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Direct linkEmily J. Barnes – ProQuest LLC, 2024
This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…
Descriptors: Artificial Intelligence, Higher Education, Models, Prediction
Peer reviewed
Download full textDowdall, Leah; Sheerin, Edel; O'Reilly, Niamh – Adult Learner: The Irish Journal of Adult and Community Education, 2019
This article is a reflection on the National Further Education and Training (FET) Learner Forum (NFLF). It uses the NFLF as an example of learner voice in practice, retracing the history of the NFLF as a means of reflecting on some of the benefits and challenges of bringing learner voice into public policy. The article outlines educational debates…
Descriptors: Adult Education, Adult Students, Individual Power, Discussion Groups
St. John, Victor; Gabriel, Alexander – National Technical Assistance Center for the Education of Neglected or Delinquent Children and Youth (NDTAC), 2021
The primary purpose of Title 1, Part D programs is to improve the educational outcomes for youth who are categorized as "neglected" (n), "delinquent" (d), or at-risk under the statute. This brief is designed to help State Coordinators, grantees involved in data collection or analyses, and personnel involved in the design of…
Descriptors: Elementary Secondary Education, Federal Legislation, Educational Legislation, At Risk Students
