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Core Methods in Educational Data Mining

Core Methods in Educational Data Mining. HUDK4050 Fall 2014. Performance Factors Analysis. What are the important differences in assumptions between PFA and BKT? What does PFA offer that BKT doesn’t? What does BKT offer that PFA doesn’t?. What do each of these parameters mean?.

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Core Methods in Educational Data Mining

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  1. Core Methods in Educational Data Mining HUDK4050Fall 2014

  2. Performance Factors Analysis • What are the important differences in assumptions between PFA and BKT? • What does PFA offer that BKT doesn’t? • What does BKT offer that PFA doesn’t?

  3. What do each of these parameters mean?

  4. Assignment 4B • Let’s go through the assignment together

  5. Assignment 4B • Any questions?

  6. Let’s look at what happens when we change g& r • Any questions?

  7. Can PFA • Have degenerate models? (How?)

  8. What do each of these mean? • When might you legitimately get them? • r < 0 • g< r • g < 0

  9. How Does PFA • Represent learning? • As opposed to just better predicted performance because you’ve gotten it right

  10. How Does PFA • Represent learning? • As opposed to just better predicted performance because you’ve gotten it right • Is it r? • Is it average of r and g?

  11. Let’s play with b values in the spreadsheet • Any questions?

  12. b Parameters • Pavlik proposes three different b Parameters • Item • Item-Type • Skill • Result in different number of parameters • And greater or lesser potential concern about over-fitting • What are the circumstances where you might want item versus skill?

  13. EM algorithm • Any questions?

  14. Other questions, comments, concerns about PFA?

  15. Assignment C3 • Data: An 8-item test given to students • Goal: Which items map to the same skill?

  16. Assignment C3 • Method: You pick • Barnes’s Q‐matrix method • Learning Factors Analysis • Learning Factors Transfer Analysis • Partial Order Knowledge Spaces • Factor Analysis • Playing around in Excel • Any other method

  17. Assignment C3: Note • If you choose the “playing around in Excel” method, make sure your hand-in clearly demonstrates each step of the thorough and thoughtful process you used • If you implemented LFA in Excel, great • If you used some thorough process in Excel to analyze the data and determine which items have high correlation in student responses, great • If you took fifteen minutes, messed around a little, and then gave up, not so great

  18. Assignment C3 • Any questions?

  19. Next Class • Wednesday, October 29 • No assignment due • No guest lecturer • Baker, R.S. (2014) Big Data and Education. Ch. 4, V5. • Beck, J.E., Chang, K-m., Mostow, J., Corbett, A. (2008) Does Help Help? Introducing the Bayesian Evaluation and Assessment Methodology. Proceedings of the International Conference on Intelligent Tutoring Systems.  • San Pedro, M.O.C., Baker, R., Rodrigo, M.M. (2011) Detecting Carelessness through Contextual Estimation of Slip Probabilities among Students Using an Intelligent Tutor for Mathematics. Proceedings of 15th International Conference on Artificial Intelligence in Education, 304-311.

  20. The End

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