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Showing 1 to 15 of 56 results Save | Export
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Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S. – Online Learning, 2018
Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…
Descriptors: Performance Factors, Online Courses, Electronic Learning, Models
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
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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
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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
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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
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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
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Herrera, Cheryl; Blair, Jennifer – Research in Higher Education Journal, 2015
As the U.S. population ages and policy changes emerge, such as the Patient Protection and Affordable Care Act of 2010, the U.S. will experience a significant shortage of Registered Nurses (RNs). Many colleges and universities are attempting to increase the size of nursing cohorts to respond to this imminent shortage. Notwithstanding a 2.6%…
Descriptors: Prediction, Success, Nursing Education, Nursing Students
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Liu, Xiangwei; Ma, Xin – Journal of Curriculum and Teaching, 2012
The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…
Descriptors: Prediction, Predictive Validity, Predictive Measurement, Models
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Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
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Fernandes Malaquias, Rodrigo; de Oliveira Malaquias, Fernanda Francielle – Turkish Online Journal of Distance Education, 2014
The objective of this study was to validate a scale for assessment of academic projects. As a complement, we examined its predictive ability by comparing the scores of advised/corrected projects based on the model and the final scores awarded to the work by an examining panel (approximately 10 months after the project design). Results of…
Descriptors: Predictive Measurement, Predictive Validity, Predictor Variables, Test Construction
Guarino, Cassandra M.; Reckase, Mark D.; Stacy, Brian W.; Wooldridge, Jeffrey M. – Education Policy Center at Michigan State University, 2014
We study the properties of two specification tests that have been applied to a variety of estimators in the context of value-added measures (VAMs) of teacher and school quality: the Hausman test for choosing between random and fixed effects and a test for feedback (sometimes called a "falsification test"). We discuss theoretical…
Descriptors: Achievement Gains, Evaluation Methods, Teacher Effectiveness, Educational Quality
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Alcaraz, Saul; Torregrosa, Miquel; Viladrich, Carme – Research Quarterly for Exercise and Sport, 2015
Purpose: The purpose of the present research was to test how behavioral regulations are mediated between basic psychological needs and psychological well-being and ill-being in a sample of team-sport coaches. Based on self-determination theory, we hypothesized a model where satisfaction and thwarting of the basic psychological needs predicted…
Descriptors: Well Being, Psychological Needs, Athletic Coaches, Motivation
Lin, Jien-Jou – ProQuest LLC, 2013
Every year a group of graduates from high schools enter the engineering programs across this country with remarkable academic record. However, as reported in numerous studies, the number of students switching out of engineering majors continues to be an important issue. Previous studies have suggested various factors as predictors for student…
Descriptors: Success, Prediction, Predictive Measurement, Predictive Validity
Goldhaber, Dan; Chaplin, Duncan – Center for Education Data & Research, 2012
In a provocative and influential paper, Jesse Rothstein (2010) finds that standard value added models (VAMs) suggest implausible future teacher effects on past student achievement, a finding that obviously cannot be viewed as causal. This is the basis of a falsification test (the Rothstein falsification test) that appears to indicate bias in VAM…
Descriptors: School Effectiveness, Teacher Effectiveness, Achievement Gains, Statistical Bias
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