Artificial Intelligence (AI) has emerged as a promising tool in the field of education, particularly in personalized learning which is why as a group we have chosen this as our topic of interest. Some of the learning events we have chosen to engage in include a Udemy course titled “ AI for Teachers and Educators” and a Coursera course titled “Innovative Teaching with ChatGPT.” It has been quite an informative journey so far and I intend to delve deeper into AI implementation, by looking at current challenges of using AI in personalized learning as it is evident that several challenges hinder its effectiveness. In this course I aim to explore these challenges, their implications, and the importance of understanding them for charting future directions in AI-driven personalized learning.
In my line of work one of the primary challenges with AI in personalized learning lies in the algorithmic biases inherent in the system. As AI models are trained on historical data, they often reflect the biases present in that data, perpetuating inequality and marginalization (Dwivedi et al.,p.6, 2021). Another challenge is the limited understanding of how AI affects the dynamics of teaching and learning. While AI promises tailored learning experiences, its implementation may lead to depersonalization and disengagement if not carefully designed (Su et al., p.2, 2021). Furthermore, there are concerns about the over-reliance on AI systems, potentially diminishing active learning (Roy & Paul, p.751,2023 ).
In order to plan for future AI implementation, I think its important to grasp the challenges of AI in personalized learning because if we don’t know better, we can’t do better. Understanding these hurdles is pivotal for creating equitable and effective educational experiences.
In your line of work ,what are the prevalent challenges in employing AI for personalized learning? Have you been able to find ways to mitigate these challenges ?
References:
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., . . . Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Roy, S., & Paul, S. K. (2023). Revolutionizing Education: How Artificial Intelligence is transforming the Learning Landscape.
Su, C., Ying, F., Shi, G., Sabatini, J., Greenberg, D., Frijters, J. C., & Graesser, A. C. (2021). Automated disengagement tracking within an intelligent tutoring system. Frontiers in Artificial Intelligence, 3. https://doi.org/10.3389/frai.2020.595627
These are such key questions, Ano, and I’m eager to see you taking this thinking further. I think when we consider hurdles in a training context, we need to think about things like: who is the imagined learner for this technology, and who is left out of that framework? This tacks into a lot of the issues you’re describing: if you are not the imagined learner, you may well feel alienated from the experience or depersonalized. Of course, this connects to bias issues, etc. Looking forward to hearing more!