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Emily J. Barnes – ProQuest LLC, 2024
This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…
Descriptors: Artificial Intelligence, Higher Education, Models, Prediction
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Rohemi Zuluaga; Alicia Camelo-Guarín; Enrique De La Hoz – Journal on Efficiency and Responsibility in Education and Science, 2023
This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The…
Descriptors: Foreign Countries, Higher Education, Educational Practices, Efficiency
Cody Gene Singer – ProQuest LLC, 2023
College and university enrollment has decreased nationwide every year for more than a decade as educational consumers increasingly question the value of higher education and discover alternatives to the traditional university system. Enrollment professionals seeking growth are tasked to develop and implement innovative solutions to address…
Descriptors: Data Collection, Predictor Variables, Electronic Learning, Enrollment
Thomas M. Kirnbauer – ProQuest LLC, 2021
This dissertation's two primary purposes were to construct an alternative socioeconomic status model and estimate how it predicts student success in higher education. This research filled a gap in knowledge about the widely acknowledged disparities in higher education based on socioeconomic status. Prior research has often relied on parental…
Descriptors: Models, Predictor Variables, Socioeconomic Status, Academic Achievement
Najib A. Mozahem – Sage Research Methods Cases, 2021
The internet has had a vast and pervasive effect on many industries. It has resulted in the creation of new industries and has overhauled the dynamics that governed existing industries. One of the most traditional industries that is now struggling to cope with the changes brought on by the internet is the industry of higher education. Students can…
Descriptors: Social Sciences, Electronic Learning, Learning Management Systems, Higher Education
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Montgomery, Amanda P.; Mousavi, Amin; Carbonaro, Michael; Hayward, Denyse V.; Dunn, William – British Journal of Educational Technology, 2019
Blended learning (BL) is a popular e-Learning model in higher education that has the potential to take advantage of learning analytics (LA) to support student learning. This study utilized LA to investigate fourth-year undergraduates' (n = 157) use of self-regulated learning (SRL) within the online components of a previously unexamined BL…
Descriptors: Blended Learning, Educational Technology, Higher Education, Undergraduate Students
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Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – Annenberg Institute for School Reform at Brown University, 2021
Colleges have increasingly turned to predictive analytics to target at-risk students for additional support. Most of the predictive analytic applications in higher education are proprietary, with private companies offering little transparency about their underlying models. We address this lack of transparency by systematically comparing two…
Descriptors: At Risk Students, Higher Education, Predictive Measurement, Models
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Lee, Don Dong-hyun; Cho, Soon-jeong – Asia Pacific Education Review, 2021
For outsiders to higher education institutions (HEIs) in South Korea, predicting the outcomes of the International Education Quality Assurance System (IEQAS)--a Korean institutional accreditation system for HEIs--is challenging. The annual IEQAS accreditation has been conducted behind closed doors; the assessment process is confidential, and there…
Descriptors: Foreign Countries, Accreditation (Institutions), Quality Assurance, Educational Quality
Glazer, Randy – ProQuest LLC, 2019
Employee turnover continues to be discussed as an outcome in Human Resources (HR), but comparatively few studies have examined the relationship between turnover as the independent variable and institutional outcomes. Although the call to HR practitioners has often been made over the past 20 years regarding the importance of tying HR programs and…
Descriptors: Labor Turnover, Employees, Correlation, Human Resources
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Raju, Dheeraj; Schumacker, Randall – Journal of College Student Retention: Research, Theory & Practice, 2015
The study used earliest available student data from a flagship university in the southeast United States to build data mining models like logistic regression with different variable selection methods, decision trees, and neural networks to explore important student characteristics associated with retention leading to graduation. The decision tree…
Descriptors: Student Characteristics, Higher Education, Graduation Rate, Academic Persistence
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Karatas, Serçin; Yilmaz, Ayse Bagriacik; Dikmen, Cemal Hakan; Ermis, Ugur Ferhat; Gürbüz, Onur – Quarterly Review of Distance Education, 2017
The aim of this study is to determine the trend concerning interaction in distance education between the years 2011 and 2015. According to this aim, 544 articles in the databases of EBSCO, Scopus, and Web of Science were examined. The examination has been conducted on the basis of various variables including year, country, number of authors,…
Descriptors: Distance Education, Trend Analysis, Interaction, Qualitative Research
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Martín-García, Antonio Víctor; Martínez-Abad, Fernando; Reyes-González, David – British Journal of Educational Technology, 2019
The purpose of the study is to analyse and identify the stages of adoption of the blended learning (BL or b-learning) methodology in higher education contexts, and to assess the relationship of these stages with a set of variables related to personal and professional characteristics, attributes perceived on BL and contextual variables. About 980…
Descriptors: Blended Learning, Adoption (Ideas), Higher Education, Educational Technology
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Fynn, Angelo – International Review of Research in Open and Distributed Learning, 2016
The prediction and classification of student performance has always been a central concern within higher education institutions. It is therefore natural for higher education institutions to harvest and analyse student data to inform decisions on education provision in resource constrained South African environments. One of the drivers for the use…
Descriptors: Academic Achievement, Higher Education, Foreign Countries, Data Collection
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Tran, Carolyn-Dung T. T.; Villano, Renato A. – Journal of Further and Higher Education, 2017
This article provides an analysis of the academic performance of higher education institutions (HEIs) in Vietnam with 50 universities and 50 colleges in 2011/12. The two-stage semiparametric data envelopment analysis is used to estimate the efficiency of HEIs and investigate the effects of various factors on their performance. The findings reveal…
Descriptors: Foreign Countries, Higher Education, Institutional Characteristics, Efficiency
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