NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Buczak, Philip; Huang, He; Forthmann, Boris; Doebler, Philipp – Journal of Creative Behavior, 2023
Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns…
Descriptors: Computer Assisted Testing, Scoring, Automation, Creative Thinking
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
Peer reviewed Peer reviewed
Direct linkDirect link
Barnali Mazumdar; Nora De la Mora; Teresa Roberts; Alexander Swiderski; Maria Kapantzoglou; Gerasimos Fergadiotis – Journal of Speech, Language, and Hearing Research, 2024
Purpose: Anomia, or word-finding difficulty, is a prevalent and persistent feature of aphasia, a neurogenic language disorder affecting millions of people in the United States. Anomia assessments are essential for measuring performance and monitoring outcomes in clinical settings. This study aims to evaluate the reliability of response time (RT)…
Descriptors: Pictorial Stimuli, Naming, Aphasia, Reaction Time
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Thao-Trang Huynh-Cam; Long-Sheng Chen; Tzu-Chuen Lu – Journal of Applied Research in Higher Education, 2025
Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…
Descriptors: Foreign Countries, Undergraduate Students, At Risk Students, Dropout Characteristics