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Showing 1 to 15 of 191 results Save | Export
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Cláudio Manoel Ferreira Leite; Herbert Ugrinowitsch; Crislaine Rangel Couto – Journal of Motor Learning and Development, 2024
Knowledge of results (KR), particularly its informational role, has often been regarded as redundant for learning interception-like tasks, such as coincidence-anticipation timing tasks. However, it is possible that the KR's guiding effect might be detrimental to motor adaptation, instead of only redundant, leading to a dependency on KR and…
Descriptors: Foreign Countries, Undergraduate Students, Psychomotor Skills, Motor Development
Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
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Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
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Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
Matthew J. Salganik; Ian Lundberg; Alexander T. Kindel; Caitlin E. Ahearn; Khaled Al-Ghoneim; Abdullah Almaatouq; Drew M. Altschul; Jennie E. Brand; Nicole Bohme Carnegie; Ryan James Compton; Debanjan Datta; Thomas Davidson; Anna Filippova; Connor Gilroy; Brian J. Goode; Eaman Jahani; Ridhi Kashyap; Antje Kirchner; Stephen McKay; Allison C. Morgan; Alex Pentland; Kivan Polimis; Louis Raes; Daniel E. Rigobon; Claudia V. Roberts; Diana M. Stanescu; Yoshihiko Suhara; Adaner Usmani; Erik H. Wang; Muna Adem; Abdulla Alhajri; Bedoor AlShebli; Redwane Amin; Ryan B. Amos; Lisa P. Argyle; Livia Baer-Bositis; Moritz Büchi; Bo-Ryehn Chung; William Eggert; Gregory Faletto; Zhilin Fan; Jeremy Freese; Tejomay Gadgil; Josh Gagné; Yue Gao; Andrew Halpern-Manners; Sonia P. Hashim; Sonia Hausen; Guanhua He; Kimberly Higuera; Bernie Hogan; Ilana M. Horwitz; Lisa M. Hummel; Naman Jain; Kun Jin; David Jurgens; Patrick Kaminski; Areg Karapetyan; E. H. Kim; Ben Leizman; Naijia Liu; Malte Möser; Andrew E. Mack; Mayank Mahajan; Noah Mandell; Helge Marahrens; Diana Mercado-Garcia; Viola Mocz; Katariina Mueller-Gastell; Ahmed Musse; Qiankun Niu; William Nowak; Hamidreza Omidvar; Andrew Or; Karen Ouyang; Katy M. Pinto; Ethan Porter; Kristin E. Porter; Crystal Qian; Tamkinat Rauf; Anahit Sargsyan; Thomas Schaffner; Landon Schnabel; Bryan Schonfeld; Ben Sender; Jonathan D. Tang; Emma Tsurkov; Austin van Loon; Onur Varol; Xiafei Wang; Zhi Wang; Julia Wang; Flora Wang; Samantha Weissman; Kirstie Whitaker; Maria K. Wolters; Wei Lee Woon; James Wu; Catherine Wu; Kengran Yang; Jingwen Yin; Bingyu Zhao; Chenyun Zhu; Jeanne Brooks-Gunn; Barbara E. Engelhardt; Moritz Hardt; Dean Knox; Karen Levy; Arvind Narayanan; Brandon M. Stewart; Duncan J. Watts; Sara McLanahan – Grantee Submission, 2020
How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning…
Descriptors: Life Satisfaction, Family Life, Quality of Life, Disadvantaged
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Morris, Darrell; Perney, Jan – Reading & Writing Quarterly, 2018
After considering the relationships between (a) reading fluency and reading rate and (b) reading rate and sight vocabulary, this study addressed a very practical question. Can a cut score on a sight vocabulary task (1-min) predict level of reading fluency 4+ months into the future? The prediction was tested at multiple times point across grades…
Descriptors: Reading Fluency, Sight Method, Sight Vocabulary, Predictive Validity
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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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Stadler, Matthias J.; Becker, Nicolas; Greiff, Samuel; Spinath, Frank M. – Higher Education Research and Development, 2016
Successful completion of a university degree is a complex matter. Based on considerations regarding the demands of acquiring a university degree, the aim of this paper was to investigate the utility of complex problem-solving (CPS) skills in the prediction of objective and subjective university success (SUS). The key finding of this study was that…
Descriptors: Success, Predictive Validity, Predictor Variables, Problem Solving
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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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Peters, S. Colby; Woolley, Michael E. – Children & Schools, 2015
Data from the School Success Profile generated by 19,228 middle and high school students were organized into three broad categories of risk and protective factors--control, support, and challenge--to examine the relative and combined power of aggregate scale scores in each category so as to predict academic success. It was hypothesized that higher…
Descriptors: Academic Achievement, Success, Risk, Risk Assessment
Eickhoff, Mary Ann – ProQuest LLC, 2016
There is currently a nursing shortage in the United States. By 2022, the Bureau of Labor Statistics (BLS) expects, the number of job openings for Practical Nurses (PN) will be 168,500, an increase of 25% over 2012 (BLS, 2014). Nursing education does not currently meet present, much less future needs. Nursing programs have limited space; according…
Descriptors: Nursing Students, Predictor Variables, Success, Licensing Examinations (Professions)
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Legrand, Fabien D.; Joly, Philippe M.; Bertucci, William M. – Research Quarterly for Exercise and Sport, 2015
Purpose: Increased core (brain or body) temperature that accompanies exercise has been posited to play an influential role in affective responses to exercise. However, findings in support of this hypothesis have been equivocal, and most of the performed studies have been done in relation to anxiety. The aim of the present study was to investigate…
Descriptors: Exercise Physiology, Exercise, Affective Measures, Metabolism
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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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