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.
NSF-SaTC-Private AI Project: Field Test in February 2023.
February 28, 2023
From February 9th to February 23rd, we conducted a field test to implement the Private AI curriculum in an undergraduate CS classroom. This endeavor involved implementing two modules out of a total of ten, with the following topics:
Dr. Min Kyu Kim Presented the Year 1 Research at the AI-ALOE Retreat
February 09, 2023
Co-Director, Dr. Min Kyu Kim, presented the year 1 research outcomes at the AI-ALOE retreat held in the Technology Square Research Building (TSRB), Rooms 133 &134, at GaTech, from Thursday, Feb. 9, and Friday, Feb. 10, 2023... Read More
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.
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.
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
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 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).
Bae, Y., Kim, J., & Kim, M. (accepted). Clustering cognitive engagement changes in a longitudinal traced discussion data from an online course. Proceedings of the 17th International Conference of the Learning Sciences/Computer-Supported Collaborative Learning (ICLS/CSCL-2023). Montréal, Canada: International Society of the Learning Sciences.
Kim, J., Haddadian, G., & Kim, M. (accepted). An investigation of knowledge-based AI vs. human evaluation in academic summary evaluation: Similarities, dissimilarities, and being toward mutual understandings. Proceedings of the 17th International Conference of the Learning Sciences/Computer-Supported Collaborative Learning (ICLS/CSCL-2023). Montréal, Canada: International Society of the Learning Sciences.
Kim, M., Kim, N., Haddadian, G., & Heidari, A. (accepted). A test of learning progress models using an AI-enabled knowledge representation system. Proceedings of the 17th International Conference of the Learning Sciences/Computer-Supported Collaborative Learning (ICLS/CSCL-2023). Montréal, Canada: International Society of the Learning Sciences.