June 14, 2015
June 14, 2015
June 17, 2015
Educational Research and Methods
26.1103.1 - 26.1103.10
Major Changes and Attrition: An Information Theoretic and Statistical Examination of Cohort Features Stratified on Major Switches Previous work in education statistics on major switching has demonstrated that studentswho eventually graduate take longer to leave the system with every change of major. The sametrend, unexpectedly, was also discovered for students who inevitably fail to graduate. A betterunderstanding of how these trends can be differentiated as the number of major switches increasewould be a great boon to policymakers on both institutional and departmental levels of decisionmaking. We utilize the Multiple-Institution Database for Investigating Engineering LongitudinalDevelopment (MIDFIELD) as a base set to compute relevant statistical and information theoreticvalues for the cohorts of students who eventually graduate the system and those that do not,breaking each subset up by the number of majors an observation is shown to have. The use of theMIDFIELD database for statistical modeling and high level feature analysis has been previouslydocumented and its coverage of over 13% of US engineering students makes it ideal for this task. The cohorts above are created from observations of 871,742 first-time in college (FTIC)students across eleven US institutions. We examine these broken up cohorts by looking atdemographic and temporal features, in particular the terms until attrition, and perform odds ratiotests to examine the probability of a student, having switched a certain number of majors,belonging to a particular cohort. We also compute information theoretic values such as mutualinformation to develop a proxy for how much we can know about these particular classes ofstudents given information on their major switches. The values above will be presented with similar work done on the database itself toprovide a high level examination of the feature space present in MIDFIELD and how it comparesto those students graduating or not. The results here couple with concurrent work to derive moreeffective classification and statistical modeling of the phenomena of major switches at a moregranular level.
Ricco, G. D., & Ryan, J. F. (2015, June), Major Changes and Attrition: An Information Theoretic and Statistical Examination of Cohort Features Stratified on Major Switches Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.24440
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