TY - JOUR
AU1 - USA, Karl E. Friedl, PhD, MS
AU2 - PhD, Harold F. O'Neil,
AB - ABSTRACT Computer-based technologies informed by the science of learning are becoming increasingly prevalent in education and training. For the Department of Defense (DoD), this presents a great potential advantage to the effective preparation of a new generation of technologically enabled service members. Military medicine has broad education and training challenges ranging from first aid and personal protective skills for every service member to specialized combat medic training; many of these challenges can be met with gaming and simulation technologies that this new generation has embraced. However, comprehensive use of medical games and simulation to augment expert mentorship is still limited to elite medical provider training programs, but can be expected to become broadly used in the training of first responders and allied health care providers. The purpose of this supplement is to review the use of computer games and simulation to teach and assess medical knowledge and skills. This review and other DoD research policy sources will form the basis for development of a research and development road map and guidelines for use of this technology in military medicine. INTRODUCTION Computer-based technologies informed by the science of learning are becoming increasingly prevalent in education and training. For the Department of Defense (DoD), this presents a great potential advantage to the effective and efficient preparation of a new generation of service members. Military medicine, in particular, has broad education and training challenges that range from combat medic training to personal protective measures required for every service member. Many of these challenges can be met with gaming and simulation technologies that this new generation has embraced.1,2 The purpose of this supplement is to review the state of the science in computer games and simulations that could be applied to military education and training in medicine. Based on this supplement and DoD research policy, we plan to develop a road map for research and development in this area as well as develop a set of What Works guidelines for the design and evaluation of these technologies in military medicine. THE NEED FOR MILITARY MEDICAL SIMULATION TRAINING Key reasons why the DoD is invested in computer games and simulation technology go beyond the obvious advantages of modern training effectiveness and patient safety.3,4 There is also a need to dramatically reduce training costs, especially through better preparation of personnel before costly field training exercises and reduction in total training time. This technology should deliver training in a form that the current generation of recruits expects. There is a need to have just-in-time training and refresher training, which potentially would reduce the decay of critical skills. There is a need to reach individuals wherever they are (e.g., away from their duty station, as they mobilize for disaster relief, in remote areas,; etc.), including team training of individuals even before the team is geographically assembled. The use of virtual patients is particularly important to replace standardized patients. Such virtual patients could also be used to teach interpersonal skills and diagnostics and treatment skills based on symptom presentation and interviews.5 The use of virtual patients could broadly be applied, from pharmacy technicians to psychiatry residents learning to interact with standardized patients. It can improve the quality of medical training by providing training adapted to the needs and ability of the individual, update relevant scenarios to provide adaptive training in response to changing health threats, and provide a large number of variations of conditions and scenarios to expand the military capability of the individual or team. These militarily unique computer training scenarios are critical to the integration of classroom and other medical training that will have to be applied in high-stress complicated environments (e.g., noisy, lowlight, airframe or vehicle vibration, threat of attack). An example is the training provided through the Army's Medical Simulation Training Centers currently established at 18 military installations (http://www.peostri.army.mil/PRODUCTS/MSTC/). Most importantly, if appropriate competency outcome measures have been determined, computer-based games and simulation training can test and objectively score individuals for their competence. There are other challenges in the application of computer-based training technologies that are important to the DoD. The service members cannot become dependent on these technologies in an operational environment rather the technology should truly improve the independent capabilities of the trained individual. This becomes important for agility and survivability, especially with modern day threats aimed at the technology itself (e.g., electromagnetic pulse weapons that would shut down all electronics). Thus, this military medical training must balance the use of technology in training context, with its probable absence in operational environments. This is especially important for the DoD and others who may operate in remote and austere environments where technology including electronic systems of all kinds, including telementoring and decision support tools, may not be available. For the DoD, there is also a need to provide elements of science, technology, engineering, and math (STEM) training for the pool of motivated recruits who may have inadequate background education in many areas critical to their skill set (e.g., math and physics for radiology technicians). Thus, STEM proficiency6 is also a military medical need (aside from the national security implications of a generation of underperforming U.S. high school students). One example of engaging game-based STEM training would be a game that incorporates positive role models and military scenarios. For example, use of physics and mathematical principles to secretly capture an enemy submarine and its code machines, revolving around a display such as the U-505 at the Chicago Museum of Science and Industry (http://www.msichicago.org/whats-here/exhibits/u-505/learning-tools/learning-games/). These games would help prepare future generations of K-12 students for critical STEM technical jobs including possible interest in military jobs. The DoD must also produce qualified individuals within a constrained period of time, to reduce manpower costs and to improve availability of the needed specialists. Over-the-horizon concepts of more efficient and effective learning through electrical stimulation and pharmacological activation of specific brain centers may ultimately serve to explain how current technologies used in the entertainment industry are so effective in promoting behaviors that facilitate learning. For example, the same learning activation in classrooms may be purposefully accomplished through the use of engaging game technology if we understand the scientific underpinnings. The requirement to reduce training time through more effective training strategies also requires an appreciation of the training “dosage” as well as evaluation criteria that will determine the probability of properly trained medical personnel. Such medical training for enlisted service members is conducted at San Antonio, Texas (http://www.metc.mil/). This command supports the largest single medical training campus in the world, i.e., Medical Education & Training Center. There are 21,000 students trained annually in more than 60 major medical specialty programs to serve the needs of the Army, Navy, and Air Force.7,8 In addition to this training campus for enlisted service members, the Uniformed Services University of the Health Sciences (USUHS) in Bethesda, Maryland trains physicians, nurses, and allied medical professionals (http://www.usuhs.mil/). The Army alone has approximately 5,000 physicians and 11,000 nurses, along with many other medical professionals. Since 1980, USUHS has trained 4,700 physicians, providing approximately 20% of the military medical corps physician accessions each year. These service members, and many more medical and allied science officers recruited from other sources, require specialty training in military medicine and refresher training within each of their specialties throughout their careers. Beyond the specific specialty training needs of DoD medical personnel, all service members require common skills training in health topics to maximize their readiness status (i.e., their preparedness to perform their trained mission today) as well as to instill individual responsibility for their own health. This training includes a wide range of topic areas such as understanding signs and symptoms associated with chemical, biological, radiological, nuclear, and explosives attacks, recognizing behavioral health issues in themselves and their buddies, proper use of effective personal protective measures against disease-carrying vectors (e.g., malarial mosquitoes), and avoidance of personal health damaging behaviors (e.g., smoking and excessive alcohol consumption). One example of a computerized approach to providing this fundamental training are the small business grants awarded under the topic “Micro Games for Proactive Preventive Medicine” (http://www.sbir.gov/sbirsearch/detail/242049). This latter topic of promoting individual responsibility for one's own health is a key theme of the Army Surgeon General (LTG Horoho), who has described the need to develop training tools to help develop the “LifeSpace” of the soldier—that majority of the soldier's time when they are not in contact with the medical health care system.9 This LifeSpace can be filled in, in part, through the use of medical education and training delivered via mobile health technologies especially for health behaviors such as weight regulation, activity and fitness habits, and smoking cessation.10 Everyday off-the-shelf technologies such as personally owned smart phones and laptop computers can be an effective means to reach and educate today's young service member. Technologies developed first in the entertainment industry, such as individual and multiplayer electronic games,11,12 interactive virtual worlds,13,14, virtual human technologies,5,15 and 3-dimensional interactive capabilities such as new motion sensing technologies that create a Star Trek-like “holodeck” (e.g., Kinect),16 can be harnessed and tested for military medical training. The challenge is not just the technology but the science of learning that should underlie technology use in medical education and training. Military use of medical simulation technologies has to date relied heavily on a family of commercially available off-the-shelf human manikins and part-task training simulators (e.g., chest tube simulators, intubation and colonoscopy simulators, anesthesia simulators, etc.).17,18 Less than a decade ago, everyone had a “simulator in a closet,” representing primarily an expensive, difficult to operate and maintain simulator with unknown training effectiveness, and thus, kept in the storage closet rather than actually used in any curriculum. Many military medical training simulation centers still have a myriad of different systems intended for different medical task training, most of which do not operate on other hardware or software systems and which are in various stages of development and validation. Unlike the Food and Drug Administration approval for new medical devices, simulation systems used in medical education and training do not fall under one governing body that would ensure that such training systems are efficient and effective. If it is not intended for medical diagnosis or treatment, but rather for training, these systems are not reviewed by the Food and Drug Administration. Thus, medical education and training simulators are currently a wild west of unregulated simulation systems and claims. There should be guidelines for the use of computer simulation in education and training. Medical training goals, curricula, and performance standards as well as test standards19,20 should dictate the appropriate insertion points where more affordable and usable training simulations could greatly improve medical training. This overall goal is, in part, the specific goal of a new DoD intramural consortium led by the USUHS National Capital Area Medical Simulation Center (http://simcen.usuhs.edu/Pages/default.aspx). For example, standards for physician training are most advanced in the surgical community where testing and training of the fundamentals of laparoscopic surgery have been pioneered.21,–23 Laparoscopic surgery is well suited to the early adoption of virtual training and testing technologies because of the similarity between virtual and real procedures.4 The training emphasizes the development of psychomotor skills and dexterity necessary to master laparoscopic surgery. Another DoD goal in the use of simulation technologies in medicine is to dramatically reduce the use of live animals in military medical training, an objective of the DoD medical simulation training research program.24 Simulations now provide a high level of training engagement and realism,25,26 which may allow some tasks with simulation to replace training with live animals. Development of such simulations needs to be guided by a science of learning approach27 that has been lacking in the earlier development of medical training including that involving live animals and cadavers. Other significant benefits of simulation vs. live animals are the ability to train to multiple presentations of a medical problem and with many repeated practice trials that would not be practical with animals. We believe that this simulation technology is most useful in the initial phase of skills development that leads up to apprentice-level competence after which a trainee can then participate and be mentored in real medical procedures using real patients. The current state of the art in either simulation or life tissue training is not an adequate substitute for the patients in the training of fully competent medical providers.28 For all of the reasons above, it is important for the DoD to determine what criteria must be applied in the design and evaluation of computer-based medical training systems. The goal is to use new simulation opportunities to change the old discomfiting concept of training medical procedures from “see one, do one, teach one” to “see one, simulate many, do one competently, teach many”.29 This supplement is based on the first of three workshops co-organized with the Office of Naval Research and the Telemedicine and Advanced Technology Research Center (TATRC) by UCLA/CRESST. The first workshop reviewed the state-of-the-science in medical simulation training, design, and evaluation from researchers in these areas. The second workshop focused on specific technology applications that could be designed and delivered to support the specific needs of the Medical Education & Training Center in combat medic training and other enlisted medical specialty training as well as training for Aeromedical Evacuation personnel. This second workshop focused on the development of a road map and topics for what works in computer simulations in gaming and simulations. It is expected that this latter book of guidelines would be published by a commercial publisher. The third workshop will finalize the road map and recommended guidelines for simulations developed for military medical education and training. This work directly supports DoD training requirements as dictated by DoD Instruction 1322.24 (Medical Readiness Training), which states that “Medical readiness training programs shall include realistic individual and collective medical skills training and shall maximize the use of emerging technology, including distance learning, simulation, and virtual reality.” It also supports another DoD Instruction, DoDI 3216.01 (Use of Animals in DoD Programs), which states that methods other than animal use shall be considered and used whenever possible to attain the objectives of training “if such alternative methods produce scientifically or educationally valid or equivalent results.” CURRENT DoD RESEARCH INVESTMENTS IN MEDICAL SIMULATION The current investment in military medical simulation education and training research is summarized in detail elsewhere30,31 and some military studies on medical simulation training have been conducted and reported.32,–34 In brief, new core funding has been made available in the DoD to support an organized research effort that includes at least four principal thrust areas. The most mature of these four areas is a fully funded multiyear academically based effort under the Combat Casualty Training Consortium initiative.31 This carefully crafted consortium specifically addresses issues that are currently highest priority in military medical training—i.e., combat medic skills training. To the disappointment of some, however, this funding was not directed to high-powered laboratories specializing in surgical specialty simulation training, but instead focused on uniquely military problems to improve medics training and also to reduce reliance on live animals. In the civilian sector, there has been a great deal of good analytic work on the tradeoffs of using live animals. For example, the impact on the neurosciences by the International Animal Research Regulations was documented by the Institute of Medicine and the National Research Council.35 Three other DoD initiatives are partially funded and in development, including the Medical Practice Initiative for medical specialty training (e.g., mobile platforms for just-in-time training and refresher training for humanitarian mission and disaster response in the Mobile Learning Environment project) (http://www.mole-project.net/the-project/global-medaid-app); the Patient Focused Initiative that addresses the Army Surgeon General's high-priority LifeSpace initiative (e.g., virtual human interactive behavioral health coaching [SimCoach] project)5,9; and the Developer Tools Initiative that will fill a critical need for open source physiology engines (models and artificial intelligence tools) to drive realistic and accurate medical simulation trainers.31 In addition to new DoD funding support, high interest in medical simulation and training is spurred in part by the recognition that current technologies can be brought to bear to address critical needs in medical education and training. Service members today tend to be equipped with personal smart phones and expect to find and receive information through these everyday technologies. The Defense Advanced Research Projects Agency has entered the field to promote development of game-based medical training software that will include development of deeper understanding of physiological principles that promote a broader ability to deal with real-life medical problems.36 In addition, the DoD has partnered with allies in a NATO workgroup on Advanced Training Technologies for Medical Healthcare Professionals (NATO HFM-215); the results of this workshop will be reported elsewhere. There is also much to learn from the rest of the DoD and the Human Systems Integration community that has embraced and continues to develop new training technologies as well as define how electronic systems integrate into military internet security systems.37 In particular, the Office of Naval Research has been a leader in advancing research in more effective education and training technologies, and the results of this effort provide a springboard to the development of guidelines for standardization and evaluation of new military medical simulations for education and training. Such military medical applications will also have many dual-use benefits in civilian medical training. The science of learning specifically targeted toward the use of computer simulations in medical education and training is also a focus of this supplement. Mayer27 conceptualized the science of learning as the scientific study of how people learn. It is supported by the science of instruction (how to teach) where teaching is accomplished by humans or technologies. Mayer conceptualizes the science of assessment as the determination of what people know. Baker38 provides an excellent overview of assessment with a focus on reliable and valid measures. The classification of learning outcomes as a family of cognitive demands has been provided by Baker and Mayer.39 These cognitive outcomes are the following: content or domain understanding, problem solving, self-regulation, communication, and collaboration/teamwork. The utility of this classification for computer games is provided by O'Neil et al.40 A complementary taxonomy of learning outcomes is provided by Anderson and Krathwohl.41 This taxonomy replaces Bloom's taxonomy.42 An application of the science of learning to science education is provided by the National Research Council.43 An interesting metalook of how to conceptualize learning is provided by Bransford et al.44 They suggest an integration of three types of learning, i.e., informal learning, implicit learning, and formal learning. They define informal learning as learning that happens in non-school public settings such as museums, zoos, and after-school clubs or the learning that occurs in homes, on playgrounds, among peers, and in other situations (p. 216). Their definition of implicit learning is information that is acquired effortlessly and sometimes without conscious recollection of the learned information or having acquired it (p. 210). Formal learning is the learning that goes on in formal environments such as schools where the science of instruction should be explicit. ORGANIZATION OF THE SUPPLEMENT The organization of this supplement was partially based on the organization of a workshop organized by TATRC/ONR/CRESST on “Designing and Using Computer Simulations in Medical Education and Training.” This supplement is the documentation of this workshop that involved presentations, followed by the development of manuscripts. The rationale for selection of authors was based on three underlying challenges, namely1 there are different research communities in simulation research in medical education and training, e.g., researchers from medical vs. nonmedical environments and defense vs. civilian research communities2; the lack of infusing research in simulation for medical education and training from a science of learning perspective; and 3 the lack of lessons learned from the use of simulation in other nonmedical fields (e.g., aviation). Unfortunately, there is minimal scientific contact between these different communities. For example, researchers tend to have specific professional identities contextualized in either military or civilian research organizations that result in different journals and conferences to report their research. To partially address these challenges, we organized this journal supplement. Thus, this supplement presents work by authors from multiple disciplines whose expertise is using computer simulation to teach or assess in both medical and nonmedical environments. Experts from both military and civilian organizations are also represented. Two disciplines, i.e., science of learning and psychometrics, were specifically overrepresented as there exists minimum impact of science of learning in the medical uses of simulation and there is little psychometric knowledge for estimating the reliability and validity of simulations used for teaching or assessment. The articles in the supplement also include original studies, reviews, and conceptual analyses. The supplement itself is organized into 4 major sections, representing 4 different issues, respectively: Design Issues, Assessment and Evaluation Issues, Instructional Strategies Issues, and Psychometric Issues. Design Issues We viewed critical design issues in computer simulation for medical education and training as the use of cognitive task analysis, how much fidelity is desirable, and costs. This cognitive task analysis focus is represented with three different but complementary cognitive task methodologies (Munro et al, Cannon Bowers et al and Pugh et al). Fidelity and cost considerations are represented by articles by Talbot and by Fletcher et al respectively. Assessment and Evaluation Issues We viewed these issues as another area where nonmedical research has useful lessons learned for military medicine education and training. This section is represented by three articles: an assessment methodology derived from a research project focused on Navy but nonmedical training (Koenig et al), the application of national test standards to simulation of clinical palpation skill (Pugh), and lessons learned in nonmedical simulation evaluations applied to the evaluation of medical simulations (Bewley et al). Instructional Strategies Issues How to teach and assess are represented by three articles: what instructional and assessment strategies are effective in reducing skill decay (Perez et al); an instructional strategy using virtual trainers on FAST Window identification, acquisition, and diagnosis (Chung et al); and the strategies effective in adaptive and perceptual learning (Kellman). Psychometric Issues Psychometrics (the study of psychological measurement) deals with the technical quality of measures, which is the overall basis of the trustworthy interpretation of measurement situation(s). It includes validity, reliability, comparability, equating, scaling, and standardization as well as theoretical frameworks such as classical test theory, item response theory, and generalizability theory.45 This section is represented by three different approaches: an evidence-centered design one (Mislevy), a latent modeling one (Cai), and the Assessment-Diagnosis-Treatment-Outcome model that includes psychometric issues (Spratt). In summary, this supplement presents an overview of the key considerations in simulation design and assessment for medical education and training. Multiple experts from multiple disciplines have contributed their specific ideas on how thoughtful simulation design should be planned and executed. These articles suggest how medical education and training simulations can be developed that are scientifically based, outcomes driven, and cost conscious. REFERENCES 1. Ahn J Digital divides and social network sites: which students participate in social media? J Educ Computing Res  2011; 45: 147– 63. Google Scholar CrossRef Search ADS   2. Orvis KA, Moore JC, Belanich J, Murphy JS, Horn DB Are soldiers gamers? Videogame usage among soldiers and implications for the effective use of serious videogames for military training. Mil Psychol  2010; 22: 143– 57. Google Scholar CrossRef Search ADS   3. Networking and Information Technology Research and Development Program (NITRD) High-Confidence Medical Devices: Cyber-Physical Systems for 21st Century Health Care—A Research and Development Needs Report , February 2009, 88 pp. Available at http://www.whitehouse.gov/files/documents/cyber/NITRD%20-%20High-Confidence%20Medical%20Devices.pdf; accessed October 14, 2012. 4. Kunkler K The role of medical simulation: an overview. Int J Med Robot  2006; 2: 203– 10. Google Scholar CrossRef Search ADS PubMed  5. Rizzo A, Lange B, Buckwalter JG, et al.   SimCoach: an intelligence virtual human for providing healthcare information and support. Proceedings of 8th International Conference on Disability, Virtual Reality and Associated Technologies. Vina del Mar, Valparaiso, Chile. August 31–September 2, 2010. Available at http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA541005; accessed September 3, 2012. 6. Aleven VA, Koedinger KR An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor. Cogn Sci  2002; 26: 147– 79. Google Scholar CrossRef Search ADS   7. Kiser WR, Hanson L, Stevens A, Miller R, Denton-Price T Joint enlisted training through DoD—the new paradigm. Presentation at the 2011 Military Health System Conference, National Harbor, Maryland, January 26, 2011. Available at http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA556307; accessed May 12, 2012. 8. Kirby SN, Marsh JA, Thie HJ Establishing a Research and Evaluation Capability for the Joint Medical Education and Training Campus . RAND Corporation, Santa Monica, CA, NTIS ADA 545349, 2011. 132 pp. 9. Horoho P Plenary remarks at the 2012 Military Health System Conference, National Harbor, Maryland , January 31, 2012. Available at http://www.armymedicine.army.mil/news/docs/MHS2012PlenaryLTGHorohoArmySurgeonGeneral_31_JAN_12_Remarks.pdf; accessed May 3, 2013. 10. Ershow AG, Friedl KE, Peterson CM, Riley WT, Rizzo A, Wansink B (editors): Virtual reality technologies for research and education in obesity and diabetes. A National Institutes of Health–Department of Defense Symposium. J Diab Sci Technol  2011; 5: 212– 344. Google Scholar CrossRef Search ADS   11. Tobias S, Fletcher JD Reflections on “a review of trends” in serious gaming. Rev Educ Res  2012; 82: 233– 7. Google Scholar CrossRef Search ADS   12. Tobias S, Fletcher JD (editors): Computer Games and Instruction . Charlotte, NC, Information Age Publishing, 2011. 13. Heinrichs WL, Youngblood P, Harter PM, Dev P Simulation for team training and assessment: case studies of online training with virtual worlds. World J Surg  2008; 32: 161– 70. Google Scholar CrossRef Search ADS PubMed  14. Riedl MO, Stern A, Dini DM, Alderman JM Dynamic experience management in virtual worlds for entertainment, education, and training. Int Trans Syst Sci Appl  2008; 3: 23– 42. 15. Kenny P, Hartholt A, Gratch J, et al.   Building interactive virtual humans for training environments. Paper No. 7105, 16 pp. Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), Orlando, Florida, 2007. Available at: http://ict.usc.edu/pubs/Building%20Interactive%20Virtual%20Humans%20for%20Training%20Environments.pdf; accessed September 2, 2012. 16. Lange B, Koenig S, McConnell E, et al.   Interactive game-based rehabilitation using the Microsoft Kinect. In: Virtual Reality Workshops, 2012 IEEE Transactions on Visualization and Computer Graphics , Washington DC: IEEE Computer Society, 2012, pp 171– 2. Available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6180935&contentType=Conference+Publications; accessed October 14, 2012. 17. Cooper JB, Taqueti VR A brief history of the development of mannequin simulators for clinical education and training. Qual Saf Health Care  2004; 13( Suppl 1): i11– i18. Google Scholar CrossRef Search ADS PubMed  18. Passiment M, Sacks H, Huang G Medical Simulation in Medical Education: Results of an AAMC Survey . Washington, DC, Association of American Medical Colleges, 2011. Available at https://members.aamc.org/eweb/upload/Medical%20Simulation%20in%20Medical%20Education%20Results%20of%20an%20AAMC%20Survey.pdf; accessed June 20, 2012. 19. American Educational Research Association (AERA), American Psychological Association (APA), and National Council for Measurement in Education (NCME) Standards for Educational and Psychological Testing . Washington, DC, American Educational Research Association, 1999. 20. Baker EL Standards for educational and psychological testing. In: Encyclopedia of Diversity in Education . Edited by Banks JA Thousand Oaks, CA, Sage, 2012. 21. Rehrig ST, Powers K, Jones DB Integrating simulation in surgery as a teaching tool and credentialing standard. J Gastrointest Surg  2008; 12: 222– 33. Google Scholar CrossRef Search ADS PubMed  22. Cotin S, Stylopoulos N, Ottensmeyer M, Neumann P, Rattner D, Dawson S Metrics for laparoscopic skills trainers: the weakest link. In: Medical Image Computing and Computer-Assisted Intervention. Lecture Notes in Computer Science , Vol 2488, pp. 35– 43. Springer-Verlag, London, UK, 2002. Google Scholar CrossRef Search ADS   23. Rosen J, Chang L, Brown JD, Hannaford B, Sinanan M, Satava R Minimally invasive surgery task decomposition—etymology of endoscopic suturing. In: Studies in Health Technology and Informatics—Medicine Meets Virtual Reality , Newport Beach, CA, January 2003, 7 pp. Available at http://brl.ee.washington.edu/BRL_Pubs/Pdfs/Rep166.pdf; accessed September 3, 2012. 24. House Report 112-078, National Defense Authorization Act for Fiscal Year 2012: Title VII. Health Care Provisions. Items of Special Interest. Use of Simulation Technology in Medical Training , 2011. Available at http://www.gpo.gov/fdsys/pkg/CRPT-112hrpt78/pdf/CRPT-112hrpt78.pdf; accessed May 3, 2013. 25. Gordon JA, Oriol NE, Cooper JB Bringing good teaching cases “to life”: a simulator-based medical education service. Acad Med  2004; 79: 23– 7. Google Scholar CrossRef Search ADS PubMed  26. Gordon JA As accessible as a book on a library shelf: the imperative of routine simulation in modern health care. Chest  2012; 141: 12– 6. Google Scholar CrossRef Search ADS PubMed  27. Mayer RE Applying the Science of Learning . Boston, MA, Pearson, 2011. 28. Sohn VY, Miller JP, Koeller CA, et al.   From the combat medic to the forward surgical team: the Madigan model for improving trauma readiness of brigade combat teams fighting the Global War on Terror. J Surg Res  2007; 138: 25– 31. Google Scholar CrossRef Search ADS PubMed  29. Vozenilek J, Huff JS, Reznek M, Gordon JA See one, do one, teach one: advanced technology in medical education. Acad Emerg Med  2004; 11: 1149– 54. Google Scholar CrossRef Search ADS PubMed  30. Pugh CM, Bevan MG, Duve RJ, White HL, Magee JH, Wiehagen GB A retrospective review of TATRC funding for medical modeling and simulation technologies. J Soc Sim Healthcare  2011; 6: 218– 25. Google Scholar CrossRef Search ADS   31. Friedl KE, Talbot TB, Steffensen S Information science and technology—a new paradigm in military medical research . Technical Report 12-1. Telemedicine and Advanced Technology Research Center, Fort Detrick, Maryland, 2012. 32. Holcomb JB, Dumire RD, Crommett JW, et al.   Evaluation of trauma team performance using an advanced human patient simulator for resuscitation training. J Trauma  2002; 52: 1078– 86. Google Scholar CrossRef Search ADS PubMed  33. Ritter EM, Bowyer MW Simulation for trauma and combat casualty care. Minim Invasive Ther Allied Technol  2005; 14: 224– 34. Google Scholar CrossRef Search ADS PubMed  34. Hackett M, Norfleet J, Pettitt B Usability analysis of prototype partial task tourniquet trainers. Presentation at The Interservice/Industry Training, Simulation & Education Conference (I/ITSEC), 2011. Available at http://ntsa.metapress.com/link.asp?id=44g7p077w7617224; accessed October 14, 2012. 35. Institute of Medicine (IOM), National Research Council (NRC) International animal research regulations: impact on neuroscience research: Workshop summary . Washington, DC, The National Academies Press, 2012. 36. Kenyon H DARPA wants gamers to design medical training software. Government Computer News , May 3, 2012. Available at http://gcn.com/articles/2012/05/03/darpa-game-designers-medical-training-software.aspx; accessed October 14, 2012. 37. Fletcher JD Education and training technology in the military. Science  2009; 323: 72– 5. Google Scholar CrossRef Search ADS PubMed  38. Baker EL The Chimera of Validity. Teachers Coll Rec  2013; 115. Available at http://www.tcrecord.org/library ID Number: 17106; accessed August 29, 2013. 39. Baker EL, Mayer RE Computer-based assessment of problem solving. Comput Human Behav  1999; 15: 269– 82. Google Scholar CrossRef Search ADS   40. O'Neil HF, Wainess R, Baker EL Classification of learning outcomes: evidence from the computer games literature. The Curriculum Journal  2005; 16( 4): 455– 74. Google Scholar CrossRef Search ADS   41. Anderson LW, Krathwohl DR (editors): A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives . Boston, MA, Allyn & Bacon, 2001. 42. Bloom BS (editor): Taxonomy of Educational Objectives: Book I: Cognitive Domain . New York, Longmans, Green, 1956. 43. National Research Council Learning Science Through Computer Games and Simulations . Washington, DC, The National Academies Press, 2011. PubMed PubMed  44. Bransford J, Vye N, Stevens R, et al.   Learning theories and education: Toward a decade of synergy. In: Handbook of Educational Psychology , Ed 2, pp 209– 44. Edited by Alexander PA, Winne PH Mahwah, NJ, Erlbaum, 2006. Google Scholar CrossRef Search ADS   45. Jones LV, Thissen DA History and Overview of Psychometrics. In: Handbook of Statistics, Vol 26: Psychometrics , pp 45– 79. Edited by Rao CR, Sinharay S Amsterdam, The Netherlands, Elsevier Science B.V., 2007. Google Scholar CrossRef Search ADS   Footnotes 2 This work was partially supported by a grant from the Office of Naval Research (Award Number N00014-10-1-0978). Reprint & Copyright © Association of Military Surgeons of the U.S.
TI - Designing and Using Computer Simulations in Medical Education and Training: An Introduction
JF - Military Medicine
DO - 10.7205/MILMED-D-13-00209
DA - 2013-10-01
UR - https://www.deepdyve.com/lp/oxford-university-press/designing-and-using-computer-simulations-in-medical-education-and-0OpepziM2M
SP - 1
EP - 6
VL - 178
IS - suppl_10
DP - DeepDyve
ER -