ELI Webinar | Learning Analytics: Using Big Data to Predict Student Success
West Virginia University’s College of Human Resources and Education
Sebastián Díaz, who serves as Senior Statistician for the PAR Framework, is an Associate Professor in the Department of Technology, Learning & Culture at West Virginia University. He teaches in the areas of Statistics, Program Evaluation, Measurement, and Education Law, and also serves as a Strategic Planning and Evaluation Consultant for International Student Affairs and Global Services. His research focuses on developing measurement instruments and evaluation methodologies germane to Intellectual Capital and Knowledge Management. Sebastián also serves as President of Diaz Consulting, LLC, dedicated to helping clients develop sound Knowledge Management practices. Before entering the tenure-track, Sebastián worked as a medical educator at both allopathic and osteopathic institutions. Sebastián earned a B.S. in Chemistry from Marietta College, a Ph.D. in Educational Research & Evaluation from Ohio University, and a law degree from the University of Akron.
Director of Academic Technologies
University of Hawaii System
Hae Okimoto is director of academic technologies for the University of Hawaii System. She is responsible for the planning, development, and implementation of an effective teaching and learning environment supporting distance, hybrid, and face-to-face formats. In addition, the Academic Technologies group manages the learning management system (Sakai), the student information system (Ellucian), web-based services, and user services. Having begun her professional life in student affairs, the use of data to improve services and support for students in their academic journey continues to be a focus of her research. She received her BA and MS from the University of Southern California and her PhD from the University of Hawaii at Manoa.
Join Malcolm Brown, EDUCAUSE Learning Initiative director, and Veronica Diaz, ELI associate director, as they moderate this webinar with Sebastian Diaz and Hae Okimoto on a multi-institutional proof-of-concept project on looking at data of online learning to predict retention, progression, and completion. Despite increasing enrollments in postsecondary institutions, completion rates have generally remained unchanged for the past 30 years and half of these students do not attain a degree within six years of initial enrollment. Although online learning has provided access for students, as well as a convenient alternative to face-to-face instruction, this innovative platform for learning is similarly laden with retention-related concerns.
This webinar will describe how six postsecondary institutions worked together toward determining factors that contribute to retention, progression, and completion of online learners with specific purposes: (1) to reach consensus on a common set of variables among the six institutions that inform student retention, progression and completion, and; (2) to discover advantages and/or disadvantages to particular statistical and methodological approaches to predicting factors related to retention, progression and completion. In the relatively short timeframe of the study, approximately 30 convenience variables informing retention, progression, and completion were identified and defined by the six participating institutions. Statistical analyses explored the associations among variables and as predictors for academic progression. In addition to the statistical results obtained, the project revealed insights into organizational challenges inherent in any study involving multiple institutions and their respective data.