AIED Workshop on Authoring and Tutoring for Psychomotor, Mobile, and Medical Domains
We report our exploratory research of psychomotor task training in intelligent tutoring systems (ITSs) that are generally limited to tutoring in the desktop learning environment where the learner acquires cognitively oriented knowledge and skills. It is necessary to support computer-guided training in a psychomotor task domain that is beyond the desktop environment. In this study, we seek to extend the current capability of GIFT (Generalized Intelligent Frame-work for Tutoring) to address these psychomotor task training needs. Our ap-proach is to utilize heterogeneous sensor data to identify physical motions through acceleration data from a smartphone and to monitor respiratory activity through a BioHarness, while interacting with GIFT simultaneously. We also uti-lize a computational model to better understand the learner and domain. We focus on a precision-required psychomotor task (i.e., golf putting) and create a series of courses in GIFT that instruct how to do putting with tactical breathing. We report our implementation of a physio-cognitive model that can account for the process of psychomotor skill development, the GIFT extension, and a pilot study that uses the extension. The physio-cognitive model is based on the ACT-R/Φ architecture to model and predict the process of learning, and how it can be used for improving the fundamental understanding of the domain and learner model. Our study contributes to the use of cognitive modeling with physiological con-straints to support adaptive training of psychomotor tasks in ITSs.
Kim, J. W., Dancy, C. L., & Sottilare, R. A. (2018). Towards using a physio-cognitive model in tutoring for psychomotor tasks. In proceedings of the AIED Workshop on Authoring and Tutoring for Psychomotor, Mobile, and Medical Domains, London, UK.
Artificial Intelligence and Robotics Commons, Nervous System Commons, Respiratory System Commons