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.
Dr. Min Kyu Kim Joins AERJ Editorial Board
October 28, 2024
We are delighted to announce that Dr. Min Kyu Kim has been appointed to the Editorial Board of the American Educational Research Journal (AERJ), a leading publication in the field of education. Congratulations to Dr. Kim!
.. Read MoreDr. Min Kyu Kim Represents ALOE at Summit for AI Institutes Leadership (SAIL) in Pittsburgh.
October 10, 2024
From October 7 to October 10, Dr. Min Kyu Kim, attended the Summit for AI Institutes Leadership in Pittsburgh, Pennsylvania (SAIL 2024). The event brought together representatives from 27 AI institutes funded by the National Science Foundation to discuss advancements in various fields, including food security, public safety, education, and weather forecasting.
.. Read MoreAI-ALOE Mini-Retreat: We presented SMART Research in Year 4
October 4, 2024
On October 2, 2024, our graduate associates, Jinho Kim, Seora Kim, Yoojin Bae, along with Dr. Min Kyu Kim attended AI-ALOE Mini-Retreat. Yoojin Bae and Seora Kim presented “SMART Research for Year 4,” focusing on technology integration in adult online education. Discussions centered on four key areas: educational goals for adult learners, instructional design collaboration, grounding in learning theories, and research contributions to adult education.
.. Read MoreNSF 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.
Haddadian, G., Radmanesh, S., & Haddadian, N. (2024). Construction and validation of a Computerized Formative Assessment Literacy (CFAL) questionnaire for language teachers: An exploratory sequential mixed-methods investigation. Language Testing in Asia, 14(33). https://doi.org/10.1186/s40468-024-00303-2
Kim, M. K., Kim, J., & Heidari, A. (2024). Exploring the multi-dimensional human mind: Model-based and text-based approaches. Assessing Writing, 61, 100878. https://doi.org/10.1016/j.asw.2024.100878
Haddadian, G. & Haddadian, N. (2024). Innovative use of grammarly feedback for improving EFL learners’ speaking: Learners’ perceptions and transformative engagement experiences in focus. The Journal of Applied Instructional Design, 13(2).