Washington College Mathematics Conference > 2018 Session Materials> Session V (Friday 2:35–3:25 p.m.)> Educational Data Mining: A Study of Usage Patterns in a Quantitative Tutoring Center [F2]

Educational Data Mining: A Study of Usage Patterns in a Quantitative Tutoring Center [F2]

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Robin Angotti, Tyler Shea & Abram Girgis • University of Washington Bothell • 3:00–3:25

Using the emerging field of Educational Data Mining (EDM), analysts can leverage large amounts of student data to discover meaningful information about learners or the structures of the educational system. UW Bothell faculty and undergraduate research (UGR) students extracted institutional data on student demographics and use statistics from a quantitative tutoring center. Using Exploratory Data Analysis and dynamic visualization software, the team studied differences in usage by gender and ethnicity, as well as the correlation of use and student grade. The team will discuss the process of mining data, data cleaning, joining multiyear data sets from two sources, and externalizing student data.

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