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Pei-Jung Wang; Hua-Fang Liao; Li-Chiou Chen; Lin-Ju Kang; Lu Lu; Karen Caplovitz Barrett – American Journal on Intellectual and Developmental Disabilities, 2024
Motivation is a key factor for child development, but very few studies have examined child and family predictors of both child task and perceived motivation. Thus, the three aims of this 6-month longitudinal study in preschoolers with global developmental delays (GDD) were to explore: 1) differences between task and perceived motivation in…
Descriptors: Preschool Children, Preschool Education, Developmental Delays, Child Development
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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
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Jessica Herring Watson; Ayanna Perkins; Amanda J. Rockinson-Szapkiw – TechTrends: Linking Research and Practice to Improve Learning, 2024
This predictive correlational study investigated to what extent, if at all, the constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) predicted special educators' use of assistive technology (AT) in virtual and hybrid settings during the COVID-19 pandemic. A survey was distributed to educators (n = 104) across the United…
Descriptors: Special Education Teachers, Technology Uses in Education, Electronic Learning, Blended Learning
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Duy M. Pham; Kirk P. Vanacore; Adam C. Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…
Descriptors: Middle School Students, Middle School Teachers, Middle School Mathematics, Algebra
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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
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Chen, Xiaobin; Meurers, Detmar – Journal of Research in Reading, 2018
Assessment of text readability is important for assigning texts at the appropriate level to readers at different proficiency levels. The present research approached readability assessment from the lexical perspective of word frequencies derived from corpora assumed to reflect typical language experience. Three studies were conducted to test how…
Descriptors: Word Frequency, Readability, Correlation, Predictive Measurement
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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
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Barramuño, Mauricio; Meza-Narváez, Claudia; Gálvez-García, Germán – Journal of Applied Research in Higher Education, 2022
Purpose: The prediction of student attrition is critical to facilitate retention mechanisms. This study aims to focus on implementing a method to predict student attrition in the upper years of a physiotherapy program. Design/methodology/approach: Machine learning is a computer tool that can recognize patterns and generate predictive models. Using…
Descriptors: Student Attrition, School Holding Power, Foreign Countries, Physical Therapy
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Naseem, Mohammed; Chaudhary, Kaylash; Sharma, Bibhya – Education and Information Technologies, 2022
The need for a knowledge-based society has perpetuated an increasing demand for higher education around the globe. Recently, there has been an increase in the demand for Computer Science professionals due to the rise in the use of ICT in the business, health and education sector. The enrollment numbers in Computer Science undergraduate programmes…
Descriptors: College Freshmen, Student Attrition, School Holding Power, Dropout Prevention
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How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Educational stakeholders would be better informed if they could use their students' formative assessments results and personal background attributes to predict the conditions for achieving favorable learning outcomes, and conversely, to gain awareness of the "at-risk" signals to prevent unfavorable or worst-case scenarios from happening.…
Descriptors: Artificial Intelligence, Bayesian Statistics, Models, Data Use
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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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Devine, Rory T.; Ribner, Andrew; Hughes, Claire – Child Development, 2019
This study of 195 (108 boys) children seen twice during infancy (Time 1: 4.12 months; Time 2: 14.42 months) aimed to investigate the associations between and infant predictors of executive function (EF) at 14 months. Infants showed high levels of compliance with the EF tasks at 14 months. There was little evidence of cohesion among EF tasks but…
Descriptors: Predictive Measurement, Predictor Variables, Individual Differences, Executive Function
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Inoue, Tomohiro; Georgiou, George K.; Muroya, Naoko; Hosokawa, Miyuki; Maekawa, Hisao; Parrila, Rauno – Journal of Research in Reading, 2020
Background: The present study aimed to examine the early growth of word and nonword reading fluency and their cognitive predictors in a consistent syllabic orthography (Japanese "Hiragana"). Method: One hundred sixty-nine Grade 1 Japanese children (M[subscript age] = 80.12 months, SD = 3.62) were followed until the middle of Grade 2 and…
Descriptors: Reading Fluency, Predictive Measurement, Grade 1, Elementary School Students
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William T. Gormley; Sara Amadon; Katherine Magnuson; Amy Claessens; Douglas Hummel-Price – AERA Open, 2023
In this study, we used data from a cohort of 4,033 Tulsa kindergarten students to investigate the relationship between pre-K enrollment and later college enrollment. Specifically, we tested whether participation in the Tulsa Public Schools universal pre-K program and the Tulsa Community Action Project (CAP) Head Start program predicted enrollment…
Descriptors: Preschool Education, Access to Education, Public Schools, Kindergarten
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Yamamoto, Scott H.; Alverson, Charlotte Y. – Autism & Developmental Language Impairments, 2022
Background and Aims: The fastest growing group of students with disabilities are those with Autism Spectrum Disorder (ASD). States annually report on post-high school outcomes (PSO) of exited students. This study sought to fill two gaps in the literature related to PSO for exited high-school students with ASD and the use of state data and…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, High School Graduates, Outcomes of Education
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