Title
Likelihood analysis of student enrollment outcomes using learning environment variables: a case study approach
Abstract
Tertiary institutions are increasing the emphasis on generating, collecting and analyzing student data as a means of targeting student support services. This study utilizes a data set from a regional Australian university to conduct logistic regression analyzing the student enrollment outcomes. The results indicate that demographic factors have a minor effect while institutional and learning environment variables play a more significant role in determining student enrollment outcomes. Using grade distribution compared to grade point average provides better estimates as to the effect particular grades have on enrollment outcomes. Moreover, the effect of an early alert system on enrollment outcomes shows that early identification has a significant relationship to a student's choice to stay enrolled versus discontinuing, lapsing or being inactive in their enrollment. These results are vital in the targeting of student support services at the case study institution. The significant results indicate the importance of learning environment variables in understanding student enrollment outcomes at tertiary institutions. This analysis forms part of a much larger research project analyzing student retention at the institution.
Year
DOI
Venue
2015
10.1145/2723576.2723621
LAK
Keywords
Field
DocType
statistical computing,logistic regression,early alert systems,linear programming,student retention,measurement,reliability,theory,multivariate statistics
Data science,Grading (education),Computer science,Learning environment,Logistic regression
Conference
Citations 
PageRank 
References 
1
0.37
5
Authors
4
Name
Order
Citations
PageRank
Scott Harrison121.07
Renato Villano291.18
Grace Lynch341.10
George Chen420.73