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Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Arnold, Kimberly E. – ProQuest LLC, 2017
In the 21st century, attainment of a college degree is more important than ever to achieve economic self-sufficiency, employment, and an adequate standard of living. Projections suggest that by 2020, 65% of jobs available in the U.S. will require postsecondary education. This reality creates an unprecedented demand for higher education, and…
Descriptors: Educational Technology, Profiles, Biographies, Demography
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Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
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Rafferty, Anna N., Ed.; Whitehill, Jacob, Ed.; Romero, Cristobal, Ed.; Cavalli-Sforza, Violetta, Ed. – International Educational Data Mining Society, 2020
The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…
Descriptors: Educational Improvement, Teaching Methods, Information Retrieval, Data Processing
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Carter, Nancy; Felton, Nathan; Schwertman, Neil – Journal of Statistics Education, 2014
Engaging students in active learning can enhance their understanding and appreciation of a subject such as statistics. Classroom activities and projects help to engage students and further promote the learning process. In this paper, an activity investigating the influence of population size and wealth on the medal counts from the 2012 London…
Descriptors: Class Activities, Demography, Athletics, Awards
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Wu, Bian; Hu, Yiling; Gu, Xiaoqing; Lim, Cher Ping – Journal of Educational Computing Research, 2016
As information and communication technology (ICT) continues to develop, it is essential for teachers to acquire ability for teaching with ICT. In China, new higher education (HE) teachers often lack teaching experience because there are limited teaching opportunities during their postgraduate studies. This status quo may compromise the quality of…
Descriptors: Professional Development, Higher Education, Beginning Teachers, College Faculty
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Tienken, Christopher H.; Colella, Anthony; Angelillo, Christian; Fox, Meredith; McCahill, Kevin R.; Wolfe, Adam – RMLE Online: Research in Middle Level Education, 2017
The use of standardized test results to drive school administrator evaluations pervades education policymaking in more than 40 states. However, the results of state standardized tests are strongly influenced by non-school factors. The models of best fit (n = 18) from this correlational, explanatory, longitudinal study predicted accurately the…
Descriptors: Predictor Variables, Standardized Tests, Test Results, Models
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Goltz, Heather Honore; Smith, Matthew Lee – Practical Assessment, Research & Evaluation, 2010
Yule (1903) and Simpson (1951) described a statistical paradox that occurs when data is aggregated. In such situations, aggregated data may reveal a trend that directly contrasts those of sub-groups trends. In fact, the aggregate data trends may even be opposite in direction of sub-group trends. To reveal Yule-Simpson's paradox (YSP)-type…
Descriptors: Data, Statistics, Statistical Analysis, Models
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Nickelson, Jen; Bryant, Carol A.; McDermott, Robert J.; Buhi, Eric R.; DeBate, Rita D. – Journal of School Health, 2012
Background: The prevalence of obesity among high school students has risen in recent decades. Many high school students report trying to lose weight and some engage in disordered eating to do so. The obesity proneness model suggests that parents may influence their offspring's development of disordered eating. This study examined the viability of…
Descriptors: Obesity, Incidence, High School Students, Eating Disorders
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Boston, Wallace E.; Ice, Phil – Online Journal of Distance Learning Administration, 2011
As the growth of online programs continues to rapidly accelerate, concern over the retention of the online learner is increasing. Educational administrators at institutions offering online courses, those fully online or brick and mortars, are eager to promote student achievement. Retention is critically important, not just for student success, but…
Descriptors: Electronic Learning, Academic Achievement, Online Courses, Academic Persistence
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Ramineni, Chaitanya; Trapani, Catherine S.; Williamson, David M.; Davey, Tim; Bridgeman, Brent – ETS Research Report Series, 2012
Automated scoring models for the "e-rater"® scoring engine were built and evaluated for the "GRE"® argument and issue-writing tasks. Prompt-specific, generic, and generic with prompt-specific intercept scoring models were built and evaluation statistics such as weighted kappas, Pearson correlations, standardized difference in…
Descriptors: Scoring, Test Scoring Machines, Automation, Models
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Dabney, Katherine P.; Chakraverty, Devasmita; Tai, Robert H. – Science Education, 2013
With recent attention to improving scientific workforce development and student achievement, there has been a rise in effort to understand and encourage student engagement in physical science. This study examines the association of family influence and initial interest in science through multiple and logistic regression models. Research questions…
Descriptors: Science Interests, Physical Sciences, Science Education, Learner Engagement
Hammer, Patricia Cahape; Hixson, Nate – West Virginia Department of Education, 2014
This is the first of three evaluation reports on the effectiveness of a regional train-the-trainer strategy to support classroom implementation of the Next Generation Content Standards and Objectives (NxGen CSOs). This report focuses on six regional Educator Enhancement Academies (EEAs) hosted by the eight regional education service agencies…
Descriptors: Trainers, Program Effectiveness, Program Evaluation, Teacher Educator Education
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Wang, Aubrey H.; Walters, Alyssa M.; Thum, Y. M. – International Journal of Educational Management, 2013
Purpose: The purpose of this paper is to provide an empirical comparison of two measures of school success -- a value-added assessment system and the federally-mandated system of adequate yearly progress (AYP) -- to identify highly effective urban schools in the USA and to explore the predictive relationship between evidence-based decision-making…
Descriptors: Comparative Analysis, Evaluation Methods, Educational Indicators, Federal Programs
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