{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/79959"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/79959","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Predicting Student Dropout Risk in Online Graduate Programs: A Survival Analysis","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Coleman, Shannon; 0000-0002-5178-4787"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Lee, Jaekyung","Counseling, School and Educational Psychology"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-07-30T15:11:24Z","date_published":"2019-07-30T15:11:24Z","updated_at":"2026-07-27T19:05:21Z","subjects":["educational psychology","higher education"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/79959","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Lee, Jaekyung","Counseling, School and Educational Psychology"]},{"key":"dc:creator","label":"Author","values":["Coleman, Shannon; 0000-0002-5178-4787"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-07-30T15:11:24Z","2019","2019-05-15 17:08:59"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["educational psychology","higher education"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/79959"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Online education has been experiencing steadily increasing enrollment rates and it is therefore vital to study student and institutional factors related to dropout risk for online students. Currently, prior research examining this rapidly developing field is limited. With online graduate programs experiencing continuous growth in enrollment rates, this study aimed to extend the prior research by investigating factors related to dropout in exclusively online graduate programs in a graduate school of education at a large public university. This study focused solely on graduate students enrolled in exclusively online programs. This is a significant group within online students that has not been given proper attention in previous studies. Using survival analysis, this study created life tables and built Cox regression models to identify patterns of dropout risk across time, analyze time as a factor of dropout behavior, and establish relationships between dropout and predictor variables. The outcome variable of interest for this study, dropout, was defined as failure to successfully complete an online graduate program within 150% of the normal time to completion: 27 months for advanced graduate certificate students, 36 months for master’s students, and 90 months for PhD students. The time metric used was the number of months students were enrolled in online graduate programs, which was calculated from each student’s date of initial enrollment and the date each student discontinued enrollment in the program, either because of dropping out or being censored. Independent predictor variables examined included: student gender, ethnicity, age, GPA, and online graduate program type. Additionally, because the students in the sample entered their respective programs at different time points, a covariate was added to the model to control for when students initially began their programs. Students were most likely to drop out early in their enrollment with risk declining until an uptick in dropout is again observed after students have been enrolled longer than the normal time to completion. Cumulative GPA at the end of enrollment, program type, and age were found to be significant predictors of dropout risk. Students with lower GPAs were more likely to drop out as were students enrolled in advanced graduate certificate online programs. There was a significant interaction effect with age and program type that indicated older students were more likely to drop out for master’s programs specifically. There was not a significant age effect for doctoral or advanced graduate certificate students."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Predicting Student Dropout Risk in Online Graduate Programs: A Survival Analysis"]}]}],"canonical_facts":{"dc:contributor":["Lee, Jaekyung","Counseling, School and Educational Psychology"],"dc:creator":["Coleman, Shannon; 0000-0002-5178-4787"],"dc:date":["2019-07-30T15:11:24Z","2019","2019-05-15 17:08:59"],"dc:description":["Ph.D.","Online education has been experiencing steadily increasing enrollment rates and it is therefore vital to study student and institutional factors related to dropout risk for online students. Currently, prior research examining this rapidly developing field is limited. With online graduate programs experiencing continuous growth in enrollment rates, this study aimed to extend the prior research by investigating factors related to dropout in exclusively online graduate programs in a graduate school of education at a large public university. This study focused solely on graduate students enrolled in exclusively online programs. This is a significant group within online students that has not been given proper attention in previous studies. Using survival analysis, this study created life tables and built Cox regression models to identify patterns of dropout risk across time, analyze time as a factor of dropout behavior, and establish relationships between dropout and predictor variables. The outcome variable of interest for this study, dropout, was defined as failure to successfully complete an online graduate program within 150% of the normal time to completion: 27 months for advanced graduate certificate students, 36 months for master’s students, and 90 months for PhD students. The time metric used was the number of months students were enrolled in online graduate programs, which was calculated from each student’s date of initial enrollment and the date each student discontinued enrollment in the program, either because of dropping out or being censored. Independent predictor variables examined included: student gender, ethnicity, age, GPA, and online graduate program type. Additionally, because the students in the sample entered their respective programs at different time points, a covariate was added to the model to control for when students initially began their programs. Students were most likely to drop out early in their enrollment with risk declining until an uptick in dropout is again observed after students have been enrolled longer than the normal time to completion. Cumulative GPA at the end of enrollment, program type, and age were found to be significant predictors of dropout risk. Students with lower GPAs were more likely to drop out as were students enrolled in advanced graduate certificate online programs. There was a significant interaction effect with age and program type that indicated older students were more likely to drop out for master’s programs specifically. There was not a significant age effect for doctoral or advanced graduate certificate students."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/79959"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["educational psychology","higher education"],"dc:title":["Predicting Student Dropout Risk in Online Graduate Programs: A Survival Analysis"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:21Z"}