture classes (over 70 students). The session discusses general issues of the implementation of clickers and then provides an example of each of the following three uses of clickers in the classroom: 1) questions designed to highlight common conceptual misunderstandings in statistics, 2) questions designed as review questions for topics already addressed, and 3) questions that were part of a class activity to help students learn a concept.
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  • April 14, 2009 Teaching and Learning webinar presented by Beth Chance and Allan Rossman, Cal Poly, and John Holcomb, Cleveland State University, and hosted by Jackie Miller, The Ohio State University. This webinar presents ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. The webinar proposes that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. During this webinar arguments are presented in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlights some difficulties with implementing this approach, and discusses ideas for assessing student understanding of inference concepts and randomization procedures.
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  • May 12, 2009 Teaching and Learning hour-long webinar panel discussion presented by Laura Kubatko, The Ohio State University; Danny Kaplan, Macalester College; and Jeff Knisley, East Tennessee State University, and hosted by Jackie Miller, The Ohio State University. National reports such as Bio2010 have called for drastic improvements in the quantitative education that biology students receive. The three panelists are involved in three differently structured integrative programs aimed to give biology students the statistics that are useful in learning and doing biology. The three programs have some surprising things in common for teaching introductory statistics. All three involve connecting calculus and statistics. All three reach beyond the mathematical topics usually encountered in intro statistics in important ways. All three aim to keep the mathematics and statistics strongly connected to biology. The panelists describe their different approaches to teaching statistics for biology and discuss how and why an integrated approach gives advantages. Important issues are how to tie statistics advantageously with calculus, how to keep "advanced" mathematical and statistical topics accessible to introductory-level biology students, and how to employ computation productively. The discussion contrasts a comprehensive "team" approach (at ETSU) with stand-alone courses (at Macalester and at OSU) and refers to the institutional opportunities and constraints that have shaped the programs at their different institutions.

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  • June 9, 2009 Teaching and Learning webinar presented by Dalene Stangl, Duke University, and hosted by Jackie Miller, The Oho State University. This webinar presents the core materials used at Duke University to teach Bayesian inference in undergraduate service courses geared toward social science, natural science, pre-med, and/or pre-law students. During the semester this material is presented after completing all chapters of the book Statistics by Freedman, Pisani, and Purves. It uses math at the level of basic algebra.
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