Transforming Higher Education with Adaptive AI Driven-Learning: Challenges and Opportunities
Palabras clave:
Artificial intelligence, Adaptive learning, Student engagement, Motivation, Higher educationResumen
Artificial Intelligence (AI) for adaptative learning is revolutionizing higher education by offering personalized learning experiences tailored to individual student needs. By leveraging real-time data analysis, AI-driven platforms can adapt content delivery, provide targeted feedback, and suggest customized learning paths based on each student’s strengths and weaknesses. In this context, this study investigates the effectiveness and perceptions of adaptive AI-driven learning systems among nursing faculty at a private university in Chile (n= 66). Using a quantitative, non-experimental design, a Likert-type questionnaire with 20 items was administered to a group of instructors to find out the systems' impact on student engagement, motivation and learning outcomes. Results reveal that adaptive AI-driven learning is highly regarded for improving conceptual understanding and information retention. The findings highlight strengths in enhancing student engagement and motivation, while identifying areas for further refinement. These insights contribute to understanding the practical implications of integrating adaptive AI into higher education and offer recommendations for optimizing system design and implementation.
Citas
Barnes, E. & Hutson, J. (2024). Strategic Integration of AI in Higher Education and Industry: The AI8-Point Model. Advances in Social Sciences and Management, 2(6), 39-52. https://digitalcommons.lindenwood.edu/cgi/viewcontent.cgi?article=1659&context=faculty-research-papers
George, B. & Wooden, O. (2023). Managing the Strategic Transformation of Higher Education through Artificial Intelligence. Administrative Sciences, 13(9):196. https://doi.org/10.3390/admsci13090196
Gligorea, I., Cioca, M., Oancea R., Gorski, A-T, Gorski, H. & Tudorache, P. (2023). Adaptive Learning Using Artificial Intelligence in e-Learning: A Literature Review. Education Sciences, 13(12):1216. https://doi.org/10.3390/educsci13121216
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 1-13. https://doi.org/10.3390/educsci13070692
Håkansson, A., Dündar, Y. C. & Hartung, R. L. (2023). Towards Robustness Analysis for Adaptive Artificial Intelligence in Multi-Autonomous agent systems. Procedia Computer Science, 225, 4657-4666. https://www.sciencedirect.com/science/article/pii/S1877050923016228
Joshi, M.A. (2024). Adaptive Learning through Artificial Intelligence. International Journal on Integrated Education, 7(2), 41-43. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4514887
Kamalov, F.; Santandreu Calonge, D. & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability 15, 12451, 2-27. https://doi.org/10.3390/su151612451
Karimi, H. & Khawaja, S. (2023). The Impact of Artificial Intelligence on Higher Education in England. Creative Education, 14(12), 2405-2415. https://www.scirp.org/journal/paperinformation?paperid=129811
Lange, K. (2023). Adaptive AI: Components, Use Cases, & Ethics. https://www.splunk.com/en_us/blog/learn/adaptive-ai.html
OECD (2023). OECD Digital Education Outlook 2023. An Overview. https://www.oecd.org/content/dam/oecd/en/about/projects/edu/smart-data-and-digital-technology-in-education/Chapter1_DL_WEB.pdf/_jcr_content/renditions/original./Chapter1_DL_WEB.pdf
Salmons, J. (2023). Quantitative Research with Nonexperimental Designs. Research Design. https://researchmethodscommunity.sagepub.com/blog/quantitative-research-with-non-experimental-designs
Smartsparrow (n.d.). What is Adaptive Learning? https://www.smartsparrow.com/what-is-adaptive-learning/
Vera, F. (2023a). Integrating Artificial Intelligence (AI) in the EFL Classroom: Benefits and Challenges. Transformar, 4(2), 66–77. https://revistatransformar.cl/index.php/transformar/article/view/93
Vera, F. (2023b). Faculty members’ perceptions of artificial intelligence in higher education: a comprehensive study. Transformar, 4(3), 55–68. https://revistatransformar.cl/index.php/transformar/article/view/103
Vera, F. (2023c). Faculty members’ perceptions of artificial intelligence in higher education: a comprehensive study. Transformar, 4(3), 55–68. https://revistatransformar.cl/index.php/transformar/article/view/103
Webisoft (2024). Adaptive AI: Explore the Use Cases, Examples, and Others. https://webisoft.com/articles/adaptive-ai/
