Unit 2 Activity 1 – Individual Critical Academic Reflection
When I first began exploring socio-emotional learning (SEL) through artificial intelligence (AI) in personalized learning environments, I imagined it would be primarily a supplementary tool. My assumption was that AI would enhance traditional training rather than drive transformative changes. However, my understanding evolved significantly after diving deeper into the nature of personalized learning and delivery technologies. As Anderson (2008) suggests, online learning requires a delicate balance between learner autonomy and structured guidance. In my exploration, I have found that AI algorithms in personalized learning environments like Udemy foster self-efficacy by adapting to each learner. This sense of efficacy helps students take ownership of their development, especially when developing socio-emotional skills. AI’s ability to analyze patterns in behavior and engagement provides a wealth of insights that traditional teaching methods often overlook. As Weller (2011) described in his pedagogy of abundance, access to vast resources and adaptive tools through this mass compilation of data can further reduce barriers and increase access to education.
While the adaptive nature of AI in learning environments presents many opportunities, I have come across concerns. One concern is the potential for algorithms to reinforce biases, as they rely on existing data that may not accurately represent all learners. Additionally, Floridi’s (2015) “Online Manifesto” warned of the hyperconnected era’s challenges, suggesting that over-reliance on data can depersonalize and oversimplify complex socio-emotional interactions. This raises questions about inclusivity, as the current systems may lack cultural sensitivity and understanding of diverse emotional expressions. Despite some drawbacks, I am interested in continuing to explore how AI-SEL integration may incorporate meaningful, problem-based activities that strengthen socio-emotional competencies through reflective practices and learner feedback. Overall, my exploration of socio-emotional learning through AI in personalized learning has deepened my understanding of its transformative potential. While challenges remain, theory-based instructional design and ethical frameworks may help ensure that AI in personalized learning enriches corporate training programs and supports comprehensive learner development.
References
Anderson, T. (2016). Chapter 3: Theories for Learning with Emerging Technologies. In Veletsianos, G. (Ed). Emergence and Innovation in Digital Learning: Foundations and Applications. Edmonton, AB: Athabasca University Press.
Floridi, L. (2015). The Online Manifesto: Being Human in a Hyperconnected Era. Springer Open
Weller, M. (2011). A pedagogy of abundance. Spanish Journal of Pedagogy, 249, 223–236.
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I really think the work of figuring out how to handle the biases inbuilt into AI systems will be the next big step before AI can make the kinds of inroads we’re talking about in lots of places, including SEL. While I have a number of reservations about AI (not surprising at this stage, I’m sure!), the potential for harm in the SEL space and its intersection with biases I think can’t be underconsidered. I am interested to see what your learning uncovers this term!
Thanks for your blog, Asha. I am intrigued by the topic of socio-emotional learning (SEL) and AI in personalized learning. Since learning more about SEL in LRNT 524, I’ve been focused on discovering best practices. You raised a valid concern about algorithms reinforcing biases. I also was reflecting on human teachers having their own biases. The topic is undoubtedly complex. You may be interested in reviewing SEL research from Shah (2023), where AI scenario-based learning helps students practice their skills. Both teacher and student AI prompts are suggested for SEL role-play, case study, and guided meditation (p. 179).
I eagerly anticipate your next SEL blog and the insights you’ll share!
Cheers,
~M
Reference
Shah, P. (2023). AI and the future of education: Teaching in the age of artificial intelligence. Jossey-Bass.
Thanks for sharing this resource, Marni! I will dive deeper into Shah’s (2023) book as it definitely has relevancy to my topic. He seems unpacks a lot of complexities regarding AI in the educational landscape, and I am looking forward to testing out the prompts provided to understand how verbiage changes based on SEL impact the efficacy of the AI output.
Hi, Asha. Admittedly, I haven’t been a heavy user of platforms like Coursera and Udemy so I’ll ask some basic questions here. I’m curious about your comment that AI algorithms can help foster a sense of self efficacy in a learner and support socio emotional learning. Could you give an example of what that looks like? When I think of socio-emotional learning, I think of scenarios where learners have the ability to apply skills like empathy and compassion in the company of others. I appreciate your critical reflection on how an over reliance on data in the context of socio-emotional learning is an imperfect solution to personalized learning. I am a big proponent of social constructivism in learning and that knowledge is created through experiences with other people. I wonder how this theory of learning aligns with future innovations in using machine learning and algorithms.
Thanks for your comments, Tracy!
To provide an example of how AI can help foster self efficacy, consider a platform like Duolingo. By providing tasks that are at the right level of challenge, the AI algorithms in this app help learners achieve small successes by slowly increasing difficulty as learners enhance their confidence in their abilities to learn and master new materials (Henry, 2024). Another example is of the GenAI tool in Udemy which is a powerful ecosystem that discovers, develops, and validates the critical and competitive skills needed by a learner to achieve business outcomes. This supports SEL as the AI can provide real-time feedback on how to meet skills based outcomes (Udemy Business, n.d.).
I share your view and interest in social constructivism, since my own personal learning experiences have often been most effective in social contexts. In my exploration though, I’ve found that AI can complement these experiences by facilitating discussions or providing feedback that prompts learners to reflect and engage more deeply (Shapiro, 2023). I know this doesn’t replace face-to-face interaction, but it can enrich it, especially in digital learning environments where direct interaction is usually limited. I think the key is to ensure that these technologies are used to support and amplify human interactions, rather than replace them. As we move forward, I think it will be crucial to keep these considerations in mind to ensure that AI serves as a tool for facilitating deeper, more meaningful learning experiences.
References:
Henry, P. (2024, May 22). How Duolingo uses AI to create lessons faster. Duolingo Blog. https://blog.duolingo.com/large-language-model-duolingo-lessons/
Shapiro, S. (2023). Exploring the impact of generative AI on education: opportunities, challenges, and ethical considerations [University of Lethbridge]. In University of Lethbridge. https://www.ulethbridge.ca/teachingcentre/exploring-impact-generative-ai-education-opportunities-challenges-and-ethical
Udemy Business. (n.d.). GenAI is changing the game. Udemy. https://business.udemy.com/learn-more-gen-ai/?utm_source=direct&utm_medium=direct