Adaptive AI Platforms for Individualized Learning and Counselling

Authors

  • Azad Ahmad Andrabi Assistant Professor, Department of Education, BGSB University Rajouri, Jammu &Kashmir, India
  • Nayyar Jabeen Assistant Professor, Department of Education, BGSB University Rajouri, Jammu &Kashmir, India

DOI:

https://doi.org/10.31305/rrijm.2023.v08.n09.019

Keywords:

Adaptive AI, Individualized Learning, Counselling, Personalized Education, Machine Learning

Abstract

The rapid advancement in artificial intelligence (AI) technologies has brought forth adaptive AI platforms capable of transforming educational and counseling landscapes. These platforms personalize experiences for users by analysing data patterns, preferences, and performance metrics. This paper explores the application, effectiveness, and challenges of adaptive AI platforms in individualized learning and counselling contexts in general and with reference to Indian scenario. It also discusses the benefits of adaptive AI platforms and their ethical and practical considerations for implementation.

References

Binns, R., Veale, M., Van Kleek, M., & Shadbolt, N. (2018). 'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1-14. https://doi.org/10.1145/3173574.3173951

Crawford, K., & Paglen, T. (2019). Excavating AI: The Politics of Images in Machine Learning Training Sets. The AI Now Institute. https://ainowinstitute.org/publication/excavating-ai

Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017). Delivering Cognitive Behavior Therapy to Young Adults With Symptoms of Depression and Anxiety Using a Fully Automated Conversational Agent (Woebot): A Randomized Controlled Trial. JMIR Mental Health, 4(2), e19. https://doi.org/10.2196/mental.7785

Holstein, K., Wortman Vaughan, J., Daumé III, H., Dudik, M., & Wallach, H. (2020). Improving Fairness in Machine Learning Systems: What Do Industry Practitioners Need? Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-16. https://doi.org/10.1145/3313831.3376440

Inkster, B., Sarda, S., & Subramanian, V. (2018). An Empathy-Driven, Conversational Artificial Intelligence Agent (Wysa) for Digital Mental Well-Being: Real-World Data Evaluation. JMIR mHealth and uHealth, 6(11), e12106. https://doi.org/10.2196/12106

KPMG & Google. (2017). Online Education in India: 2021. https://assets.kpmg/content/dam/kpmg/in/pdf/2017/05/Online-Education-in-India-2021.pdf

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson Education. https://www.pearson.com/content/dam/one-dot-com/one-dot-com/global/Files/about-pearson/innovation/open-ideas/Intelligence-Unleashed-Publication.pdf

Ministry of Education. (2020). National Education Policy 2020. Government of India. https://www.education.gov.in/sites/upload_files/mhrd/files/NEP_Final_English_0.pdf

NITI Aayog. (2018). National Strategy for Artificial Intelligence #AIForAll. Government of India. https://www.niti.gov.in/sites/default/files/2021-02/NationalStrategy-for-AI-Discussion-Paper.pdf

Pane, J. F., Steiner, E. D., Baird, M. D., & Hamilton, L. S. (2015). Continued Progress: Promising Evidence on Personalized Learning. RAND Corporation. https://www.rand.org/pubs/research_reports/RR1365.html

Walkington, C., & Bernacki, M. L. (2018). Personalization of Instruction: Design Principles and Impacts. Handbook of Learning Analytics, 190-200.

Xie, H., Chu, H. C., Hwang, G. J., & Wang, C. C. (2019). Trends and Development in Technology-Enhanced Adaptive/Personalized Learning: A Systematic Review of Journal Publications from 2007 to 2017. Computers & Education, 140, 103599. https://doi.org/10.1016/j.compedu.2019.103599

Downloads

Published

14-09-2023

How to Cite

Andrabi, A. A., & Jabeen, N. (2023). Adaptive AI Platforms for Individualized Learning and Counselling . RESEARCH REVIEW International Journal of Multidisciplinary, 8(9), 143–147. https://doi.org/10.31305/rrijm.2023.v08.n09.019