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Exploring the Potential of AI-Generated Videos for Learning

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Presenters

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PhD Student in Cognitive Science in Edu.
Columbia University
@limjsy
@lim.jsy
Jullia is a designer and researcher in education technology, specializing in the social domain of learning. The long-term goal of her research is to better understand human behaviors and cognitive processes to enhance technology designs. Her previous projects include an augmented reality (AR) simulation game for social skills and a virtual reality (VR) speech therapy for stutter patients. Currently, she is a PhD student in Cognitive Science at Columbia University, where she's investigating how generative AI contents influence the learning process in her doctoral research.

Session description

This session delves beyond the excitement of ChatGPT, and explores the potential of AI-generated videos and avatars to not only revolutionize teaching and learning in both physical and online classrooms, but its potential to bridge educational gaps, democratize access to quality education globally, and facilitate inclusive/efficient learning ecosystem.

Purpose & objective

The main purpose of this presentation is for me to share my findings from my research on AI-generated videos on learning, which have many practical implications for educators to practice in their physical and/or online classroom.

Amidst the recent wave of excitement surrounding artificial intelligence (AI), it's undeniable that the realm of education has been overflowing with discussions about the potential of AI to transform teaching and learning. And at the forefront of these conversations have been advancements like Chat GPT and AI tutors, which have garnered substantial attention for their capabilities in aiding educational processes. However, there are many more unexplored ways AI can enhance student learning in the physical classroom and/or online classroom. This presentation aims to unravel a diverse array of applications of AI that extend far beyond the commonly discussed chatbots and tutoring systems, such as AI-generated videos and AI-avatars, as well as suggest ways AI can continue to support learning, especially to advance learning that meets the diverse learning, cultural, and social-emotional needs of individual students.

Participants will learn about the cognitive processes that happen in learning to gain a deeper understanding of the learning sciences, and will also learn how different methods of using AI can support their teaching practice and student learning. They will not only walk away with a list of AI tools they can use right away, but also with an understanding of how I (cognitive scientist) hypothesize AI can really empower learning and its potential to bridge educational gaps, democratize access to quality education globally, and facilitate a more inclusive and efficient learning ecosystem.

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Outline

1) 5 min Introduction
- Introduction of AI tools commonly used in the classroom today

2) 5 min discussion on AI Avatars:
- how I used to use avatars in AR and VR apps I made in the past for students with autism, or adult stutter patients.
- the theory on how avatars help learning (social agency theory, social presence theory etc.)
- how much AI technology has advanced, how hyper-realistic avatars look today
- how avatars are helping in supporting learning for students with autism
- the potential I see in AI avatars to transform learning for students with autism

3) 5 min discussion on AI-generated videos
- how easy it is to make an AI-generated video
- how teachers can use AI-generated videos in their classroom
- how students can make AI-generated videos for their learning or even for assessment

4) 15 min discussion on my research
- how I am currently investigating AI avatars, and AI-generated videos in my doctoral research
- my findings and future opportunities (potential)

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Supporting research

Atkinson, R. K. (2002). Optimizing learning from examples using animated pedagogical agents. Journal of Educational Psychology, 94(2), 416–427. https://doi.org/10.1037/0022-0663.94.2.416

Leiker, D., Gyllen, A. R., Eldesouky, I., & Cukurova, M. (2023b). Generative AI for learning: Investigating the potential of learning videos with Synthetic Virtual Instructors. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky, 523–529. https://doi.org/10.1007/978-3-031-36336-8_81

Pataranutaporn, P., Danry, V., Leong, J., Punpongsanon, P., Novy, D., Maes, P., & Sra, M. (2021). Ai-generated characters for supporting personalized learning and well-being. Nature Machine Intelligence, 3(12), 1013–1022. https://doi.org/10.1038/s42256-021-00417-9

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Session specifications

Topic:
Artificial Intelligence
Skill level:
Beginner
Audience:
Chief technology officers/superintendents/school board members, Teachers, Teacher education/higher ed faculty
Attendee devices:
Devices useful
Attendee device specification:
Laptop: Mac
ISTE Standards:
For Education Leaders:
Empowering Leader
  • Empower educators to exercise professional agency, build teacher leadership skills and pursue personalized professional learning.
For Educators:
Learner
  • Stay current with research that supports improved student learning outcomes, including findings from the learning sciences.