Abstract
Tools for adaptive learning are on the rise, resulting in the creation and implementation of increasingly intelligent tutoring systems. These systems can be applied in a variety of contexts, including civilian, military, and emergency operations. Such systems may also include the capability to adapt to learner needs based on performance or behavioral input. However, the use of such adaptation may vary in its success depending on the domain it is applied to. This paper examines the potential utility of adaptive tutoring for educating Emergency Medical Service (EMS) workers. We examine two complementary approaches that can be used to drive adaptation: performance-based and behavior-based adaptive learning models in intelligent tutoring. We then discuss implications of implementing such learning models for intelligent tutoring in EMS. Next, we outline ongoing research as a use case for the validation of different adaptive learning models. Finally, we discuss expected impacts of this line of research, including the expansion of adaptive tutoring to other domains related to EMS.
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Acknowledgments
This work was supported, in part, by the Office of the Assistant Secretary of Defense for Health Affairs, through the Joint Program Committee-1/Medical Simulation and Information Science Research Program under Award No. W81XWH-16-1-0460. Opinions, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by the Department of Defense. The U.S. Army Medical Research Acquisition Activity, 820 Chandler Street, Fort Detrick MD 21702-5014 is the awarding and administering acquisition office.
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Stowers, K., Brady, L., Huh, Y., Wray, R.E. (2019). Assessing the Role of Behavioral Markers in Adaptive Learning for Emergency Medical Services. In: Nazir, S., Teperi, AM., Polak-Sopińska, A. (eds) Advances in Human Factors in Training, Education, and Learning Sciences. AHFE 2018. Advances in Intelligent Systems and Computing, vol 785. Springer, Cham. https://doi.org/10.1007/978-3-319-93882-0_19
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