Core Methods in Educational Data Mining

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Core Methods in Educational Data Mining HUDK4050 Fall 2014

Correlation Mining The simplest form of relationship mining

Assignment B6 Let’s go over each answer

Questions about why post-hoc controls are needed?

Questions about Bonferroni?

Questions about Stigler’s Law of Eponomy?

Questions about FDR vs FWER?

Questions about p versus q?

Questions about p versus q? p = probability that the results could have occurred if there were only random events going on q = probability that the current test is a false discovery, given the post-hoc adjustment

Other questions about post-hoc controls?

Questions about ideas behind causal data mining?

Fancsali (2013) Example This example uses an algorithm that allows for unmeasured common causes of measured variables. pretest_score  total_steps can signify (1) pretest_score is a cause of total_steps; (2) pretest_score & total_steps share a common cause; (3) both!

Rau & Scheines (2012)

Rai et al. (2011)

Rai et al. (2011) What’s wrong with this graph?

Rai et al. (2011) What’s wrong with this graph?

Solution Use domain knowledge to constrain search. The future can’t cause the past.

Result

Does this seem OK?

Does this seem OK? Or does it call the whole method into question? If we can get future->past relationships, why should we trust any causal arrows tetrad produces?

Any other questions or comments?

Assignment B7 Clustering

Next Class No class next week

Next Class Monday, November 24 Baker, R.S. (2014) Big Data and Education. Ch. 8, V1, V2. Pardos, Z.A., Baker, R.S., San Pedro, M.O.C.Z., Gowda, S.M., Gowda, S.M. (2014) Affective states and state tests: Investigating how affect and engagement during the school year predict end of year learning outcomes. Journal of Learning Analytics, 1 (1), 107-128. Hershkovitz, A., Baker, R.S.J.d., Gobert, J., Wixon, M., Sao Pedro, M. (2013) Discovery with Models: A Case Study on Carelessness in Computer-based Science Inquiry. American Behavioral Scientist, 57 (10), 1479-1498.

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