Supporting student success through predictive analytics: Preparing to intervene
PROCEEDING
Kerry Rice, Andy Hung, Boise State University, United States
Society for Information Technology & Teacher Education International Conference, in Online ISBN 978-1-939797-48-3 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
Abstract
Researchers will present findings from a series of three data mining studies designed to test the accuracy and power of differing Educational Data Mining, Machine, and Deep Learning methods. The design of an intervention study in the spring of 2020 will also be discussed along with any preliminary findings.
Citation
Rice, K. & Hung, A. (2020). Supporting student success through predictive analytics: Preparing to intervene. In D. Schmidt-Crawford (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 709-713). Online: Association for the Advancement of Computing in Education (AACE). Retrieved September 29, 2022 from https://www.learntechlib.org/primary/p/215814/.
© 2020 Association for the Advancement of Computing in Education (AACE)
Slides
- presentation_3104_55817.pptx (Access with Subscription)
- SITE2020.pptx (Access with Subscription)
