AI in Education: Personalized Learning Systems and Their Impact on Student Performance and Engagement

This research investigates the effect of AI-based personalized learning systems on students' performance, engagement, and participation, as well as challenges and ethical issues related to AI implementation in education. Adopting a quantitative research approach, data were gathered from 268 university instructors from all provinces of Pakistan using a self-administered questionnaire. Correlation analysis indicated a high positive correlation between AI-based learning and student performance (r = 0.74, p < 0.001), whereas regression analysis indicated significant influence on participation and engagement (β = 0.72, p < 0.001). Moreover, chi-square findings validated that accessibility problems (χ² = 12.76, p < 0.001) and data privacy issues (χ² = 15.89, p < 0.001) are significant challenges. The results indicate that AI improves learning outcomes but needs meticulous implementation to overcome barriers of access, ethics, and the working of teachers. This research adds to the increasing body of research on AI-based education and highlights the importance of inclusive, ethical, and regulated adoption of AI in higher education.

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Publication Details

Journal
˜The œcritical review of social sciences studies
Published
2025-02-27
DOI
https://doi.org/10.59075/c35qa453
Citations
15
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
25.40
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article

AI in Education: Personalized Learning Systems and Their Impact on Student Performance and Engagement

Muhammad Aziz, Muhammad Jawed Iqbal, Shahid Abbas, Sadaf Saleem
15 citations
˜The œcritical review of social sciences studies
Online Learning and Analytics
25.40
article

AI in Education: Personalized Learning Systems and Their Impact on Student Performance and Engagement

Muhammad Aziz, Muhammad Jawed Iqbal, Shahid Abbas, Sadaf Saleem
article en
15 citations

Abstract

This research investigates the effect of AI-based personalized learning systems on students' performance, engagement, and participation, as well as challenges and ethical issues related to AI implementation in education. Adopting a quantitative research approach, data were gathered from 268 university instructors from all provinces of Pakistan using a self-administered questionnaire. Correlation analysis indicated a high positive correlation between AI-based learning and student performance (r = 0.74, p < 0.001), whereas regression analysis indicated significant influence on participation and engagement (β = 0.72, p < 0.001). Moreover, chi-square findings validated that accessibility problems (χ² = 12.76, p < 0.001) and data privacy issues (χ² = 15.89, p < 0.001) are significant challenges. The results indicate that AI improves learning outcomes but needs meticulous implementation to overcome barriers of access, ethics, and the working of teachers. This research adds to the increasing body of research on AI-based education and highlights the importance of inclusive, ethical, and regulated adoption of AI in higher education.

˜The œcritical review of social sciences studiesVol. 3(1)
The University of Agriculture, Peshawar (PK), Bahria University (PK), National University of Sciences and Technology (PK)
Openalex Percentile: Top 1%
Online Learning and Analytics
25.40
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