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.
Dr. Kim presented at the Capitol.
February 19, 2026
Dr. Kim and researchers from the Byrdine F. Lewis College of Nursing and Health Professions showcased an AI simulation project as part of Georgia State University’s Research Day at the Capitol.
Our lab members provided a pre-conference workshop for SNRS.
February 18, 2026
Associate Professor Min Kyu Kim, doctoral students Jinho Kim and Seora Kim and faculty from the Byrdine F. Lewis College of Nursing and Health Professions presented at the Southern Nursing Research Society Annual Conference pre-conference workshop entitled “Optimization of AI Integration for Nursing Education and Research" at the Southern Nursing Research Society Annual Conference.
Dr. Kim presented a talk for the NSF AI ALOE Virtual Discussions
February 09, 2026
This presentation, titled "Instructional Design in Practice: Case Studies," details a multi-layered approach to studying and advancing AI-driven instructional design in practice. Building on the same overarching case-study framework introduced in the AI-ALOE project, it moves from task conceptualization and case narrative collection through a refined instructional design space analysis—mapping cases along dimensions such as learning mode, structure, participation, task scope, and design format—and then applies the PICRAT model to evaluate how AI technology integration affects both student engagement and teaching practice. The presentation goes further by showcasing concrete case examples (including engineering and instructional design courses), reviewing cross-case findings, and proposing a forward-looking vision called "AIM HIGH" (AI-Powered Multimodal Instruction for Growth), which envisions enhanced human–AI interaction through personalized feedback, multi-agent support, advanced hybrid learning environments, and generative AI–driven simulation-based training in fields such as nursing education.
