Stopout, Swirl, Double-Dip, and Dropout: Attempting to Understand Student Enrollment Patterns

Schulte, Marthann

doi:10.1080/07377363.2015.1043001

Cited by 9 publications

(10 citation statements)

References 2 publications

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“…Donhardt [45] showed that a higher proportion of failed courses and the existence of stopouts had a negative impact on graduation, but this study was not specific with regard to high failure rate courses, and the sequence of events was not analyzed. Schulte [46] mentioned that stopout related to academic reasons is more often linked to dropout, because stopout could be used as a strategy to avoid or postpone failure by those students who eventually end in late dropout. Students who return from a stopout with high-failure rate courses they must retake have distanced themselves from their peer group, affecting both their sense of belonging and their self-efficacy beliefs [31].…”

Section: Discussionmentioning

confidence: 99%

Curricular Analytics to Characterize Educational Trajectories in High-Failure Rate Courses That Lead to Late Dropout

et al. 2021

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Late dropout is one of the most pressing challenges currently facing higher education, and the process that each student follows to arrive at that decision usually involves several academic periods. This work presents a curricular analytics approach at the program level, to analyze how educational trajectories of undergraduate students in high-failure rate courses help to describe the process that leads to late dropout. Educational trajectories (n = 10,969) of high-failure rate courses are created using Process Mining techniques, and the results are discussed based on established theoretical frameworks. Late dropout was more frequent among students who took a stopout while having high-failure rate courses they must retake. Furthermore, students who ended in late dropout with high-failure rate courses they must retake had educational trajectories that were on average shorter and less satisfactory. On the other hand, the educational trajectories of students who ended in late dropout without high-failure rate courses they must retake were more similar to those of students who graduated late. Moreover, some differences found among ISCED fields are also described. The proposed approach can be replicated in any other university to understand the educational trajectories of late dropout students from a longitudinal perspective, generating new knowledge about the dynamic behavior of the students. This knowledge can trigger improvements to the curriculum and in the follow-up mechanisms used to increase student retention.

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Section: Discussionmentioning

confidence: 99%

Curricular Analytics to Characterize Educational Trajectories in High-Failure Rate Courses That Lead to Late Dropout

et al. 2021

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“…Students stop out of college for a variety of reasons. Some of the most significant reasons students cite center around caregiving responsibilities, financial difficulties, and academic difficulties ( Donhardt, 2012 ; Lane et al, 2012 ; Hagelskamp et al, 2013 ; Schulte, 2015 ; Steele and Erisman, 2016 ; Mabel and Britton, 2017 ). Increasing work and family obligations directly conflict with the time needed to pursue an education and are the most frequently cited challenges for adult students.…”

Section: Introductionmentioning

confidence: 99%

Bringing them back: using latent class analysis to re-engage college stop-outs

West,

Chen,

Boika

2024

Front. Psychol.

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Half of the students who begin college do not complete a degree or certificate. The odds of completing a degree are decreased if a student has a low socio-economic status (SES), is the first in a family to attend college (first-generation), attends multiple institutions, stops out multiple times, reduces credit loads over time, performs poorly in major-specific coursework, has competing family obligations, and experiences financial difficulties. Stopping out of college does not always indicate that a student is no longer interested in pursuing an education; it can be an indication of a barrier, or several barriers faced. Institutions can benefit themselves and students by utilizing person-centered statistical methods to re-engage students they have lost, particularly those near the end of their degree plan. Using demographic, academic, and financial variables, this study applied latent class analysis (LCA) to explore subgroups of seniors who have stopped out of a public four-year Tier One Research intuition before graduating with a four-year degree. The findings indicated a six-class model was the best fitting model. Similar to previous research, academic and financial variables were key determinants of the latent classes. This paper demonstrates how the results of an LCA can assist institutions in the decisions around intervention strategies and resource allocations.

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“…(S) While many universities are increasing proactive measures to support student persistence, contemporary enrollment in post-secondary education is characterized by swirling attendance patterns and stop-outs. 22 We see our outreach to students who are not currently enrolled as a thread that may keep them connected to the university and prompt them to continue or return.…”

Section: Figure 1| Reported First or Second Undergraduate Majorsmentioning

confidence: 99%