Evaluating the Integration and Impact of Artificial Intelligence (AI) Tools on Academic Learning, Assessment, and Research Practices in Higher Education
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| Title: | Evaluating the Integration and Impact of Artificial Intelligence (AI) Tools on Academic Learning, Assessment, and Research Practices in Higher Education |
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| Language: | English |
| Authors: | Vinoth S. (ORCID |
| Source: | Education and Information Technologies. 2025 30(18):25655-25682. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 28 |
| Publication Date: | 2025 |
| Intended Audience: | Policymakers; Teachers |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Technology Integration, Academic Achievement, Student Evaluation, Educational Research, Research Methodology, Higher Education, Individualized Instruction, Equal Education, Digital Literacy, Ethics, Privacy, Student Improvement, College Students, Access to Computers |
| DOI: | 10.1007/s10639-025-13719-x |
| ISSN: | 1360-2357 1573-7608 |
| Abstract: | This is a fast-changing landscape of higher education through the adoption of AI tools, opening new transformative possibilities in personalized learning, academic writing, and research productivity. This study makes a theoretical contribution by applying the lens of equity and technological adaptation frameworks to examine disparities in AI tool access, digital literacy gaps, and ethical concerns such as data privacy (51%) and over-dependency (42%). It follows a rigorous methodological approach by applying advanced machine learning techniques, including Decision Tree, Support Vector Machine, Principal Component Analysis, and Gradient Boosting Classifier, and a structured questionnaire to survey students across all disciplines. The results show a pivotal role of AI in enhancing academic performance, with 68% of students reporting improvement and a higher adoption rate in Business and Social Sciences as opposed to Engineering and Humanities. Principal Component Analysis shows that 63.69% of the variance in AI adoption is explained by improved study habits, academic performance, and understanding of complex concepts. However, 48% of rural students reported inadequate access to AI tools despite its benefits, thereby underlining the persistent inequities. The study concludes with actionable recommendations that governments can take, including infrastructure development, AI literacy, and ethical guidelines, towards fostering inclusive AI integration. Beyond its immediate implications for Indian higher education, these findings contribute to the global discourse on the transformative role of AI in education, thus serving as a source of insights for policymakers and educators worldwide. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1504426 |
| Database: | ERIC |
| Abstract: | This is a fast-changing landscape of higher education through the adoption of AI tools, opening new transformative possibilities in personalized learning, academic writing, and research productivity. This study makes a theoretical contribution by applying the lens of equity and technological adaptation frameworks to examine disparities in AI tool access, digital literacy gaps, and ethical concerns such as data privacy (51%) and over-dependency (42%). It follows a rigorous methodological approach by applying advanced machine learning techniques, including Decision Tree, Support Vector Machine, Principal Component Analysis, and Gradient Boosting Classifier, and a structured questionnaire to survey students across all disciplines. The results show a pivotal role of AI in enhancing academic performance, with 68% of students reporting improvement and a higher adoption rate in Business and Social Sciences as opposed to Engineering and Humanities. Principal Component Analysis shows that 63.69% of the variance in AI adoption is explained by improved study habits, academic performance, and understanding of complex concepts. However, 48% of rural students reported inadequate access to AI tools despite its benefits, thereby underlining the persistent inequities. The study concludes with actionable recommendations that governments can take, including infrastructure development, AI literacy, and ethical guidelines, towards fostering inclusive AI integration. Beyond its immediate implications for Indian higher education, these findings contribute to the global discourse on the transformative role of AI in education, thus serving as a source of insights for policymakers and educators worldwide. |
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| ISSN: | 1360-2357 1573-7608 |
| DOI: | 10.1007/s10639-025-13719-x |
