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Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics
Cannistrà, Marta; Masci, Chiara; Ieva, Francesca; Agasisti, Tommaso; Paganoni, Anna Maria – Studies in Higher Education, 2022
This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…
Descriptors: Dropouts, Potential Dropouts, Dropout Prevention, Dropout Characteristics
Huang, Liuli; Roche, Lahna R.; Kennedy, Eugene; Brocato, Melissa B. – International Journal of Higher Education, 2017
Many researchers have explored the relationships between the likelihood of graduating from college and demographic and pre-college factors such as gender, race/ethnicity, high school grade point average (GPA), and standardized test scores. However, additional factors such as a student's college major, home address, or use of learning support in…
Descriptors: Graduation Rate, Predictor Variables, Predictive Measurement, Predictive Validity
Deering, Pamela Rose – ProQuest LLC, 2014
This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…
Descriptors: Comparative Analysis, Multiple Regression Analysis, Hierarchical Linear Modeling, Mathematics Achievement
Wladis, Claire; Conway, Katherine M.; Hachey, Alyse C. – Online Learning, 2016
This study explored the interaction between student characteristics and the online environment in predicting course performance and subsequent college persistence among students in a large urban U.S. university system. Multilevel modeling, propensity score matching, and the KHB decomposition method were used. The most consistent pattern observed…
Descriptors: Online Courses, Electronic Learning, Learning Readiness, Student Characteristics
Bozick, Robert; Gonzalez, Gabriella; Engberg, John – Journal of Student Financial Aid, 2015
The Pittsburgh Promise is a scholarship program that provides $5,000 per year toward college tuition for public high school graduates in Pittsburgh, Pennsylvania who earned a 2.5 GPA and a 90% attendance record. This study used a difference-in-difference design to assess whether the introduction of the Promise scholarship program directly…
Descriptors: Merit Scholarships, College Bound Students, Enrollment Influences, Enrollment Management
Singh, Malkeet – Journal of Educational Research, 2015
Closing the achievement gap in public education is a worthy goal that has been included as a top priority in the No Child Left Behind Act of 2001 (2002). This study analyzed the most salient predictors at the student and school levels to identify their long-term impact on mathematics achievement from the elementary grades to high school. The…
Descriptors: Socioeconomic Influences, Achievement Gap, Public Education, Mathematics Achievement
Flores, Raymond; Inan, Fethi; Lin, Zhangxi – Journal of Computers in Mathematics and Science Teaching, 2013
In this study, the National Educational Longitudinal Study (ELS:2002) dataset was used and a predictive data mining technique, decision tree analysis, was implemented in order to examine which factors, in conjunction to computer use, can be used to predict high or low probability of success in high school mathematics. Specifically, this study…
Descriptors: Educational Technology, Computer Uses in Education, Longitudinal Studies, Predictor Variables
Cawthon, Stephanie W.; Caemmerer, Jacqueline M.; Dickson, Duncan M.; Ocuto, Oscar L.; Ge, Jinjin; Bond, Mark P. – Applied Developmental Science, 2015
Social skills function as a vehicle by which we negotiate important relationships and navigate the transition from childhood into the educational and professional experiences of early adulthood. Yet, for individuals who are deaf, access to these opportunities may vary depending on their preferred language modality, family language use, and…
Descriptors: Predictor Variables, Prediction, Predictive Measurement, Predictive Validity
Van Bragt, Cyrille A. C.; Bakx, Anouke W. E. A.; Bergen, Theo C. M.; Croon, Marcel A. – Higher Education: The International Journal of Higher Education and Educational Planning, 2011
The central goal of this study is to clarify to what degree former education and students' personal characteristics (the "Big Five personality characteristics", personal orientations on learning and students' study approach) may predict study outcome (required credits and study continuance). Analysis of the data gathered through questionnaires of…
Descriptors: Academic Achievement, Credits, Educational Attainment, Academic Persistence
Cohen, Kristin E. – Online Submission, 2012
This study was designed to investigate the factors that affect master's student persistence in the United States. More specifically, this study explored whether the following factors: students' background, institution's, academic, environmental and psychological influences, had a significant effect on whether a master's student persisted and/or…
Descriptors: Academic Persistence, Student Attrition, Models, Performance Factors
Lau, Wilfred W. F.; Yuen, Allan H. K. – Computers & Education, 2011
In the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of…
Descriptors: Foreign Countries, Academic Achievement, Information Technology, Least Squares Statistics
Wang, Xueli – Journal of Higher Education, 2012
This study examined factors associated with the upward transfer of baccalaureate aspirants beginning at community colleges. Based on data from the National Education Longitudinal Study of 1988 and the Postsecondary Education Transcript Study, a sequential logistic regression analysis was conducted to predict bachelor's degree-seeking community…
Descriptors: Community Colleges, Performance Factors, College Transfer Students, Longitudinal Studies
Kitmitto, Sami – National Center for Education Statistics, 2011
The National Center for Education Statistics (NCES) continues to be interested in addressing the issue identified by the Government Accountability Office (GAO). With the release of the 2009 National Assessment of Educational Progress (NAEP) reading and mathematics assessments, NCES again had the opportunity to measure the status and change in…
Descriptors: Inclusion, Disabilities, National Competency Tests, Methods
Johnson, James – NACADA Journal, 2013
In an effort to standardize academic risk assessment, the NCAA developed the graduation risk overview (GRO) model. Although this model was designed to assess graduation risk, its ability to predict grade-point average (GPA) remained unknown. Therefore, 134 individual risk assessments were made to determine GRO model effectiveness in the…
Descriptors: Risk Assessment, College Athletics, Athletes, Graduation Rate