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Agus Santoso; Heri Retnawati; Kartianom; Ezi Apino; Ibnu Rafi; Munaya Nikma Rosyada – Open Education Studies, 2024
The world's move to a global economy has an impact on the high rate of student academic failure. Higher education, as the affected party, is considered crucial in reducing student academic failure. This study aims to construct a prediction (predictive model) that can forecast students' time to graduation in developing countries such as Indonesia,…
Descriptors: Time to Degree, Open Universities, Foreign Countries, Predictive Measurement
McCarthy, Richard V.; Ceccucci, Wendy; McCarthy, Mary; Sugurmar, Nirmalkumar – Information Systems Education Journal, 2021
This case is designed to be used in business analytics courses; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People's United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize…
Descriptors: Business Administration Education, Data Analysis, Prediction, Crime
Kelli A. Bird; Benjamin L. Castleman; Zachary Mabel; Yifeng Song – AERA Open, 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, Identification, Two Year College Students, Community Colleges
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
Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
Yanagiura, Takeshi – Community College Research Center, Teachers College, Columbia University, 2020
Among community college leaders and others interested in reforms to improve student success, there is growing interest in adopting machine learning (ML) techniques to predict credential completion. However, ML algorithms are often complex and are not readily accessible to practitioners for whom a simpler set of near-term measures may serve as…
Descriptors: Community Colleges, Man Machine Systems, Artificial Intelligence, Prediction
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
Yanagiura, Takeshi – Community College Review, 2023
Objective: This study examines how accurately a small set of short-term academic indicators can approximate long-term outcomes of community college students so that decision-makers can take informed actions based on those indicators to evaluate the current progress of large-scale reform efforts on long-term outcomes, which in practice will not be…
Descriptors: Community Colleges, Community College Students, Educational Indicators, Outcomes of Education
Davis, Glenn M.; Hanzsek-Brill, Melissa B.; Petzold, Mark Carl; Robinson, David H. – Journal of the Scholarship of Teaching and Learning, 2019
Educational institutions increasingly recognize the role that student belonging plays in retention. Many studies in this area focus on helping students improve a sense of belonging before they matriculate or identifying belonging as a reason for their departure. This study measures students' sense of belonging at key transition points during the…
Descriptors: School Holding Power, Predictive Measurement, Instructional Effectiveness, Academic Persistence
Aiken, John M.; Henderson, Rachel; Caballero, Marcos D. – Physical Review Physics Education Research, 2019
Physics education research (PER) has used quantitative modeling techniques to explore learning, affect, and other aspects of physics education. However, these studies have rarely examined the predictive output of the models, instead focusing on the inferences or causal relationships observed in various data sets. This research introduces a modern…
Descriptors: Physics, Bachelors Degrees, College Science, Student Records
Ganchorre, Athena; Buxner, Sanlyn; Vassquez, Jacob Alfredo – AERA Online Paper Repository, 2017
A predictive model for the USMLE Step 1 was created based on NBME Comprehensive Basic Sciences Self-Assessment (CBSSA) exams. All second year medical students at a southwestern university from 2014-2016 took a NBME CBSSA exam under controlled testing conditions six months (January) and three months (April) prior to their Step 1. A multiple…
Descriptors: Medical Students, Licensing Examinations (Professions), Academic Achievement, Predictive Measurement
Qin, Lu; Phillips, Glenn Allen – International Journal of Higher Education, 2019
The 3-year graduation rate is a rarely measured metric in higher education compared to its 4- or 6- year graduation rate counterparts. For the first time in college (FTIC) students to graduate in three years, they must come with certain skills, abilities, plans, supports, or motivations. This project considers two distinct but interrelated ways of…
Descriptors: Graduation Rate, Time to Degree, College Credits, Grade Point Average
Rajabalee, Yousra Banoor; Santally, Mohammad Issack; Rennie, Frank – International Journal of Distance Education Technologies, 2020
This paper reports the findings of a research using marks of students in learning activities of an online module to build a predictive model of performance for the final assessment of the module. The objectives were (1) to compare the performances of students of two cohorts in terms of continuous learning assessment marks and final learning…
Descriptors: Performance Factors, Electronic Learning, Learning Analytics, Learning Activities
Hao, Jinmei; Li, Suke – Journal of Education and Practice, 2017
With the adjustment of industrial structure of China in recent years, the market urgently needs different levels of professionals. Specialty education is an important part of higher education in China, has its unique advantages. Through the analysis of the history data of specialty education in our country, the result shows that the specialty…
Descriptors: Foreign Countries, Specialization, Specialists, Enrollment Trends
Marini, Jessica P.; Shaw, Emily J.; Young, Linda – College Board, 2016
During the transition period between the use of exclusively old SAT® scores and the use of exclusively new SAT scores, college admission offices will be receiving both types of scores from students. Making an admission decision based on new SAT scores can be challenging at first because institutions have methods, procedures, and models based on…
Descriptors: College Entrance Examinations, Scores, College Admission, Decision Making