To What Extent Does AI-Precision Education Improve Student Learning Outcomes Compared to Traditional Instructional Methods

Authors

  • Bekam Jogora kotebe University of Education Menilik I Science Shared Campus

Abstract

Precision education has emerged as a key focus in modern education, with AI playing a critical role in customizing learning experiences. This research examines how AI-personalized education influences student learning outcomes compared to traditional methods. Through a comprehensive analysis of recent studies and academic data, the study highlights the unique advantages of AI-driven learning environments, such as real-time feedback and individualized instruction. The findings demonstrate a marked improvement in student engagement and performance, positioning AI-personalized education as a powerful tool for enhancing educational outcomes. These results offer significant implications for future educational practices and policy-making.

Key Words: AI-Precision Education, Student Learning Outcomes, Traditional Instructional Methods, Personalized Learning, Adaptive Learning, Behavioral Data, Engagement Metrics, Real-Time Feedback, Resource Utilization, Retention Rates, ANCOVA

Downloads

Published

2026-02-04

Data Availability Statement

The Data set is uploaded along side the research paper.

Issue

Vol. 19 No. 1 (2025)

Section

Research Articles

License

Copyright (c) 2026 Intersect: The Stanford Journal of Science, Technology, and Society

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).