Enhancing Personalized Learning Through Artificial Intelligence: Opportunities and Challenges in Modern Classrooms

This quantitative study explored student perceptions of the impact of AI-enabled personalized learning in four domains (engagement, perceived usefulness, feedback quality, and self-regulation support). Addressing the limitations of prior work, this experimental study builds on mounting enthusiasm for AI as a mechanism to personalize instruction one that is poised to scale in primary and middle school environments along with the lack of substantive evidence of the good conditions under which it might succeed across classrooms. Researcher collected data from 300 students (150 male, 150 female) in grades of five to eight, using a purposive sampling strategy from the school with AI personalized learning platforms. A structured questionnaire designed on a five-point Likert scale assessed student perceptions, and the reliability of the scales was established with Cronbach’s α values ranging from 0.80 to 0.86. Overall response descriptive statistics (means, standard deviations) as well as independent-samples t-tests and one-way ANOVA were calculated to determine differences in survey responses by gender and grade level. Students generally held favorable attitudes toward AI personalization, with a positive intention towards use scores of at least 3.85 in all subscales (Table 2). AI also maintained the highest average rating for increasing (1) student interest [engagement, M = 4.08] and student perceived learning value [perceived usefulness, M = 4.02]. The quality of feedback (M = 3.89) and support for self-regulation (M = 3.95) were rated a little lower but also very positive. There were no differences found between male and female students, indicating that both genders benefitted equally. There were respective grade-level differences for engagement and perceived utility, though, with the 6th graders reporting higher scores on those dimensions than did 5th graders. AI-supported personalization for students improves engagement and perceived learning benefits with system design implications, offering equitable experiences across genders; but considering developmental differences. Expert recommendations reflect the need to integrate AI tools with curricular goals, offer ongoing teacher training, and conduct equity audits for remaining conscientious community practices. These results add to the existing literature on how AI can be used appropriately in contemporary schools.

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Publication Details

Journal
Research Journal for Social Affairs
Published
2025-08-15
DOI
https://doi.org/10.71317/rjsa.003.05.0358
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Enhancing Personalized Learning Through Artificial Intelligence: Opportunities and Challenges in Modern Classrooms

Bushra Mustafa Kamal, Farah Fida, Muhammad Owais Ifzal
Research Journal for Social Affairs
Online Learning and Analytics
article

Enhancing Personalized Learning Through Artificial Intelligence: Opportunities and Challenges in Modern Classrooms

Bushra Mustafa Kamal, Farah Fida, Muhammad Owais Ifzal
article en

Abstract

This quantitative study explored student perceptions of the impact of AI-enabled personalized learning in four domains (engagement, perceived usefulness, feedback quality, and self-regulation support). Addressing the limitations of prior work, this experimental study builds on mounting enthusiasm for AI as a mechanism to personalize instruction one that is poised to scale in primary and middle school environments along with the lack of substantive evidence of the good conditions under which it might succeed across classrooms. Researcher collected data from 300 students (150 male, 150 female) in grades of five to eight, using a purposive sampling strategy from the school with AI personalized learning platforms. A structured questionnaire designed on a five-point Likert scale assessed student perceptions, and the reliability of the scales was established with Cronbach’s α values ranging from 0.80 to 0.86. Overall response descriptive statistics (means, standard deviations) as well as independent-samples t-tests and one-way ANOVA were calculated to determine differences in survey responses by gender and grade level. Students generally held favorable attitudes toward AI personalization, with a positive intention towards use scores of at least 3.85 in all subscales (Table 2). AI also maintained the highest average rating for increasing (1) student interest [engagement, M = 4.08] and student perceived learning value [perceived usefulness, M = 4.02]. The quality of feedback (M = 3.89) and support for self-regulation (M = 3.95) were rated a little lower but also very positive. There were no differences found between male and female students, indicating that both genders benefitted equally. There were respective grade-level differences for engagement and perceived utility, though, with the 6th graders reporting higher scores on those dimensions than did 5th graders. AI-supported personalization for students improves engagement and perceived learning benefits with system design implications, offering equitable experiences across genders; but considering developmental differences. Expert recommendations reflect the need to integrate AI tools with curricular goals, offer ongoing teacher training, and conduct equity audits for remaining conscientious community practices. These results add to the existing literature on how AI can be used appropriately in contemporary schools.

Research Journal for Social AffairsVol. 3(5)
Hamdard University (PK), Government College University, Faisalabad (PK), University of Education (PK)
Openalex Percentile: Top 77%
Online Learning and Analytics
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