Dr. Kim delivered an invited talk at Inha University in Incheon, South Korea.

May 22, 2026

Dr. Kim was invited to a workshop series on instructional innovations offered by Inha University in Incheon, South Korea. The workshop was held via Zoom with over two hundred faculty and staff members from the university. This workshop introduced cases of AI-augmented instruction applied to higher education and adult learning. In particular, it presented educational programs and a range of application cases developed by the NSF AI Institute for Adult Learning and Online Education (AI-ALOE). The workshop also featured live demos of systems currently under development that integrate generative AI and knowledge-based AI to support hybrid instruction and simulation-based learning, along with a discussion of how these systems can be applied and scaled in real classrooms.  

Key Topics

• Introduction to AI-powered educational programs and application case studies
• A multimodal instructional platform for supporting hybrid learning
• An AI-augmented simulation platform and its application cases

Our lab members presented their research during the AI ALOE EAB meeting.

May 15, 2026

AI-ALOE held its final EAB meeting on May 15, 2026, which aimed to update the Advisory Board on the institute's accomplishments and products, showcase findings from various ALOE teams, foster networking, highlight student research, and gather insights for the NSF Annual Report and Review Meeting. The meeting was attended by our director, Dr. Kim, alongside graduate associates Ahnaf, Hyunkyu, Jinho, Seora, and Yoojin, as well as recent graduate Dr. Haddadian. Dr. Kim served as chair for the "Theories of Learning" session, where Jinho and Yoojin delivered three-minute talks on theories of learning and personalization in learning, respectively. Additionally, Ahnaf, Hyunkyu, and Seora presented posters during the lunch break.

As session chair, Dr. Kim delivered the EAB presentation "Theories of Learning," which traced how the AI-ALOE project has built and refined a theoretical foundation for one central question: how can we enhance the proficiency of adult online education across both well-structured and ill-structured learning tasks?

Jinho's talk, "Theories of Learning: Whole-Person Perspective," argued that designing equitable AI learning tools requires looking beyond standard cognitive metrics to account for a student's complete identity and life circumstances.

Yoojin's presentation, "Personalization: Five Years of SMART," explored how personalized AI feedback from the SMART agent influences student engagement during writing-based concept learning.

Seora's poster, "Design Principles for AI-Supported Chatbots to Scaffold Problem-Based Learning in Undergraduate Nursing Education," proposed a framework for developing AI chatbots tailored for nursing students.

Hyunkyu's poster presentation, "How Do Students Differ in Writing and Revision?," framed summarization as a critical learning strategy in undergraduate STEM that is often hindered by a lack of timely feedback.

Ahnaf's poster, "The Digital Chameleon: Why AI Undetectability in Writing Is a Problem for Effective Learning," explored how the rise of generative AI challenges academic integrity and trust in higher education by testing the reliability of AI-text detection tools.

Lab members attended an ALOE virtual retreat

April 2, 2026

Dr. Kim was invited to deliver one of the five AI-ALOE theme presentations during the fifth-year ALOE retreat on April 2, 2026. The presentation offered a synthesis of the project's work on theories of learning, tracing how AI-ALOE has built and refined a theoretical foundation for AI-supported adult learning over the course of the initiative. Our graduate research associates, Jinho, Yoojin, and Seora, also attended the virtual meeting.

Dr. Kim presented a talk for the NSF AI ALOE Virtual Discussions

March 16, 2026

This presentation, entitled "Contributions to Theories of Learning: Discussions on Open-Ended Problems," examines contributions to theories of learning through the lens of the SMART platform, with a particular focus on open-ended problems. It is organized around four theoretical dimensions: adult learning, which emphasizes building mental models through diverse formative supports and self-directed, personalized learning environments; cognition and knowledge, which integrates the ICAP framework (Passive, Active, Constructive, Interactive) with the Community of Inquiry model to guide instructional design decisions; personality and temperament, which draws on Self-Determination Theory, Pekrun's Control-Value Theory, and the concept of cognitive engagement to explore how motivation drives effort, persistence, and achievement; and contextual/learner background, which investigates how demographic factors such as race and first-generation status interact with engagement and performance patterns over time. Across these dimensions, the presentation connects SMART's multimodal feedback, flexible navigation, and data visualization features to measurable learning behaviors—particularly writing, revision, and review activities—offering both a theoretical grounding and empirical evidence for understanding how AI-integrated instruction can support diverse learners.