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Article . 2026
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Impact of Artificial Intelligence on Academic Achievement at the tertiary level of Education

Authors: Kartick Chandra Mandal; Minakshi Malik; Dr. Gopa Saha Roy; Dr. Chandan Adhikary;

Impact of Artificial Intelligence on Academic Achievement at the tertiary level of Education

Abstract

Artificial Intelligence (AI) in higher education is transforming the teaching–learning process and student performance. This research explores the effect of AI on the learning outcome of university students. This study is mainly intended to investigate the extent of AI usage, measure the academic performance of students and predict the academic performance with the help of AI. Descriptive and inferential statistics have been employed to analyse data gathered by using standard scales of AI and academic achievement from 200 postgraduate students of University of Burdwan. Data were analyzed using descriptive statistics, Pearson’s correlation, regression analysis and t-test. The findings indicated that the participants have a moderate level of AI usage (M=3.42) and a moderate level of academic achievement (M=3.58). There was a significant positive association (r=0.62, p<0.01) between AI usage and academic performance. Regression analysis showed that AI use significantly predicted academic success (β = 0.62, R² = 0.38). There were no significant gender differences in AI use. The discussion emphasizes that AI improves learning by personalized support, engagement and academic support efficiency, while the usage is moderate because of such reasons as digital literacy and pedagogical integration. The research finds that AI has a great impact on the tertiary student’s academic performance, suggesting in turn that it is a very effective solution in raising the efficacy of teaching and learning.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green