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Utilizing a Digital Library to Teach Introductory Statistics

Utilizing a Digital Library to Teach Introductory Statistics. Joint Fall Conference, TMTA and MTMT. Utilizing a Digital Library to Teach Introductory Statistics. Lisa Bloomer Green, Ph. D. Scott McDaniel, Ed. D. Ginger Holmes Rowell, Ph. D. Megan Duffey*, Ileah McKee*

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Utilizing a Digital Library to Teach Introductory Statistics

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  1. Utilizing a Digital Library to Teach Introductory Statistics Joint Fall Conference, TMTA and MTMT

  2. Utilizing a Digital Library to Teach Introductory Statistics Lisa Bloomer Green, Ph. D. Scott McDaniel, Ed. D. Ginger Holmes Rowell, Ph. D. Megan Duffey*, Ileah McKee* *Undergraduate Students Middle Tennessee State University

  3. Outline • CAUSE and CAUSEweb • Using Internet Resources throughout the Learning Cycle • Specific Examples • Your Ideas

  4. CAUSE Consortium for the Advancement of Undergraduate Statistics Education

  5. CAUSEweb: Resources Digital Library for Undergraduate Statistics Education www.CAUSEweb.org

  6. CAUSEweb Searching: Browse Categories • Lecture Examples • Laboratories • Out-of-class • Teaching Tips • Datasets • Analysis Tools • Curriculum • Humor • Building Blocks • Multimedia

  7. CAUSEweb Advanced Search

  8. Advanced Searching • Conditional probability • Keyword • Filter by math level • Hypothesis testing • Keyword • Math level • Lecture presentation

  9. Case Study + Case Teaching Notes Case Study Example Teacher’s Viewpoint: = a “Ready-To-Go” Classroom Lesson

  10. Finding “Related” Items Related (or Companion) Items are Identified

  11. Outline • CAUSE and CAUSEweb • Using Internet Resources throughout the Learning Cycle • Specific Examples • Your Ideas

  12. Explore Lecture Assess • PowerPoint slides • Reference Materials • History • Demonstrations: • Applets • Videos • Simulations • Data Sets • Case Studies • Guided Demos • Simulations • Laboratories • Applets • Tutorials • Teacher-directed assessments • Laboratories • Homework Problems • Self-directed assessments • Immediate Feedback

  13. Outline • CAUSE and CAUSEweb • Using Internet Resources throughout the Learning Cycle • Specific Examples • Your Ideas

  14. Lecture Explore Assess To help students understand the use of conditional probability, a teacher can lead a demonstration of the Monty Hall Problem using one of the many available Internet applets. Tutorials, such as Mrs. Glosser’s Math Goodies Lesson on Conditional Probability, can be given to students who miss a class or students that would like additional instruction. In some self-assessment tools like Trees and Conditional Probability from Tutorials for Finite Math, students receive immediate feedback when answering questions including hints for incorrect answers and steps to correct solutions.

  15. Lecture Explore Assess To help students understand the use of conditional probability, a teacher can lead a demonstration of the Monty Hall Problem using one of the many available Internet applets.

  16. Whatever applet we choose goes here. Pause to do a worksheet. Applet http://www.shodor.org/~rcogan/interactivate/activities/index.html#pro

  17. Lecture Explore Assess To help students understand the use of conditional probability, a teacher can lead a demonstration of the Monty Hall Problem using one of the many available Internet applets. Tutorials, such as Mrs. Glosser’s Math Goodies Lesson on Conditional Probability, can be given to students who miss a class or students that would like additional instruction.

  18. http://www.mathgoodies.com/lessons/vol6/conditional.html

  19. Lecture Explore Assess To help students understand the use of conditional probability, a teacher can lead a demonstration of the Monty Hall Problem using one of the many available Internet applets. Tutorials, such as Mrs. Glosser’s Math Goodies Lesson on Conditional Probability, can be given to students who miss a class or students that would like additional instruction. In some self-assessment tools like Trees and Conditional Probability from Tutorials for Finite Math, students receive immediate feedback when answering questions including hints for incorrect answers and steps to correct solutions.

  20. http://people.hofstra.edu/faculty/Stefan_Waner/RealWorld/tutorialsf3/frames6_5B.htmlhttp://people.hofstra.edu/faculty/Stefan_Waner/RealWorld/tutorialsf3/frames6_5B.html

  21. http://ocw.mit.edu/OcwWeb/Mathematics/18-05Spring-2005/CourseHome/index.htmhttp://ocw.mit.edu/OcwWeb/Mathematics/18-05Spring-2005/CourseHome/index.htm

  22. Lecture Explore Assess Introduction to Probability and Statistics

  23. Lecture Explore Assess This slide from Sampling Distributions can help a teacher guide a discussion on when the sample mean can be assumed to be normally distributed. This applet from Statistical Java demonstrates the convergence implied by the central limit theorem by allowing students to manipulate sample size, number of samples, and underlying distribution. This guided applet activity from Wise includes assessment questions that, when answered correctly, allow students to proceed to new concepts.

  24. Lecture Explore Assess This slide from Sampling Distributions can help a teacher guide a discussion on when the sample mean can be assumed to be normally distributed.

  25. http://www.stat.psu.edu/~resources/ClassNotes/hrm_08/sld018.htmhttp://www.stat.psu.edu/~resources/ClassNotes/hrm_08/sld018.htm

  26. Lecture Explore Assess This slide from Sampling Distributions can help a teacher guide a discussion on when the sample mean can be assumed to be normally distributed. This applet from Statistical Java demonstrates the convergence implied by the central limit theorem by allowing students to manipulate sample size, number of samples, and underlying distribution.

  27. Applet Applet http://kitchen.stat.vt.edu/~sundar/java/applets/CLTApplet.html

  28. Lecture Explore Assess This slide from Sampling Distributions can help a teacher guide a discussion on when the sample mean can be assumed to be normally distributed. This applet from Statistical Java demonstrates the convergence implied by the central limit theorem by allowing students to manipulate sample size, number of samples, and underlying distribution. This guided applet activity from Wise includes assessment questions that, when answered correctly, allow students to proceed to new concepts.

  29. Lecture Explore Assess An in-class activity from the STAR Library can help introduce the concept of regression. Applets like this one from SticiGui Java Tools allow students to explore changes in the data to see how they affect the regression line. Using self-tests like this one from Biometry: Statistics for Ecology, students can submit their answers and receive immediate feedback regarding questions answered correctly and questions or topics needing improvement.

  30. Lecture Explore Assess An in-class activity from the STAR Library can help introduce the concept of regression.

  31. http://www.causeweb.org/repository/StarLibrary/activities/buskirk_young2001/http://www.causeweb.org/repository/StarLibrary/activities/buskirk_young2001/

  32. Lecture Explore Assess An in-class activity from the STAR Library can help introduce the concept of regression. Applets like this one from SticiGui Java Tools allow students to explore changes in the data to see how they affect the regression line.

  33. Regression applet http://stat-www.berkeley.edu/~stark/Java/Html/Correlation.htm

  34. Lecture Explore Assess An in-class activity from the STAR Library can help introduce the concept of regression. Applets like this one from SticiGui Java Tools allow students to explore changes in the data to see how they affect the regression line. Using self-tests like this one from Biometry: Statistics for Ecology, students can submit their answers and receive immediate feedback regarding questions answered correctly and questions or topics needing improvement.

  35. http://aerg.canberra.edu.au/cgi-bin/tiegen?/share/www/envirostats/bm/L6/ffq12.tiehttp://aerg.canberra.edu.au/cgi-bin/tiegen?/share/www/envirostats/bm/L6/ffq12.tie

  36. Lecture Explore Assess DIGSTATS contains examples and data sets, like the one below about Acid Rain. The Intuitor site contains an introduction to hypothesis testing, relating it to what happens at a criminal trial. The ARTIST database contains questions classified by topic and learning outcomes.

  37. Lecture Explore Assess The Intuitor site contains an introduction to hypothesis testing, relating it to what happens at a criminal trial.

  38. http://www.intuitor.com/statistics/T1T2Errors.html

  39. Lecture Explore Assess DIGSTATS contains examples and data sets, like the one below about Acid Rain. The Intuitor site contains an introduction to hypothesis testing, relating it to what happens at a criminal trial.

  40. http://www.cvgs.k12.va.us/DIGSTATS/Sitemap.html

  41. Acid Rain Activity

  42. Acid Rain Data

  43. Lecture Explore Assess DIGSTATS contains examples and data sets, like the one below about Acid Rain. The Intuitor site contains an introduction to hypothesis testing, relating it to what happens at a criminal trial. The ARTIST database contains questions classified by topic and learning outcomes.

  44. https://ore.gen.umn.edu/artist/index.html

  45. Outline • CAUSE and CAUSEweb • Using Internet Resources throughout the Learning Cycle • Specific Examples • Your Ideas

  46. Lisa Green lbgreen@mtsu.edu Scott McDaniel smcdanie@mtsu.edu Ginger Holmes Rowell rowell@mtsu.edu

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