
Learning Data Analytics: Providing Actionable Insights to Increase College Student Success
Learning Data Analytics: Providing Actionable Insights to Increase College Student Success
Project Description: The objective of this project is to develop new computational methods to analyze large and diverse types of education and learning data to help (a) discover successful academic pathways for students; (b) improve pedagogy for instructors; and (c) enhance student persistence and retention for institutions. The project outcomes are designed to help students select courses that fit their needs, capabilities, and learning styles, and are likely to lead to (faster) graduation; help instructors to better meet student needs; and give advisors and institutions the analytics needed to improve retention and persistence. Research will coalesce into three pilot applications: DegreePlanner for students, CourseInsights for instructors, and StudentWatch for academic advisors.
Research Area(s): Big Data, Learning Analytics and Educational Data Mining
Funding: NSF#1447489
URL: http://www.nsf.gov/awardsearch/showAward?AWD_ID=1447489
Participants: Aditya Johri (IST), Huzefa Rangawala (CS, Project PI), Jaime Lester (Higher Education) and collaborators from University of Minnesota