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

AI2 lab members attended the AI ALOE's Year 2 Executive Advisory Board Meeting

AI2 lab members attended the AI ALOE's Year 2 Executive Advisory Board Meeting

May 19, 2023

Director Dr. Min Kyu Kim and the graduate associates from the AI2 lab, Jinho Kim, Lia Haddadian, and Yoojin Bae, attended the AI ALOE's Year 2 Executive Advisory Board Meeting on May 19, 2023. Approximately 40 members, including 7 EAB members, participated in the meeting either in person or online.

.. Read More

NSF AI ALOE Institute Research Videos Now Available

NSF AI ALOE Institute Research Videos Now Available

May 4, 2023

We have created two video presentations for public access. The videos introduce our AI research and development, centering on two topics: Concept Learning and Personalization. We define concept learning as the cognitive process of building a solid understanding of STEM content necessary for developing critical thinking and problem-solving skills. Personalization is one of the goals pursued in AI in education that enables learners to be better engaged in and regulate their learning and performance. Additionally, personalized support for instructors can empower them to support learners in more adaptive and appropriate ways. Our three graduate associates, Jinho, Lia, and Yoojin, have served as narrators. Enjoy!

.. Read More

Attending and Presenting at the 2023 AERA Annual Meeting

Attending and Presenting at the 2023 AERA Annual Meeting

April 13, 2023

Members of our AI2 Lab attended and presented at the 2023 American Educational Research Association (AERA) Annual Meeting, which took place from April 13-16 at Chicago, IL.

Dr. Min Kyu Kim and our graduate associate, Jinho Kim, presented the paper titled "Using Machine Learning for Cognitive Presence Detection in Asynchronous Online Learning" at the Instructional Technology SIG Roundtables on the 13th.

.. Read More

See more >

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).

See more >

Publications

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.

See more >