Module 6: Relationship Mining Readings

Correlation Mining

• Baker, R.S. (2023) Big Data and Education. Ch. 5, V1.

• Slater, S., Ocumpaugh, J., Baker, R., Scupelli, P., Inventado, P.S., Heffernan, N. (2016) Semantic Features of Math Problems: Relationships to Student Learning and Engagement. Proceedings of the 9th International Conference on Educational Data Mining, 223-230.[pdf]

• Matayoshi, J., & Karumbaiah, S. (2021). Investigating the Validity of Methods Used to Adjust for Multiple Comparisons in Educational Data Mining. Proceedings of the International Conference on Educational Data Mining. [pdf]

Association Rule Mining and Sequential Pattern Mining

• Baker, R.S. (2023) Big Data and Education. Ch. 5, V2, V3.

• Merceron, A., Yacef, K. (2008) Interestingness Measures for Association Rules in Educational Data. Proceedings of the 1st International Conference on Educational Data Mining,57-66. [pdf]

• Kinnebrew, J. S., Loretz, K. M., & Biswas, G. (2013). A contextualized, differential sequence mining method to derive students’ learning behavior patterns. JEDM-Journal of Educational Data Mining, 5(1), 190-219.[pdf]

• Cukurova, M., Khan-Galaria, M., Millán, E., & Luckin, R. (2022). A Learning Analytics Approach to Monitoring the Quality of Online One-to-one Tutoring. Journal of Learning Analytics, 1-16. [pdf]