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Core Methods in Educational Data Mining

Explore interesting rules found in sequential pattern mining, differences between textual and interaction data, advantages and disadvantages of word counts, bigrams, trigrams, grammatical structures, and semantic tagging. Understand measures used in student response analysis and goals of prominent papers in educational data mining. Prepare for final project presentations and discussions on visualization techniques.

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Core Methods in Educational Data Mining

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  1. Core Methods in Educational Data Mining HUDK4050Fall 2015

  2. Assignment C4 • What are some interesting rules that people found?

  3. Assignment C4 • How did people find their rules?

  4. Last thoughts or comments on sequential pattern mining

  5. Text Mining

  6. Thoughts about video lecture?

  7. How is textual data different than interaction data?

  8. What are the advantages and disadvantages • Of looking for counts of words • Also called “bag of words”/LSA • Of looking for bigrams • Of looking for trigrams • Of looking for grammatical structures

  9. Semantic Tagging • What is it?

  10. WMatrix categories • http://ucrel.lancs.ac.uk/people/paul/publications/phd2003.pdf • At the end

  11. What are the advantages and disadvantages • Of semantic tagging versus looking for specific words

  12. Questions/Comments?

  13. What measures (of student responses) did Graesser et al. paper use?

  14. What measures (of student responses) did Graesser et al. paper use? • Learner Verbosity • LSA-based comparison to “good” and “bad” answers • Change in degree of goodness of answer

  15. Questions/Comments • About Graesser et al. paper?

  16. Talk about other papers (2015)

  17. What was goal/approach of • Adamson et al. paper

  18. Questions/comments • About Adamson paper?

  19. What was goal/approach of • Crossley et al. paper

  20. Questions/comments • About Crossley paper?

  21. Assignment C5 • Visualization • Questions? • Email me your visualizations

  22. Assignment C6 • Final project • Please read assignment, I keep getting questions that indicate people have not read assignment • Questions?

  23. Next Class • Monday, December 10: Visualization • Readings • Baker, R.S. (2014) Big Data and Education. Ch. 6, V1, V2, V3, V4, V5. • Kay, J., Maisonneuve, N., Yacef, K., Reimann, P. (2006) The big five and visualisations of team work activity. Intelligent Tutoring Systems: Proceedings 8th International Conference, ITS 2006, 197-206. • Ritter, S., Harris, T., Nixon, T., Dickinson, D., Murray, R.C., Towle, B. (2009) Reducing the Knowledge Tracing Space. Proceedings of the 2nd International Conference on Educational Data Mining, 151-160. • Martinez, R., Kay, J., Yacef, K. (2011) Visualisations for longitudinal participation, contribution and progress of a collaborative task at the tabletop. International Conference on Computer Supported Collaborative Learning, CSCL 2011, 25-32.

  24. Some final project presentations next class • Check where you are on the sign-up sheet on the forum!

  25. The End

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