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Abstract Title: Supporting Future Educational Data Miners through a Summer Research Internship
Abstract: Educational data mining is an emerging field that leverages large-scale data collected by university registration systems, online learning portals, and other digital data collection systems. Text data and modern machine learning methods are used to gain insight into undergraduate student learning, participation, and other outcomes. These data can be connected to traditional PER data such as surveys and concept inventories and be used to produce new insights in the PER space. In 2019, the University of Oslo and Michigan State University offered a nine week summer internship program for bachelor's and master's students. Eight students attended from China, Norway, and the United States. Students learned how to use SQL databases and python to clean and parse dirty data, visualize that data, and build machine learning models to predict outcomes. This poster presents an outline of the summer program and the projects the students pursued.
Abstract Type: Contributed Poster Presentation
Session Time: Poster Session III
Poster Number: C7

Author/Organizer Information

Primary Contact: John Aiken
University of Oslo
sem saelands vei 24
Oslo, Non U.S. 0316
Phone: 40477189
and Co-Presenter(s)
Rachel Henderson, Nicholas Young, Marcos D. Caballero

all: michigan state university