Adaptive instruction for medical training in the psychomotor domain

Abstract

The adaptive instruction provided by Intelligent Tutoring Systems (ITSs) tailors direction, support, and feedback to enhance/maintain the learning needs (e.g., lack of knowledge or skill) of each individual. Today, ITSs are generally developed to support desktop training applications, with the most common domains involving cognitive problem solving tasks (e.g., mathematics and physics). In recent years, implementations of game-based tutors authored using the Generalized Intelligent Framework for Tutoring (GIFT), an open-source tutoring architecture, provided tailored training experiences for military tasks through desktop applications (e.g., games including Virtual Battlespace and Virtual Medic). However, these game-based desktop tutors have also been limited to adaptive instruction for cognitive tasks (e.g., problem solving and decision-making). The military requires adaptive instruction to extend beyond the desktop to be compatible with the physical nature of many tasks performed by soldiers, sailors, and airmen. This article examines how commercial sensor technologies might be adapted to work with GIFT and support tailored computer-guided instruction in the psychomotor domain for a military medical training task, specifically hemorrhage control. Toward this goal, we evaluated the usability and system features of commercial smart glasses and pressure-sensing technologies. Smart glasses were selected as the focus of this study over handheld mobile devices in order to promote a hands-free experience during the training of hemorrhage-control tasks on a mannequin. Pressure sensors were selected to provide direct measures of effectiveness during the application of tourniquets and pressure bandages. Each set of technologies (smart glasses and pressure sensors) was evaluated not with respect to each other, but with respect to their capabilities to support adaptive instruction in the wild at the learner’s point-of-need and criteria based on established usability heuristics. Instruction in the wild is training provided in an environment outside the classroom and areas where tracking and sensing infrastructure are available (e.g., deployed areas of operation). We examined a wide range of features and capabilities, and evaluated their compatibility with the hemorrhage-control task, to answer the following question: what system design features (e.g., usability and interaction) are needed to support adaptive instruction for this individual psychomotor task at the point-of-need in locations where no formal training infrastructure is available?

Keywords

Adaptive instruction Intelligent Tutoring Systems psychomotor domain smart glasses pressure-sensing technologies hemorrhage control

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References

Sottilare

. Adaptive Intelligent Tutoring System (ITS) research in support of the Army Learning Model—research outline. Report No. ARL-SR-0284. Orlando, FL: Army Research Laboratory, 2013.

Sottilare

LaViola

. A process for adaptive instruction of tasks in the psychomotor domain. Des Recommend Intell Tutor Syst 4 Domain Model 2016; 15: 185.

Cossairt

LaViola

Jr . SetPad: a sketch-based tool for exploring discrete math set problems. In: proceedings of the international symposium on sketch-based interfaces and modeling, Eurographics Association, Cagliari, Italy, 4 June 2012, pp.47–56.

Cheema

LaViola

. PhysicsBook: a sketch-based interface for animating physics diagrams. In: Proceedings of the 2012 ACM international conference on intelligent user interfaces, Lisbon, Portugal, 14 February 2012, pp.51–60. ACM.

Sottilare

Brawner

Goldberg

et al . The Generalized Intelligent Framework for Tutoring (GIFT). Concept paper released as part of GIFT software documentation. Orlando, FL: US Army Research Laboratory–Human Research & Engineering Directorate (ARL-HRED), 31 July 2012.

Sottilare

Holden

. Motivations for a generalized intelligent framework for tutoring (gift) for authoring, instruction and analysis. In: AIED 2013 workshops proceedings, Memphis, USA, 9 July 2013, Vol. 7, p.1.

Sottilare

Holden

Goldberg

et al . The Generalized Intelligent Framework for Tutoring (GIFT). In: Best

Galanis

Kerry

Sottilare

(eds) Fundamental issues in defense simulation & training. Surrey, UK: Ashgate Publishing, 2013.

Goldberg

Sottilare

Brawner

et al . Adaptive game-based tutoring: mechanisms for real-time feedback and adaptation. In: Proceedings of the I3M: the 9th International Multidisciplinary Modeling & Simulation Multiconference, Vienna, Austria, 19–22 September 2012.

Army

. The US Army learning concept for 2015. US Army, 2011.

10.

Butler

Jr Butler

Jr Holcomb

et al . Tactical combat casualty care 2007: evolving concepts and battlefield experience. Mil Med 2007; 172(Supplement_1): 1–9.

11.

Combat Application Tourniquet. http://combattourniquet.com/ (September 2015).

12.

Sotomayor

Proctor

. Assessing combat medic knowledge and transfer effects resulting from alternative training treatments. J Defens Model Simulat 2009; 8: 121–134.

13.

Hackett

Willson

Fefferman

et al . The effect of difficulty levels within a virtual medical simulation. In: the interservice/industry training, simulation & education conference (I/ITSEC), Orlando, Florida, 1–4 December 2014, paper no. 14228.

14.

Nielsen

. Heuristic evaluation. Usabil Inspect Meth 1994; 17: 25–62.

15.

Holcomb

. The 2004 Fitts Lecture: current perspective on combat casualty care. J Trauma Acute Care Surg 2005; 59: 990–1002.

16.

Wedmore

McManus

Pusateri

et al . A special report on the chitosan-based hemostatic dressing: experience in current combat operations. J Trauma Acute Care Surg 2006; 60: 655–658.

17.

Tarrant

Ryan

Hamilton

et al . A pictorial review of hypovolaemic shock in adults. Br J Radiol 2008; 81: 252–257.

18.

Sottilare

LaViola

. Extending intelligent tutoring beyond the desktop to the psychomotor domain: a survey of smart glass technologies. In: proceedings of the 2015 interservice/industry training, simulation, and education conference (I/ITSEC), Arlington, VA, National Training and Simulation Association.

19.

Sottilare

. Considerations in the development of an ontology for a generalized intelligent framework for tutoring. In: proceedings of the international defense & homeland security simulation workshop of the I3M conference, Vienna, Austria, September 2012.

20.

Sottilare

Ragusa

Hoffman

et al . Characterizing an adaptive tutoring learning effect chain for individual and team tutoring. In: proceedings of the interservice/industry training simulation & education conference, Orlando, FL, December 2013.

21.

Younger

McEwen

Inkpen

. Wide contoured thigh cuffs and automated limb occlusion measurement allow lower tourniquet pressures. Clin Orthopaed Relat Res 2004; 428: 286–293.

22.

Kalla

Younger

McEwen

et al . Survey of tourniquet use in podiatric surgery. J Foot Ankle Surg 2003; 42: 68–76.

23.

Hagenouw

Bridenbaugh

van Egmond

et al . Tourniquet pain: a volunteer study. Anesthes Analges 1986; 65: 1175–1180.

24.

Welch

Foxlin

. Motion tracking survey. IEEE Comput Graph Appl 2002; 22: 24–38.

25.

Huang

Zhao

et al . A robust rgb-d slam algorithm. In: 2012 IEEE/RSJ international conference on intelligent robots and systems, Vilamoura, Portugal, 7 October 2012, pp.1714–1719. IEEE.

26.

Maimone

Lanman

Rathinavel

et al . Pinlight displays: wide field of view augmented reality eyeglasses using defocused point light sources. In: ACM SIGGRAPH 2014 emerging technologies, Vancouver, Canada, 27 July 2014, p.20. ACM.