Matching Items (3)
Filtering by
- All Subjects: community college
- Creators: Thompson, Marilyn S
- Creators: Barber, Lori D.
Description
Many methodological approaches have been utilized to predict student retention and persistence over the years, yet few have utilized a Bayesian framework. It is believed this is due in part to the absence of an established process for guiding educational researchers reared in a frequentist perspective into the realms of Bayesian analysis and educational data mining. The current study aimed to address this by providing a model-building process for developing a Bayesian network (BN) that leveraged educational data mining, Bayesian analysis, and traditional iterative model-building techniques in order to predict whether community college students will stop out at the completion of each of their first six terms. The study utilized exploratory and confirmatory techniques to reduce an initial pool of more than 50 potential predictor variables to a parsimonious final BN with only four predictor variables. The average in-sample classification accuracy rate for the model was 80% (Cohen's κ = 53%). The model was shown to be generalizable across samples with an average out-of-sample classification accuracy rate of 78% (Cohen's κ = 49%). The classification rates for the BN were also found to be superior to the classification rates produced by an analog frequentist discrete-time survival analysis model.
ContributorsArcuria, Philip (Author) / Levy, Roy (Thesis advisor) / Green, Samuel B (Committee member) / Thompson, Marilyn S (Committee member) / Arizona State University (Publisher)
Created2015
Description
Although U.S. rates of college enrollment among 18-24 year olds have reached historic highs, rates of degree completion have not kept pace. This is especially evident at community colleges, where a disproportionate number of students from groups who, historically, have had low college-completion rates enroll. One way community colleges are attempting to address low completion rates is by implementing institutional interventions intended to increase opportunities for student engagement at their colleges. Utilizing logistic and linear regression analyses, this study focused on community college students, examining the association between participation in institutional support activities and student outcomes, while controlling for specific student characteristics known to impact student success in college. The sample included 746 first-time, full-time, degree-seeking students at a single community college located in the U.S. Southwest. Additional analyses were conducted for the 440 first-time, full-time, degree-seeking students in this sample who placed into at least one developmental education course. Findings indicate that significant associations exist between different types of participation in institutional interventions and various student outcomes: Academic advising was found to be related to increased rates of Fall to Spring and Fall to Fall persistence and, for developmental education students, participation in a student success course was found to be related to an increase in the proportion of course credit hours earned. The results of this study provide evidence that student participation in institutional-level support may relate to increased rates of college persistence and credit hour completion; however, additional inquiry is warranted to inform specific policy and program decision-making at the college and to determine if these findings are generalizable to populations outside of this college setting.
ContributorsBeckert, Kimberly Marrone (Author) / De Los Santos Jr., Alfredo G (Thesis advisor) / Thompson, Marilyn S (Thesis advisor) / Berliner, David C. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The function and purpose of higher education has changed over the last decade. COVID-19 exacerbated that change, but well before Coronavirus exploded on the world stage, standard operations at most colleges and universities were in flux. In 2013, a New York Times article predicted many colleges and universities would shutter their doors or merge with another institution. A new paradigm for post-secondary education is emerging akin to what American community colleges have been doing since their inception; they work closely with industry and the community in which they are situated to ensure they teach skills students need to receive a living wage job upon graduation. Change and disruption have engendered problems at times tantamount to chaos in the higher education space. To make meaningful modifications in higher education, the chaos of change should be harnessed to devise a better system, as transformative chaos works its power to create a more cohesive model. Moreover, if change is not managed with expertise, it has the potential to run amok, leaving organizations in ruins. The purpose of this study was to examine how a nine-week workshop based in mindfulness and gentle movement affected College of Eastern Idaho staff members’ ability to manage constant change to see if it might augment their coping, competence, self-efficacy, resiliency and reframe the chaos of change to opportunity for their careers, their department, and the college. Mixed methods of inquiry were utilized; data sources included two pre- and post-intervention staff surveys, a focus group interview with four participants, participant journals they kept throughout the nine-weeks, and the researcher’s field notes from individual one-on-one check-ins with participants. This study demonstrated that staff members at College of Eastern Idaho had difficulty efficaciously performing their jobs because of the constant change and initiative fatigue. The study found that a nine-week Mindfulness from the Mat workshop positively impacted staff members coping, competence, self-efficacy, resiliency, and their attitudes about change. Moreover, the workshop had unexpected benefits of positively impacting participants personal lives, too. The discussion includes implications for future practice and research and potential explanations for the findings.
ContributorsBarber, Lori D. (Author) / Ott, Molly (Thesis advisor) / Henriksen, Danah (Committee member) / Redington, Lyn (Committee member) / Arizona State University (Publisher)
Created2023