MAD | AI 2020: Applications of AI in Game-Based Learning: Creating Adaptive Learning Experiences.

Lloyd Donelan | LIVE LAB @ Texas A&M University
Brenton Lenzen | LIVE LAB @ Texas A&M University

AI is found in many entertainment and edutainment games alike, often non-responsive to user actions which fall beyond the scope of actions anticipated by the game’s designers. In the context of game-based learning (GBL), this means that any “intelligent” agent or system within the game can never truly provide a learning experience tailored to a particular student. What if modern advances in AI were used to create truly intelligent agents and game systems, which could adapt to every learners’ needs? Adaptive Hypermedia (AH) and Intelligent Tutoring Systems (ITS) could be used to present/teach new information, and then provide additional assistance to the learner in a context-sensitive manner. In this talk, the speakers discuss the concepts behind GBL which make AH and ITS ideal solutions to this problem. Existing research in intelligent GBL will be discussed – most notably Lester et. al.’s Crystal Island, a game which models and reacts to student knowledge using a dynamic bayesian network (Lester 2013), and Bermudez et. al.’s proposed “knowledge discovery framework” for an open-world educational game (Bermudez et. al. 2019).