Residence Life initiated a research project on March 28th, 2017 designed to better understand predictive factors associated with student retention and completion based on housing information from current and former on-campus residents.
Since Residence Life serves the needs of students with diverse academic backgrounds, Residence Life is interested in using current and historical housing application data as well as student educational record data to develop a predictive model of student success. In addition, Residence Life is interested in using learner analytics and data mining techniques to make sense of the big data it had available on students’ learning. Residence Life will use these data in predicting student success so that interventions could be developed to assist students in need of support. Thus, the study aims to use predictive modeling and data mining to identify indicators of students’ success.
Significance: To use research to inform the development of interventions aimed at improving outcomes for undergraduate and graduate students living on the Texas A&M University campus.
Academic Support Initiatives