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ISCAT Faculty Development Workshop

ISCAT Faculty Development Workshop. Allan Rossman and Beth Chance Cal Poly – San Luis Obispo June 21-25, 2004. Overview - Outline. Workshop goals, format, binder The problem Motivation/audience Principles Course materials Content, Structure, Status. Workshop Goals - Primary.

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ISCAT Faculty Development Workshop

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  1. ISCAT Faculty Development Workshop Allan Rossman and Beth Chance Cal Poly – San Luis Obispo June 21-25, 2004

  2. Overview - Outline • Workshop goals, format, binder • The problem • Motivation/audience • Principles • Course materials • Content, Structure, Status ISCAT workshop

  3. Workshop Goals - Primary • To help prepare you to • Present a course that provides a more balanced introduction to statistics for mathematically inclined students • Infuse a post-calculus introductory statistics course with activities and data • Model recommended pedagogy and content for future teachers of statistics ISCAT workshop

  4. Workshop Goals - Secondary • To generate productive thought and discussion about appropriate • Goals • Content • Pedagogy of an introductory statistics course for mathematically inclined students ISCAT workshop

  5. Workshop Goals - Secondary (cont.) • Offer helpful guidance for • Implementing activities and data • Assessing student learning • Using technology effectively in such a course • Provide an enjoyable, collegial experience ISCAT workshop

  6. Workshop Format • Most sessions will consist of working through activities/investigations • Please be willing to play the role of student • Investigations chosen from throughout course to illustrate guiding principles • We’ll “lecture” more than with our students • We’ll offer implementation suggestions along the way ISCAT workshop

  7. Workshop Format (cont.) • Some discussion sessions focused on particular issues • Goals/content • Implementation/assessment • We’d love to hear feedback from you at any point during and after this workshop • Also corner us during breaks, meals, beginning and end of day • Email discussion list ISCAT workshop

  8. Workshop Binder • Logistical information • Campus map, workshop schedule • Biographical sketches • Course materials • We’ll work through a small subset this week • May want to record your work on tablet paper • Additional activities, materials • Articles • Sample syllabi, exams, homework, review • More to come ISCAT workshop

  9. Features of Statistics Education Reform • Active Learning • Conceptual Understanding • Genuine Data • Use of Technology • Communication Skills • Interpretation in Context • Authentic Assessment ISCAT workshop

  10. Textbooks Activity Books Lab Manuals Books of Data Sources Books of Case Studies On-line Books Journals Dynamic Software Java Applets Web Sites Project Templates Assessment Instruments Workshops Products of Statistics Education Reform ISCAT workshop

  11. What’s the Problem? • Vast majority of reform efforts have been directed at the “Stat 101” service course • Rarely reaches Mathematics or Statistics majors • Option A: Take Stat 101 • Option B: Standard Prob and Math/Stat sequence ISCAT workshop

  12. What’s the Problem? • Option A • Does not challenge students mathematically • Rarely counts toward major • Option B • Does not give balanced view of discipline • Fails to recruit all who might be interested • Leaves prospective K-12 teachers ill-prepared to teach statistics, implement reform methods • Does not even prepare assistants for Stat 101! ISCAT workshop

  13. Is This Problem Important? “The question of what to do about the standard two-course upperclass sequence in probability and statistics for mathematics majors is the most important unresolved issue in undergraduate statistics education.” - David Moore ISCAT workshop

  14. Is This Problem Important? “The standard curriculum for mathematics majors allows little time for statistics until, at best, an upper division elective. At that point, students often find themselves thrust into a calculus-based mathematical statistics course, and they miss many basic statistical ideas and techniques that are at the heart of high school statistics courses.” - CBMS MET report (ch. 5) ISCAT workshop

  15. Is This Problem Important? “In most teacher preparation programs appropriate background in statistics and probability will not be provided by simply requiring a standard probability-statistics course for mathematics majors. It is essential to carefully consider the important goals of statistical education in designing courses that reflect new conceptions of the subject.” - CBMS MET report (ch. 5) ISCAT workshop

  16. Our Project To develop and provide a: Data-Oriented, Active Learning, Post-Calculus Introduction to Statistical Concepts, Applications, Theory Supported by the NSF DUE/CCLI #9950476, 0321973 ISCAT workshop

  17. Principle 1 • Motivate with real studies, genuine data • Statistics as a science • Wide variety of contexts • Some data collected on students themselves ISCAT workshop

  18. Principle 2 • Emphasize connections among study design, inference technique, scope of conclusions • Issues arise in chapter 1, recur often • Observational study vs. controlled experiment • Randomization of subjects vs. random sampling • Inference technique follows from randomization in data collection process ISCAT workshop

  19. Principle 3 • Conduct simulations often • Problem-solving tool and pedagogical device • Address fundamental question: “How often would this happen in the long run?” • Hands-on simulations usually precede technological simulations • Java applets • Small-scale Minitab programming (macros) ISCAT workshop

  20. Principle 4 • Use variety of computational tools • For analyzing data, exploring statistical concepts • Assume that students have frequent access to computing • Not necessarily every class meeting in computer lab • Choose right tool for task at hand • Analyzing data: statistics package (e.g., Minitab) • Exploring concepts: Java applets (interactivity, visualization) • Immediate feedback from calculations: spreadsheet (Excel) ISCAT workshop

  21. Principle 5 • Investigate mathematical underpinnings • Primary distinction from “Stat 101” course • Some use of calculus but not much • Will assume familiarity with mathematical ideas such as function • Example: study principle of least squares in univariate and bivariate settings • Often occurs as follow-up homework exercises ISCAT workshop

  22. Principle 6 • Introduce probability “just in time” • Not the goal • Studied as needed to address statistical issues • Often introduced through simulation • Examples • Hypergeometric distribution: Fisher’s exact test for 2x2 table • Binomial distribution: Sampling from random process • Continuous probability models as approximations ISCAT workshop

  23. Principle 7 • Foster active explorations • Students learn through constructing own knowledge, developing own understanding • Need direction, guidance to do that ISCAT workshop

  24. Principle 8 • Experience entire statistical process over and over • Data collection • Graphical and numerical displays • Consider inference procedure • Apply inference procedure • Communicate findings in context • Repeat in new setting • Repeat in new setting • Repeat in new setting… ISCAT workshop

  25. Content- Chapter 1 • Comparisons and conclusions • Categorical variables • Two-way tables • Relative risk, odds ratio • Variability, confounding, experimental design, randomization, probability, significance • Fisher’s exact test ISCAT workshop

  26. Content- Chapter 2 • Comparisons with quantitative variables • Visual displays • Numerical summaries • Randomization distribution • Significance, p-value, … ISCAT workshop

  27. Content- Chapter 3 • Sampling from populations and processes • Bias, precision • Random sampling • Sampling variability, distributions • Bernoulli process and binomial model • Binomial approximation to hypergeometric • Significance, confidence, types of errors ISCAT workshop

  28. Content- Chapter 4 • Models and sampling distributions • Probability models, including normal • Approximate sampling distribution for sample proportion • Normal approximation to binomial • Sampling distribution of sample mean • t-procedures • Bootstrapping ISCAT workshop

  29. Content- Chapter 5 • Comparing two populations • Categorical variables • Two-sample z-test • Approximation to randomization distribution • Odds ratio • Quantitative variables • Two-sample t-test • Approximation to randomization distribution ISCAT workshop

  30. Content- Chapter 6 • Association and relationships • Chi-square tests • Analysis of variance • Simple linear regression ISCAT workshop

  31. Course Materials- Structure • Investigations • Can be adapted for variety of teaching styles • Exposition • Study conclusions, discussion, summaries • Technology explorations • Detours for terminology, probability • Practice problems • Help students to assess their understanding • Expand their knowledge ISCAT workshop

  32. Course Materials- Status • Preliminary version to be published by Duxbury in August • Hot-off-the-press version in your binders • Companion website: www.rossmanchance.com/iscam/ • Next year: polishing, refining, developing resource materials • Homework problems/solutions, teachers’ guide, powerpoint, practice problem solutions to appear on web • Include more worked out examples • Please share your suggestions with us ISCAT workshop

  33. Questions? • On the workshop? • On the course materials? • Ready to play the role of (good) student now? ISCAT workshop

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