AI2 Research Laboratory

AI2 stands for Artificial intelligence (A), Interactive (I), Augmented (A), and Immersive (I) learning environments. AI2 represents the innovative learning environments we pursue to advance more adaptable, engaged, equitable, and effective teaching and learning in various educational contexts. We build on the legacy of our understanding of how people learn to answer the question, how we can scaffold people to learn better. Our endeavor to promote AI2 learning is driven by our belief that most learners can achieve learning goals if provided with appropriate instructional support.

News@AI2 RL

Publication in the Journal of Korea Multimedia Society

Publication in the Journal of Korea Multimedia Society

January 27, 2023

Kim, J., Lee, M., Park, J., Kim, J., & Sohn, E. (2022). Effects of a Cognitive Flexibility Hypertext Learning Environment for University Software Education. Journal of Korea Multimedia Society, 25(12), 1698–1713.

Abstract
This paper analyzed the effects of a cognitive flexibility hypertext learning environment to improve computational thinking skills, and perceptions and attitudes towards software in university software education.

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Dr. Young Rok Kim joined the lab as a visiting scholar

Dr. Young Rok Kim joined the lab as a visiting scholar

January 19, 2023

We have a visiting scholar! Dr. Young Rok Kim joined our lab. He is an associate professor at the Department of Public Administration and Policy at Kangwon National University, one of the largest national universities in Korea. His studies cover education policy, especially distance education policies, based on his 12 years of work experience at Korean Educational Research and Information Systems. During his visit to GSU, he wants to conduct a comparative study on how the pandemic impacted educational technology policies in the United States and Korea.

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Senior Program Committee Member for 2023 ICLS  and Program Committee Member for CSCL

Senior Program Committee Member for 2023 ICLS and Program Committee Member for CSCL

January 19, 2023

Co-Director, Dr. Min Kyu Kim, serves as a Senior Program Committee Member for the Learning Sciences (ICLS) and program Committee Member for  Computer-Supported Collaborative Learning (CSCL).  

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Research Projects

NSF AI Institute: AI Institute for Adult Learning and Online Education (ALOE) (Grant/Award Number: 2112532), National Science Foundation.

NSF AI Institute: AI Institute for Adult Learning and Online Education (ALOE) (Grant/Award Number: 2112532), National Science Foundation.

The ALOE institute is led by the Georgia Research Alliance (GRA), headquartered at Georgia Tech. The interdisciplinary and cross-institutional effort unites experts in computer science, artificial intelligence (AI), cognitive science, learning science and education from two Non-Profit Organizations (GRA and IMI Global), three industry partners (IBM, Boeing and Wiley) and seven universities (Georgia Tech, Georgia State, Harvard, Arizona State, Drexel, University of North Carolina, and multiple colleges within the Technical College System of Georgia [TCSG]). The multinational company Accenture joins NSF as a funding partner of ALOE.

The 5-year NSF grant is to establish the NSF AI Institute for Adult Learning and Online Education (ALOE) that will develop new AI theories and techniques as well as new models of lifelong learning, and evaluate their effectiveness at Georgia Tech, Georgia State, multiple colleges within the Technical College System of Georgia (TCSG), as well as with corporate partners IBM, Boeing and Wiley. ALOE aims to integrate AI theories, models, and techniques into online adult learning to create more available, affordable, adaptable, and scalable learning experiences, which creates more effective and efficient teaching and learning.

Artificial Intelligence-Augmented Motivation Indicator (AIMI) System

Artificial Intelligence-Augmented Motivation Indicator (AIMI) System

AIMI is an AI-augmented system that detects learners’ real-time motivation levels. AIMI utilizes neural network algorithms that interpret student facial expressions to indicate students’ current emotions (i.e., anger, disgust, fear, happiness, sadness, surprise, and neutral) and motivation levels in real-time.

SMART (Student Mental Model Analyzer for Research and Teaching) System

SMART (Student Mental Model Analyzer for Research and Teaching) System

SMART is a formative assessment and feedback system that analyze students’ academic essays (e.g., summaries of a text) and provide feedback to help learners to build a solid knowledge structure of a complex problem situation or reading materials. SMART analyzes students’ mental models in three dimensions (surface, structure, and semantic).

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Publications

Kim, J., Lee, M., Park, J., Kim, J., & Sohn, E. (2022). Effects of a Cognitive Flexibility Hypertext Learning Environment for University Software Education. Journal of Korea Multimedia Society, 25(12), 1698–1713.

Lee, M., Kim, S., Choi, S. Y., & Kim, J. (2022). Does the International Baccalaureate Diploma Program (IBDP) contribute to Whole-Person Development? The Rise of the IBDP in Asia and its implications for education reform. In Centering Whole-Child Development in Global Education Reform (pp. 83–101). Routledge.

Kim, M., & Kim, N. (2022). AI-supported scaffolding for writing academic arguments. In C. Chinn, E. Tan, C. Chan, & Y. Kali (Eds.), Proceedings of the 16thInternational Conference of the Learning Sciences-ICLS2022 (pp. 1129-1132). Hiroshima, Japan: International Society of the Learning Sciences. https://www.dropbox.com/s/ws5sdcfi72aykj1/ICLS2022%20Proceedings.pdf?dl=0  

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