Harnessing Artificial Intelligence for Educational Innovation: Enhancing Learning Outcomes and Teaching Practices
Amani BOUCHAREB
Amar Telidji University of Laghouat, Algeria
a.bouchareb@lagh-univ.dz
https://orcid.org/0000-0002-0285-0610
Hafsa GHEDIR
Amar Telidji University of Laghouat, Algeria
h.ghedir@lagh-univ.dz
https://orcid.org/0009-0005-2135-0506
Abstract
The rapid advancement of Artificial Intelligence offers a transformative opportunity for education by potentially revolutionizing teaching and learning practices. This study investigates the use of artificial intelligence tools, such as intelligent tutoring systems and adaptive learning platforms, to enhance personalized and engaging learning experiences. The significance of the study lies in its exploration of how artificial intelligence can improve student engagement, academic outcomes, and operational efficiency through automation and predictive analytics. The findings reveal that AI-powered personalized learning platforms enhance student involvement and academic results. However, challenges such as ethical concerns, data protection, and algorithmic bias must be addressed through robust data governance and ongoing oversight. The study also emphasizes the importance of comprehensive training and support for educators, advocating for the integration of artificial intelligence with best practices that involve stakeholder inclusion, iterative testing, and context-specific approaches. By considering these ethical and practical issues, the successful implementation of artificial intelligence can maximize its benefits in educational settings.
Keywords: adaptive learning, artificial intelligence, educational innovation, personalized learning
How to Cite this Paper :
Bouchareb, A., & Ghedir, H. (2024). Harnessing Artificial Intelligence for educational innovation: Enhancing learning outcomes and teaching practices. Atras Journal, 5 (Special Issue),414-431
DOI:
https://doi.org/10.70091/atras/AI.26
References:
Carnegie Learning. (2024). AI in education report. https://discover.carnegielearning.com/ai-in-education
Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of Artificial Intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
Dönmez, E. (2024). The future of education: AI-supported reforms in the USA and China BT – Global agendas and education reforms: A comparative study (B. Akgün & Y. Alpaydın (Eds.); pp. 135–150). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3068-1_7
Hooda, M., Rana, C., Dahiya, O., Rizwan, A., & Hossain, M. S. (2022). Artificial Intelligence for assessment and feedback to enhance student success in higher education. Mathematical Problems in Engineering, 2022(1), 5215722. https://doi.org/10.1155/2022/5215722
Igbokwe, I. (2023). Application of Artificial Intelligence (AI) in educational management. International Journal of Scientific and Research Publications (IJSRP), 13, 300. https://doi.org/10.29322/IJSRP.13.03.2023.p13536
Jia, F., Sun, D., & Looi, C. (2024). Artificial Intelligence in science education (2013–2023): Research trends in ten years. Journal of Science Education and Technology, 33(1), 94–117. https://doi.org/10.1007/s10956-023-10077-6
Joshi, M. (2024). Adaptive learning through Artificial Intelligence. International Journal on Integrated Education, 7, 41–43. https://doi.org/10.2139/ssrn.4514887
Lee, A. V. Y., Koh, E., & Looi, C. K. (2023). AI in education and learning analytics in Singapore: An overview of key projects and initiatives. Information and Technology in Education and Learning, 3(1), Inv-p001-Inv-p001. https://doi.org/10.12937/itel.3.1.Inv.p001
Lin, C.-C., Huang, A. Y. Q., & Lu, O. H. T. (2023). Artificial Intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y
Microsoft. (2024). AI in education report. http://aka.ms/AIinEDUReport
Murtaza, M., Ahmed, Y., Shamsi, J. A., Sherwani, F., & Usman, M. (2022). AI-based personalized E-learning systems: Issues, challenges, and solutions. IEEE Access, 10, 81323–81342. https://doi.org/10.1109/ACCESS.2022.3193938
Niraj, R. (2024). How AI virtual teaching assistants enhance instruction and learning. EdTech. https://www.harbingergroup.com/blogs/how-ai-virtual-teaching-assistants-enhance-instruction-and-learning/
Patel, B. (2023). AI and analytics in higher education: Transforming decision-making. Amoghvarta, 03(02), 57–65. https://www.amoghvarta.com/uploads/current_issue/1697888149I-and-Analytics-in-Higher-Education-Transforming-Decision-Making.pdf
Patil, S., & T. D., P. (2024). Case studies on Artificial Intelligence for sustainable education in the 21st century. Shodh Disha, 62(6), 303-310.
U.S. Department of Education. (2024). Artificial Intelligence and the future of teaching and learning: Insights and recommendations. https://www2.ed.gov/documents/ai-report/ai-report.pdf
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