ENHANCING STUDENT ENGAGEMENT IN PRIVATE COLLEGES IN CHENNAI: THE ROLE OF ARTIFICIAL INTELLIGENCE AND GAMIFICATION
Abstract
Purpose: This study investigates the transformative potential of artificial intelligence (AI) and gamification in elevating student engagement within the context of private colleges in Chennai, India. This research targets the dynamic population of students attending these institutions, aiming to shed light on how AI and gamification strategies impact their educational experience. Methodology: Data collection was carried out using an online questionnaire designed to capture student perspectives on the role of AI and gamification in their academic engagement. Initially, 215 questionnaires were received, with 50 being excluded due to incomplete or inconsistent responses. Initially a pilot study was conducted to refine the questionnaire and establish its reliability. Statistical Analysis: The collected data underwent rigorous statistical analyses, including correlation, regression, and structural equation modeling (SEM). These statistical techniques were employed to explore the complex relationships between AI, gamification, and student engagement. Findings: The research findings reveal significant positive correlations between the integration of AI and gamification and student engagement within private colleges in Chennai. Specifically, AI-driven personalized learning platforms and gamified educational content were identified as major drivers of student engagement. Regression analysis demonstrated that the incorporation of AI and gamification accounted for a substantial portion of the variance in student engagement scores. Moreover, the SEM analysis established a robust structural model, emphasizing the positive influence of AI and gamification on student engagement. Suggestions: In light of the findings, we recommend that private colleges in Chennai consider implementing AI-based personalized learning systems and gamified educational content in their pedagogical approaches. Faculty members should receive training to effectively utilize AI tools and gamification strategies, enhancing student engagement. Furthermore, these institutions should invest in the necessary technological infrastructure to support the seamless integration of these innovative approaches.
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References
1. Adare-TasiwoopaÁpi, S., & Silva, N. K. (2023). Gamification in higher education. Gamification in Higher Education, 26–35. https://doi.org/10.4324/9781003444954-4 2. Ahmed, M. S., Chunduri, P., &Vivek, S. (2020). Improving faculty pedagogy through use of Artificial intelligence- A student engagement facilitation tool. EDULEARN Proceedings. https://doi.org/10.21125/edulearn.2020.0136 3. Delgado-Algarra, E. J. (2022). Gamification and game-based learning. Research Anthology on Developments in Gamification and Game-Based Learning, 932–956. https://doi.org/10.4018/978-1-6684-3710-0.ch043 4. Halder, S., &Saha, S. (2023). Games, gamification, and simulation in Education. The Routledge Handbook of Education Technology, 363–377. https://doi.org/10.4324/9781003293545-31 5. Hou, H. T. (2023). Game-based learning and gamification for Education. MDPI - Multidisciplinary Digital Publishing Institute. 6. Hwang, G. J., Wu, P. H., & Chen, C. C. (2012). An online game approach for improving students’ learning performance in web-based problem-solving activities. Computers & Education, 59(4), 1246-1256. 7. Johnson, L., Becker, S. A., Cummins, M., Estrada, V., Freeman, A., & Hall, C. (2016). NMC horizon report: 2016 higher education edition (pp. 1-50). The New Media Consortium. 8. Landers, R. N., Bauer, K. N., Callan, R. C., & Armstrong, M. B. (2015). Psychological theory and the gamification of learning. Gamification in education and business, 165-186. 9. Lee, J. J., & Hammer, J. 2011. Gamification in education: What, How, Why Bother?. Academic Exchange Quarterly, 15(2), 146. 10. Nadi-Ravandi, S., &Batooli, Z. (2022). Gamification in education: A scientometric, content and co-occurrence analysis of systematic review and meta-analysis articles. Education and Information Technologies, 27(7), 10207–10238. https://doi.org/10.1007/s10639-022-11048-x 11. Navarro C, G. (2021). Relationship between artificial intelligence and the engagement variable. Journal of Psychological Science and Research, 1(3). https://doi.org/10.53902/jpssr.2021.01.000515 12. Smith, T. J. Porayska-Pomsta, K., Alcorn, A. M., Avramides, K., Beale, S., Bernardini, S., Foster, M. E., ...& (2018). Blending human and artificial intelligence to support autistic children’s social communication skills. ACM Transactions on Computer-Human Interaction (TOCHI), 25(6), 1-35. 13. Toda, A., Cristea, A. I., &Isotani, S. (2023). Gamification for education. Gamification Design for Educational Contexts, 3–14. https://doi.org/10.1007/978-3-031-31949-5_1 14. You, C., & Park, A. (2023). A data-driven application for matching student traits with learning opportunities using artificial intelligence. Artificial Intelligence Advances. https://doi.org/10.5121/csit.2023.130714 15. Zhao, X., Ismail, I. S., &Narasuman, S. (2023). Measurement indicators of student engagement and investigation on student engagement in blended learning. Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022), 823–829. https://doi.org/10.2991/978-94-6463-040-4_125 16. Durga Bhavani, K., Ferni Ukrit, M. Design of inception with deep convolutional neural network based fall detection and classification model. Multimed Tools Appl (2023). https://doi.org/10.1007/s11042-023-16476-6 17. K. Durga Bhavani, Dr. Radhika N. (2020). K-Means Clustering using Nature-Inspired Optimization Algorithms-A Comparative Survey. International Journal of Advanced Science and Technology, 29(6s), 2466-2472. 18. K. D. Bhavani and M. F. Ukrit, "Human Fall Detection using Gaussian Mixture Model and Fall Motion Mixture Model," 2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2023, pp. 1814-1818, doi: 10.1109/ICIRCA57980.2023.10220913.