Quantifying the relationship between student enrollment patterns and student performance (2003.10874v4)

Abstract: Simplified categorizations have often led to college students being labeled as full-time or part-time students. However, at many universities student enroLLMent patterns can be much more complicated, as it is not uncommon for students to alternate between full-time and part-time enroLLMent each semester based on finances, scheduling, or family needs. While prior research has established full-time students maintain better outcomes then their part-time counterparts, limited study has examined the impact of enroLLMent patterns or strategies on academic outcomes. In this paper, we applying a Hidden Markov Model to identify and cluster students' enroLLMent strategies into three different categorizes: full-time, part-time, and mixed-enroLLMent strategies. Based the enroLLMent strategies we investigate and compare the academic performance outcomes of each group, taking into account differences between first-time-in-college students and transfer students. Analysis of data collected from the University of Central Florida from 2008 to 2017 indicates that first-time-in-college students that apply a mixed enroLLMent strategy are closer in performance to full-time students, as compared to part-time students. More importantly, during their part-time semesters, mixed-enroLLMent students significantly outperform part-time students. Similarly, analysis of transfer students shows that a mixed-enroLLMent strategy is correlated a similar graduation rates as the full-time enroLLMent strategy, and more than double the graduation rate associated with part-time enroLLMent. Such a finding suggests that increased engagement through the occasional full-time enroLLMent leads to better overall outcomes.