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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
Bejar, Isaac I.; Li, Chen; McCaffrey, Daniel – Applied Measurement in Education, 2020
We evaluate the feasibility of developing predictive models of rater behavior, that is, "rater-specific" models for predicting the scores produced by a rater under operational conditions. In the present study, the dependent variable is the score assigned to essays by a rater, and the predictors are linguistic attributes of the essays…
Descriptors: Scoring, Essays, Behavior, Predictive Measurement
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
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
Oswald, Christopher A. – ProQuest LLC, 2019
During the 1990s computers were placed into most educational classrooms; however, they sat underused or not used at all. One reason for this is students lacked the skills to use computers effectively. One set of skills that can help students make use of computers is self-regulated learning. By using think aloud protocol analysis while students…
Descriptors: Protocol Analysis, Learning Processes, Self Management, Regression (Statistics)
Baker, Ryan S.; Berning, Andrew W.; Gowda, Sujith M.; Zhang, Shizhu; Hawn, Aaron – Journal of Education for Students Placed at Risk, 2020
Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…
Descriptors: At Risk Students, High School Students, Dropout Prevention, Student Diversity
Fako, Thabo T.; Nkhukhu-Orlando, Esther; Wilson, Debra R.; Forcheh, Ntonghanwah; Linn, James G. – International Journal of Educational Administration and Policy Studies, 2018
Organizational commitment is a major determinant of organizational effectiveness and desirable employee attitudes and behaviours. Highly committed academic staff are the backbone of universities since they play an important role in the success of their institutions. This study investigated factors associated with organizational commitment among…
Descriptors: Foreign Countries, Organizational Climate, Performance Factors, Employee Attitudes
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
Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad – Journal of Experimental Education, 2017
Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…
Descriptors: Predictor Variables, Models, Predictive Measurement, Statistical Analysis
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
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Mertes, Scott J.; Hoover, Richard E. – Community College Journal of Research and Practice, 2014
Retention is a complex issue of great importance to community colleges. Several retention models have been developed to help explain this phenomenon. However, these models typically have used four-year college and university environments to build their foundations. Several researchers have attempted to identify predictor variables using…
Descriptors: Community Colleges, Predictor Variables, College Freshmen, Academic Persistence
Barrett, Jamie D.; Vessey, William B.; Griffith, Jennifer A.; Mracek, Derek; Mumford, Michael D. – Creativity Research Journal, 2014
There is little doubt that career experiences contribute to scientific achievement; however this relationship has yet to be thoroughly investigated in terms the effects on scientific creativity. In this study, a historiometric approach was used to examine 3 areas of adult career experiences common to scientific achievement. In doing so, prior…
Descriptors: Science Achievement, Prediction, Predictor Variables, Correlation
Lichtman, Allan – Social Education, 2012
Conventional pundits, pollsters, and forecasters are focused on whether the economy will improve sufficiently in 2012 for President Barack Obama to gain reelection. The Keys to the White House, a prediction system that the author developed in collaboration with Vladimir Keilis-Borok, founder of the International Institute of Earthquake Prediction…
Descriptors: Political Campaigns, Presidents, Elections, Economic Development