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Score end talk 1

  1. 1. Teaching Statistics in Psychology Martin Le Voi
  2. 2. Statistics is hard to understand <ul><li>At least for psychologists… </li></ul><ul><li>Many psychology departments struggle with explaining it </li></ul><ul><li>Students struggle </li></ul><ul><li>Every lecturer has a pet way of teaching </li></ul><ul><li>Is the problem with “one-size-fits-all” </li></ul>
  3. 3. How do you understand the “mean” <ul><li>The central tendency of a group of numbers </li></ul><ul><li>The expected value of a random variable </li></ul><ul><li>As an equation: </li></ul>
  4. 4. In pictures?
  5. 5. As a simulation?
  6. 6. As a song?!! <ul><li>http://resources4statistics.typepad.com/blog/2010/03/mean-median-and-mode-song.html </li></ul>
  7. 7. Students learn in different ways <ul><li>Well, they claim some things are easier than others </li></ul><ul><li>Some text books are easier than others </li></ul><ul><li>And it never seems unanimous </li></ul><ul><li>Certainly some concepts can be explained in different ways </li></ul>
  8. 8. The Matching Hypothesis <ul><li>If you teach a student in concordance with their learning style, learning will be optimised </li></ul><ul><li>But what is Learning Style? </li></ul><ul><li>And how do you teach to it? </li></ul><ul><li>Masser & Mayer (2006). ATI hypothesis: fails! </li></ul>
  9. 9. The ATI Hypothesis <ul><li>Masser & Mayer (2006). </li></ul><ul><li>Visual student, visual instruction GOOD </li></ul><ul><li>Visual Student, verbal instruction BAD </li></ul><ul><li>Verbal student, visual instruction BAD </li></ul><ul><li>Verbal Student, verbal instruction GOOD </li></ul><ul><li>Fails… </li></ul>
  10. 10. Dodge the problem! <ul><li>Find and evaluate existing OERs for teaching statistics </li></ul><ul><li>Classify by teaching approach </li></ul><ul><li>Invite students to self-assess by sampling quality materials in different approaches </li></ul><ul><li>Automate the process! </li></ul>
  11. 11. Search for psychometrically valid learning style assessment <ul><li>Mayer & Masser 2003 </li></ul><ul><li>Factor Analysed 14 measures together </li></ul><ul><li>Best are: </li></ul><ul><li>MLPQ Cronbach’s alpha 0.8, “retest” 0.59 </li></ul><ul><li>Loads 0.98/0.54 on Learning Preference factor </li></ul><ul><li>VVLS loads 0.83 on Cognitive Style factor, (0.38 on MLPQ) </li></ul><ul><li>Coded both into OpenLearn (demo) </li></ul>
  12. 12. Finding resources: the problem <ul><li>http://psych. hanover . edu/aps/teaching .html#statistics </li></ul><ul><li>http://it. stlawu .edu/~rlock/tise98/onepage.html </li></ul><ul><li>http://www.stat.duke. edu/sites/java .html </li></ul><ul><li>Problem of evaluation </li></ul><ul><li>Merlot http://www.merlot.org/ </li></ul>
  13. 13. Merlot <ul><li>Merlot has a systematic peer review system </li></ul><ul><li>http://www.merlot.org/ </li></ul><ul><li>Peer review example (file) </li></ul><ul><li>Clear winner for Visualisation teaching </li></ul><ul><li>http://www.seeingstatistics.com/ </li></ul>
  14. 14. OpenLearn courses in development <ul><li>Learning Statistics by visualisation </li></ul><ul><li>Learning Statistics by graphics (maybe too similar to 1) </li></ul><ul><li>Learning Statistics by algebra and text </li></ul><ul><li>Not in OpenLearn: </li></ul><ul><li>Learning Statistics: the non-linear approach (to be prepared in Prezi: http://prezi.com/ ) </li></ul>

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