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October 23,
2009 |
"Bayes, and the (post-data) Future of Our Curriculum: The Camel's Nose, the Tent, and Who's Inside, Who's Outside" This talk will have two parts: First and concretely, I'll offer a trail of bread crumbs that mark out an elementary path back home to Bayesian thinking, including a class activity. Second, and abstractly, I'll offer my best long view of hwere I think our curriculum is headed. In particular, I'll address my sense that our current happy curricular picnic has only begun to register the unwelcome skunk scent of the digital revolution. To learn more about George Cobb, go to : To view slides from the presentation: Bayes In The Long Run.pdf |
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June 23,
2009 |
"Informal Statistical Inference"
An informal presentation and discussion of their current work on informal statistical inference. Chris Wild has written on statistical thinking and assessment. Nick Horton spent a sabbatical at the University of Auckland working with Chris and is a member of the ASA/NCTM Joint Committee on Curriculum in Statistics and Probability. |
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March 10,
2009 |
"The Impact of AP Statistics on K-16 Education and the Statistics Profession" The AP Statistics program will celebrate the administration of the 13th AP Statistics exam in 2009. The program has grown from 7500 exams in 1997 to a projected 120,000 exams in 2009. What has been the impact of AP Statistics during this 13 year evolution? This stat chat talk will include: why offer the AP Statistics program, the impact of AP Statistics on statistics at the Pre-K-12 level and on undergraduate and graduate program in statistics, the critical issues facing the AP Statistics program such as teacher preparation, and how students are assessed in AP Statistics. |
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February 20,
2009 |
"Building an Infrastructure for STEM Education Teaching and Research" The Database for Assessment of National STEM Education Research (DANSER) is an emerging project geared toward developing a multi-disciplinary on-line STEM education research environment supporting teachers, assessment instrument authors, and education researchers. This presentation will outline a vision for DANSER and illustrate its use in support of two projects in the teaching and learning of statistics. To learn more about Dennis Pearl, go to
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April 23,
2008 |
"Understanding
What Makes Assessment Items Difficult: Tackling
Cognitive, Methodological, and Political Challenges in Assessing
Quantitative Literacy" This talk will address selected issues that are infrequently discussed in the literature but critical for planning large scale assessments of numeracy and quantitative literacy, for interpreting their results, and for translating assessment results into actionable knowledge. Examples and lessons learned from the international Adult Literacy and Lifeskills survey, NAEP, and PISA will be used to illustrate some key points. To learn more about Professor Ido Gal, go to
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November 16 ,
2007 |
"Is
Statistics Getting Harder as it Gets Softer?" We all recognize the destabilizing effect that computers are having on what we do, and, potentially at least, on how we think about what we do. The resulting changes bring both good news and bad news. Much of the good news is well known: we no longer have to teach all those boring computational rituals that used to give statistics such a bad name; we can use real data in our classes, and leave the dirty work to silicon. The bad news is only beginning to sink in: teaching and learning mere technique is a lot easier than teaching and learning whatever it is that we should be doing instead, now that computers have so drastically cheapened the value of mere technique. This talk will offersome opinions about what we should teach, and why: (1) Scrap distribution theory in favor of simulation. (2) Teach testing and intervals based on simulation. (3) Teach a lot more design. (4) Teach Bayes without his Theorem. To learn more about George Cobb, go to : Viewa movie of the presentation: GeorgeCobbLecture.mov |
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| October 5, 2007 2:15 - 3:45 PM 120 Burton Hall |
"Balancing Innovation and Efficiency
In Statistics Learning" An important goal of education is to prepare students to adapt to new circumstances. Given the centrality of this educational goal, it is surprising that education has not developed assessments of adaptiveness. Instead, most measures of learning emphasize efficiency—the ability to apply one’s knowledge quickly and without error. This is different from adaptation, which often involves letting go of immediate efficiencies to learn new ways of doing things. This talk will describe instruction on the statistical topic of variability that targets a specific type of adaptiveness; namely, the preparation for future learning. It will demonstrate that measures of preparation for future learning can capture positive outcomes from curricula that emphasize student innovation. At the same time, it will demonstrate that innovation-oriented curricula can also lead to efficient outcomes if done well. To learn more about Daniel Schwartz, go to : |
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| September 14, 2007 1:30 - 3:00 PM 240 Burton Hall |
"Teaching and
Learning Statistics Using R" The R package has a number of advantages
for both teachers and To learn more about Daniel Kaplan, go to: |
