Enhancing adult learner success in higher education through decision tree models: A machine learning approach

  • Emily Barnes Capitol Technology University, AI Center of Excellence (AICE), Laurel, MD 20708, USA
  • James Hutson Lindenwood University, Saint Charles, MO 63301, USA
  • Karriem Perry Capitol Technology University, Laurel, MD 20708, USA
Ariticle ID: 1415
99 Views, 58 PDF Downloads
DOI: https://doi.org/10.59400/fes.v2i3.1415
Keywords: adult learners; decision tree models; machine learning; higher education; predictive accuracy

Abstract

This article explores the use of machine learning, specifically Classification and Regression Trees (CART), to address the unique challenges faced by adult learners in higher education. These learners confront socio-cultural, economic, and institutional hurdles, such as stereotypes, financial constraints, and systemic inefficiencies. The study utilizes decision tree models to evaluate their effectiveness in predicting graduation outcomes, which helps in formulating tailored educational strategies. The research analyzed a comprehensive dataset spanning the academic years 2013–2014 to 2021–2022, evaluating the predictive accuracy of CART models using precision, recall, and F1 score. Findings indicate that attendance, age, and Pell Grant eligibility are key predictors of academic success, demonstrating the strong capability of the model across various educational metrics. This highlights the potential of machine learning (ML) to improve data-driven decision-making in educational settings. The results affirm the effectiveness of Decision Tree (DT) models in meeting the educational needs of adult learners and underscore the need for institutions to adapt their strategies to provide more inclusive and supportive environments. This study advocates for a shift towards nuanced, data-driven approaches in higher education, emphasizing the development of strategies that address the distinct challenges of adult learners, aiming to enhance inclusivity and support within the sector.

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Published
2024-07-09
How to Cite
Barnes, E., Hutson, J., & Perry, K. (2024). Enhancing adult learner success in higher education through decision tree models: A machine learning approach. Forum for Education Studies, 2(3), 1415. https://doi.org/10.59400/fes.v2i3.1415
Issue
Vol. 2 No. 3 (2024)
Section
Article

Copyright (c) 2024 Emily Barnes, James Hutson, Karriem Perry

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