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.
August 17, 2023
We are delighted to share the recent recognition of our exceptional lab members in the AI-ALOE Summer Newsletter! Our lab director, Dr. Min Kyu Kim, has been prominently featured in the Team Member Splotlight for his work with SMART. Furthermore, we celebrate the achivements of our graduate associate, Jinho, in the Student Highlights section.
.. Read MoreCongratulations! The director, Dr. Min Kyu Kim, has been awarded a new NSF IUSE grant.
August 4, 2023
We have great news! The director, Dr. Min Ky Kim, has received the new NSF IUSE grant entitled 'Artificial Intelligence-Scaffolded Pre-Classroom Learning for Large, Introductory Undergraduate Physics Courses.' Dr. M. Shameer Abdeen from the Department of Physics & Astronomy at Georgia State University is the Co-PI of the grant project. See the information below.
NSF: Improving Undergraduate STEM Education (Grant/Award Number: 2315709)
Dr. Young Ju Jeong has joined our lab as a visiting scholar.
August 4, 2023
Dr. Young Ju Jeong has joined our lab as a visiting scholar. Dr. Jeong is an associate professor in the software department at Sookmyung Women's University, Seoul, Korea. During her visit, she will work with us to conduct research and development to integrate AI techniques with AR/VR learning environments.
.. Read More
NSF IUSE-Engaged Student Learning (Level 1): AI-Scaffolded Pre-Classroom Learning for Large/Introductory Undergraduate Physics Courses
This Engaged Student Learning Level 1 project aims to serve the national interest by designing and implementing an Artificial Intelligence (AI)-augmented formative assessment and feedback system. This system will help students develop source-based STEM arguments, such as STEM text summarization, or problem spaces, which are mental representations of a problem and of multiple paths to solving it. This will be implemented in large, undergraduate introductory physics courses at an urban university that serves diverse and historically underrepresented student groups. Persistent learner engagement in pre-classroom learning activities is critical to learner success in introductory STEM courses. The innovation of the project will include AI-generated adaptive scaffolding information and learning progress feedback with data visualization techniques to help students with concept learning and self-regulatory behaviors. The unique learning opportunities supported by an AI-scaffolded feedback system will significantly increase students' engagement levels in self-paced online pre-classroom learning. This, in turn, will help students acquire content knowledge and build a proper understanding of problems to prepare themselves for success in in-classroom interactive problem-solving activities.
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.
Bae, Y., Kim, J., & Kim, M. (in press). 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. (in press). 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. (in press). 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.