A Study of Attitude Towards AI Among Higher Education Students with Respect to Academic Stream Arts & Science
DOI:
https://doi.org/10.55544/ijrah.6.3.43Keywords:
AI, Higher education, impact, learning & teachingAbstract
Artificial intelligence (AI) has been a topic of growing interest and investigation in various fields, including higher education. This research article explores the impact of AI on higher education by examining its effects on teaching and learning, assessment, ethics, required skills, and future careers. The aim of this study is to analyse the influence of AI on higher education, investigate its impact on the teaching and learning process, examine its effect on assessment and grading, and predict its influence on graduates' future careers. To accomplish this, the study employs a qualitative approach based on a survey of the higher education audience. The results of this study demonstrate the crucial role of AI in the future of higher education. The findings highlight the effectiveness and efficiency of AI in equipping graduates with new skills for their future careers. They also emphasise the importance of considering the ethical implications of AI. The study reveals that higher education institutions need to integrate AI more extensively in their programs to prepare graduates for the future workforce.AI has the potential to revolutionize education by personalizing teaching methods to suit individual student needs, providing prompt feedback, and automating administrative tasks. It can also assist in grading and assessment, freeing educators to focus on developing curriculum and providing quality instruction. The study findings suggest that AI has a positive impact on the learning experience by facilitating the acquisition of new knowledge and skills. This research provides insights into the potential of AI to transform higher education and contribute to the development of new skills for graduates. It has important implications for educators, policymakers, and other stakeholders in the higher education sector. The study findings suggest that AI should be more extensively integrated into higher education curricula, and that institutions need to consider the ethical implications of AI in the development and implementation of their programs. By doing so, they can better prepare graduates for the demands of the future workforce.
Downloads
References
Acid, S. and De Campos. L. M., Searching for Bayesian network structures in the space of restricted acyclic partially directed graphs, Journal of Artificial Intelligence Research, Vol. 18, pp.445-490. 2003.
Alai, M., AI, scientific discovery and realism, Minds and Machines, Vol. 14, No. 1, pp.21-42, 2004.
Al-Ani, A. and Derice, M., A new technique for combining multiple classifiers using the dempster- Shafer theory of evidence, Journal of Artificial Intelligence Research, Vol. 17, pp.333-361, 2002.
Ambit, J. L. and Knoblock, C. A., Planning by rewriting, Journal of Artificial Intelligence Research, Vol. 15, pp.207-261, 2001.
Andrew, A. M., Short paper: lifemanship and AI. Kubernetes: The International Journal of Systems & Cybernetics, Vol. 30, No. 2. 2001.
Argaman-Engelson, S. and Dagan, I., Committee-based sample selection for probabilistic classifiers, Journal of Artificial Intelligence Research, Vol. 11, pp.335-360, 1999
K. and Bench-Capon T., Practical reasoning as presumptive argumentation using action based alternating transition systems, Artificial Intelligence, Vol. 171, No. 10-15, pp.855-874, 2007.
Baader, F., Lutz, C., Sturm, H. and Wolter, F., Fusions of description logics and abstract description systems, Journal of Artificial Intelligence Research, Vol. 16, pp.1-58, 2002.
Bacchus, F., The power of modelling response to PDDL2.1., Journal of Artificial Intelligence Research, Vol. 20, pp.125-132, 2003.
Baget, J. F. and Mugnier, M. L., Extensions of simple conceptual graphs: the complexity of rules and constraints, Journal of Artificial Intelligence Research, Vol. 16, pp.425-465, 2002.
Bleszinski, M., Czogala, E., Jemielniak, K. and Leslie J., Tool condition monitoring using artificial intelligence methods, Engineering Applications of Artificial Intelligence, Vol. 15, Issue 1, pp.73-80, 2002.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Neha Srivastava, Chandni Verma

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















