"Our Mission is to Build on Theories of Learning and Instruction to Create Innovative Learning Environments that Maximize Learner Capacity to Achieve Learning Goals"

To achieve our mission, the AI2 Research Laboratory builds an interdisciplinary and cross-institutional effort that unites experts in learning sciences, computer sciences, STEM educators, and literacy researchers from multiple institutions. We pursue answers to two critical questions in education: (a) how can we personalize and advance learning experiences supported by emerging technologies such as AI and augmented reality? and (b) how can we design highly accessible learner experiences using learning technologies that deepen learner engagement?

Specifically, we have focused on four aspects of learning technologies

AI-Supported Learning

We have deployed advanced AI techniques–for example, affective computing and Natural Language Processing (NLP) AI– to develop automated formative assessment and feedback technologies for learner cognition, motivation, and emotions.

Interactive Learning

Human-Computer Interaction is not just about learner-to-computer interaction. Technology can enable learners to be more interactive with peers and instructors in technology-based learning environments.

Augmented Learning

Teaching and learning effectiveness can be augmented by learning technologies appropriately integrated with the optimal pedagogy in a context. We focus on the affordances of new technologies to track and diagnose the patterns of learner performance and provide multi-dimensional scaffolds catered to individuals’ needs.

Immersive Learning

Problem-centered learning requires effective problem-posing strategies that engage learners in a real-world problem situation. Given a problem context, learners play a pivotal role in solving the problem. We utilize mixed-reality and augmented-reality techniques to build immersive learning in real-world scenarios.

IMPACTS & TRANSFORMATIONS

Our effort centering on AI2 aims to improve education practices in regard to adaptability, engagement, equitability, and effectiveness.

Adaptability

AI2 learning environments help provide personalized learning that reacts to learners’ individual differences in beliefs and knowledge as well behaviors and affects. A smarter technology can diagnose and provides individualized, formative guidance as learners practice more open-ended and complex skills such as solving complex STEM problems or writing discipline-specific academic essays.

Engagement

Sustaining or improving learner engagement in ill-defined and complex tasks is challenging. The demanding problems or collaborative leaning tasks can create emotional turmoil and decrease morale, resulting in the early loss of interest. We create technologies that track and support multidimensional learner engagement (i.e., cognitive, behavioral, and emotional engagement) in interactive learning environments.

Equitability

AI2 learning environments create more diverse, equitable, and inclusive learning experiences by providing technology-enhanced scaffolding adaptive to individual students’ cognition, metacognition, and motivation. Technology can work as a learning agent that helps learners connect their backgrounds, current knowledge, skill, and beliefs to the new problem situation.

Effectiveness

AI2 learning environments make teaching effective by informing instructors of the patterns of individuals or groups of learners and suggesting appropriate instructional remedies. Also, AI2 learning environments enable learners to engage in interactive and immersive learning activities and to regulate their cognition, behaviors, emotions, and motivation as they progress toward learning goals. Technology plays an essential role in helping learners to experience meaningful learning.

We are an interdisciplinary collaborative team from multiple institutions.
Please join us through the Contact Us

Researchers at the AI2 RL
Min Kyu Kim, Ph.D.

Min Kyu Kim, Ph.D. 

Min Kyu Kim is an Associate Professor of Learning Sciences at Georgia State University. Kim is the founding director of the AI2 Research Laboratory. His research pursues innovative research that advances our understanding of how people learn and how to assess and foster transformative learning, especially in technology-rich learning environments. Specifically, he has focused on three major areas of research: (a) adaptive learning informed by learning progression models, (b) descriptive and predictive models of how people learn individually or in a group in CSCL environments, and (c) creative and innovative design solutions to advance technology-enhanced learning experience. For example, he is committed to ing new models of learning progression and computational models to collect, externally represent and diagnose learner characteristics such as cognition, learning emotion, and social interaction in emerging learning technologies. Also, he has developed adaptive learning technologies called Student Mental Model Analyzer for Research and Teaching (SMART) and the Artificial Intelligence-Enabled Scaffolding System (AISS) to support students' academic writing.

Taehee Lee

Taehee Lee 

Mr. Taehee Lee has joined our lab as a visiting scholar. He earned a B.S. degree in electrical engineering from Korea University, Seoul, Korea, in 2004, and an M.S. degree in electrical engineering from the University of Southern California, Los Angeles, United States, in 2006. He is currently pursuing his Ph.D. degree in computer education from Sungkyunkwan University, Seoul, Korea. Additionally, he holds a senior engineer position at Korea Telecom in Seoul, South Korea. Prior to joining KT, he worked as a junior engineer at Samsung Advanced Institute of Technology. His areas of expertise include computer vision and specialized person attribute recognition in artificial intelligence, industrial/vertical deep learning applications, unstructured data analysis, and AI-based education platforms.

Young Ju Jeong

Young Ju Jeong 

Dr. Young Ju Jeong has joined our lab as a visiting scholar. Dr. Jeong received her Ph.D. in computer science and electrical engineering from the University of Southern California, Los Angeles, USA. She is currently an associate professor in the software department at Sookmyung Women's University, Seoul, Korea. Before joining Sookmyung, she worked as a Research Member at Samsung Advanced Institute of Technology, Suwon, South Korea. Her research interests include Augmented Reality and Virtual Reality content rendering and display design. During her visit, she will lead the research and development efforts to integrate AI techniques with AR/VR learning environments.

Research Partners
Daniel Takabi, Ph.D.

Daniel Takabi, Ph.D. 

Daniel Takabi is the director of the School of Cybersecurity at Old Dominion University, as well as the Batten Endowed Chair of Cybersecurity and professor of electrical and computer engineering. His work is to increase the research capacity of the School of Cybersecurity and build on the growth of the undergraduate and graduate cybersecurity programs.

Hongli Li, Ph.D.

Hongli Li, Ph.D. 

Hongli Li, Ph.D., is an associate professor of Research, Measurement & Statistics in the Department of Educational Policy Studies at Georgia State University. She graduated from the Pennsylvania State University with a Ph.D. in educational measurement in 2011. Her major areas of research are quantitative methods and applied measurement in education. At Georgia State University, she teaches a number of courses, such as structural equation modeling, item response theory, meta-analysis, educational measurement, classroom assessment, research methods in education. Her research has been supported by the Spencer Foundation, Educational Testing Service, among other sources. She has published in many refereed journals, and her publications can be viewed here: https://scholar.google.com/citations?user=jfQii-oAAAAJ&hl=en

Kathryn Soo McCarthy, Ph.D.

Kathryn Soo McCarthy, Ph.D. 

Dr. McCarthy is an Assistant Professor of Educational Psychology in the Department of Learning Sciences at Georgia State University and the director of the Disciplinary Comprehension Lab. Her research examines how reading and writing processes vary across disciplines and across readers. She is interested in how AI can be used to study and support these processes through educational technologies.

Nam Ju Kim, Ph.D.

Nam Ju Kim, Ph.D. 

Nam Ju Kim is an associate professor in the education department at Yonsei University, Seoul, Korea.He has been active in a wide range of technology-related learning initiatives including educational games, robots, artificial intelligence, spatial tools, and adaptive online learner-centered instructional models where cutting-edge technology can be embedded. His research has been supported by internal grants, foundations, industries, and federal agencies. His recent research focuses on a) investigating the effectiveness of the online learning platform for English learning through big data and machine learning algorithms and b) demonstrating the concept of adopting the Artificial Intelligence-based learning support systems he has developed to the Learning Management System.

Sua Im

Sua Im 

Sua Im has joined our lab as a visiting scholar through the Outstanding Graduate Students’ Overseas Training Program (BK21 FOUR Project) sponsored by The National Research Foundation of Korea. She earned a bachelor’s degree in French language and literature, and bachelor’s and master’s degrees in sports industry from Yonsei University, South Korea. She is currently advancing her PhD studies at Yonsei. Her research focuses on various aspects of sports, serious leisure, and enhancing quality of life. Currently, she is exploring the intersection of AI-based programs and well-being among older adults within senior centers.

Yinying Wang, Ph.D.

Yinying Wang, Ph.D. 

Yinying Wang is an associate professor of educational leadership in Educational Policy Studies at Georgia State University. Her research interest intersects technology, decision making, neuroscience and social network analysis in educational leadership and policy. She is also an associate faculty member in the Neuroscience Institute at Georgia State University.

Graduate Research Associates
Akshit Calonia

Akshit Calonia 

Akshit is an honors college student pursuing a major in Computer Science at Georgia State University. He is currently undertaking an internship in the lab, focusing on harnessing the power of AI to develop smarter and more innovative applications.

Crystal Budrage – Doctoral Student

Crystal Budrage – Doctoral Student 

Crystal Bundrage is a Ph.D. student in the College of Education and Human Development at Georgia State University. She received her master’s degree in Business Administration from the University of South Florida, and her bachelor’s degree in Business Administration from Stetson University. She has spent over a decade supporting technology-enhanced instruction and online learning through the development and facilitation of workshops and professional development courses in the higher education setting. Her research focuses on the various instructional approaches and practices used in a blended synchronous learning environment.

Golnoush Haddadian – Doctoral Student

Golnoush Haddadian – Doctoral Student 

Golnoush Haddadian is a Graduate Research Associate and a Ph.D. student at College of Education and Human Development, Georgia State University (GSU). She has received her master’s degree in Applied Linguistics (TEFL) from Sharif University of Technology. Using IRT as its psychometric framework, she developed a Computerized Adaptive Test of Written Receptive Vocabulary (CATWRV); a desktop-based software to test English vocabulary knowledge of foreign language learners. As a researcher, she is fervently interested in inviting technology to understand how people learn and help them learn more effectively. Her main areas of research include investigating adaptive technologies to improve learning and designing innovative technological solutions to facilitate learning.

HyunKyu Han – Doctoral Student

HyunKyu Han – Doctoral Student 

HyunKyu joined our lab in Spring 2024. She earned a Master's in Educational Technology from Yonsei University, South Korea and an undergrad in Elementary Education from Gongju National University of Education. Currently, she is an elementary school teacher in South Korea. Her research interests involve leveraging AI to create personalized learning environments that cater to the needs of learners and implementing AI-augmented active learning strategies.

Jinash Rouniyar

Jinash Rouniyar 

Jinash is an honors college undergraduate student pursuing a major in Computer Science at GSU. He is actively engaged in various lab projects, leveraging his experience as a front-end developer at NSTEM and his proficiency in Java/Python programming languages.

Jinho Kim – Doctoral Student

Jinho Kim – Doctoral Student 

Jinho Kim is a Graduate Research Associate and a Ph.D. student at the Department of Learning Sciences in the College of Education and Human Development, Georgia State University (GSU). She earned her Bachelor of Arts (B.A.) in Education, Bachelor of Science in Engineering (B.S.E.) in Computer Science and Engineering, and Master of Arts (M.A.) in Education from Yonsei University, South Korea. Her research interests include educational technology, online learning environments, computer and software education, and artificial intelligence-assisted learning.

YooJin Bae – Doctoral Student

YooJin Bae – Doctoral Student 

Yoojin is a Graduate Research Associate and a Ph.D. student at the Department of Learning Sciences in the College of Education and Human Development, Georgia State University (GSU). She earned her master’s degree in Education from Seoul National University, South Korea. Her research interests lie in the intersection of Education and Computer Science. Her work’s focus is on examining ways to leverage artificial intelligence in order to offer adaptive learning environment. Yoojin is exploring natural language processing to analyze text data in educational circumstances.

Alumni
Akshat Namdeo

Akshat Namdeo 

Akshat is an honors college undergraduate student in the Department of Computer Science at Georgia State University. He previously served as a UAP intern, contributing to lab projects.

Ali Heidari, Ph.D.

Ali Heidari, Ph.D. 

Ali, a former graduate associate in the lab, received his Ph.D. in Learning Sciences from the College of Education and Human Development at Georgia State University (GSU) in spring 2024. He also holds a master's degree in Applied Linguistics from the Department of Applied Linguistics at GSU. Ali's research focuses on learner experience (LX) during feedback information processing within technology-enabled formative feedback systems, leveraging various natural language processing tools and combining computational and behavioral experimental methods.

Ethan Lim

Ethan Lim 

Ethan is an undergraduate student pursuing a major in Computer Science at GSU. He previously served as an intern, contributing to lab projects.

Jeshal Patel

Jeshal Patel 

Jeshal is an honors college undergraduate student pursuing a major in Computer Science at GSU. He was interning at the lab, driven by his keen interest in integrating technology and AI into various aspects of educational problem-solving.

Liping Yang, Ph.D.

Liping Yang, Ph.D. 

Liping Yang earned her Ph.D. in STEM education at the University of Miami. Her research interests include the use of cutting-edge technology such as augmented reality, virtual reality, augmented reality, mixed reality, robots, game-based learning, and artificial intelligence in a variety of learning contexts to increase students' engagement and outcomes.

Murat Kasli, Ph.D.

Murat Kasli, Ph.D. 

Murat Kasli was a former graduate associate. He earned his Ph.D. from the Research, Measurement, and Evaluation Department at the University of Miami. During his time in the lab, he assisted in research projects focusing on the analysis of cognitive diagnostic models.

Shanshan Wen

Shanshan Wen 

Shanshan, an undergraduate student in the Department of Computer Science at Georgia State University, served as our undergraduate intern. She possesses a keen interest in Artificial Intelligence and full-stack development, with a strong desire to leverage these skills to enhance the online learning experience.

Shyama Bhuvanendran Sheela, M.S.

Shyama Bhuvanendran Sheela, M.S. 

Master of Science in Computer Science Computer Science, Georgia State University, December 2018 Shyama contributed to the SMART development in the following areas:

  • Natural language processing, social network analysis, data visualization
  • Web programming

Solanlly Rijo Lake

Solanlly Rijo Lake 

Solanlly Rijo Lake, an Honors college student majoring in Computer Science with a concentration in Cybersecurity at Georgia State University, served as our intern. Her passion for learning and improving education by leveraging learning technologies in her home country, the Dominican Republic, led her to volunteer in the lab.

Swathi Kiran Reddy Pallamreddy, M.S.

Swathi Kiran Reddy Pallamreddy, M.S. 

Master of Science in Computer Science Computer Science, Georgia State University, May 2018 Swathi worked on SMART project with the following major contributions:

  • System architecting and database design
  • Natural language processing, social network analysis, data visualization
  • Web programming

Young Rok Kim, Ph.D.

Young Rok Kim, Ph.D. 

Dr. Young Rok Kim was a visiting scholar. 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.