Engagement and learning in simulation:recommendations of the Simnovate EngagedLearning Domain GroupWayne Choi,1,2 Ollivier Dyens,3 Teresa Chan,4 Mariles Schijven,5 Susanne Lajoie,6

Mary E Mancini,7 Parvati Dev,8 Li Fellander-Tsai,9 Mathieu Ferland,10 Pamela Kato,11

James Lau,12 Michael Montonaro,13 Joelle Pineau,14 Rajesh Aggarwal1,15

▸ Additional material ispublished online only. To viewplease visit the journal online(http://dx.doi.org/10.1136/bmjstel-2016-000177).

For numbered affiliations seeend of article.

Correspondence toDr Rajesh Aggarwal,Department of Surgery,Steinberg Centre for Simulationand Interactive Learning,Faculty of Medicine, McGillUniversity, 3575 Parc Avenue,Suite 5640, Montreal,Quebec H2X 3P9, Canada;rajesh.aggarwal@mcgill.ca

Received 5 December 2016Revised 2 February 2017Accepted 7 February 2017

To cite: Choi W, Dyens O,Chan T, et al. BMJ Stel2017;3(Suppl 1):S23–S32.

ABSTRACTBackground Health professions education (HPE) isbased on deliberate learning activities and clinicalimmersion to achieve clinical competence. Simulation isa tool that helps bridge the knowledge-to-action gapthrough deliberate learning. This paper considers how tooptimally engage learners in simulation activities as partof HPE.Methods The Simnovate Engaged Learning DomainGroup undertook 3 teleconferences to survey the currentconcepts regarding pervasive learning. Specific attentionwas paid to engagement in the learning process, withrespect to fidelity, realism and emotions, and the use ofnarratives in HPE simulation.Results This paper found that while many types ofsimulation exist, the current ways to categorise the typesof simulation do not sufficiently describe what aparticular simulation will entail. This paper introduces anovel framework to describe simulation bydeconstructing a simulation activity into 3 corecharacteristics (scope, modality and environment). Then,the paper discusses how engagement is at the heart ofthe learning process, but remained an understudiedphenomenon with respect to HPE simulation. Buildingon the first part, a conceptual framework for engagedlearning in HPE simulation was derived, with potentialuse across all HPE methods.Discussion The framework considers how the 3characteristics of simulation interplay with thedimensions of fidelity (physical, conceptual andemotional), and how these can be conveyed by andarticulated through beauty (as a proxy for efficiency) ascoexisting factors to drive learner engagement. Thisframework leads to the translation of deliberately taughtknowledge, skills and attitudes into clinical competenceand subsequent performance.

INTRODUCTIONEducation, in any form, is dependent on theengagement of the learner or student1 to be physic-ally, mentally and emotionally involved in learning.In health professions education (HPE), the aim isfor graduates to possess knowledge, exhibit skills,and demonstrate attitudes and behaviours that areparamount to providing high-quality medical care.Educational organisations such as medical andnursing schools, residency programmes, and con-tinuing HPE, tend to define a syllabus, and focuson deliberate activities to assist in learning.2 These

activities typically consist of lectures, tutorials andpractical sessions delivered by an expert clinician.Beyond such deliberate and didactic activities,

arrangements with healthcare facilities allow learn-ing in hands-on clinical settings, thus providing theexperiential learning so advocated by Sir WilliamOsler.3 This educational programme is basedaround clinical activity, and learning through obser-vation, experience and gradual acquisition ofknowledge, skills and behaviours. The quality ofexperiences and interactions may be highly depend-ent on the level of student–teacher interactions, thetypes of patient presentations encountered, and ona finely tuned elaboration of patient and diseasecharacteristics specific to the clinical setting. Otherfactors, such as primacy of patient care, heavy clin-ical workload of tutors, the presence of multiplelearners from multiple healthcare backgrounds,learner capacity and their existing knowledge, andrecently, work hour restrictions,3 may interact posi-tively or negatively on the effective engagementand outcomes of the learning process.A pertinent example of education in the clinical

setting is of the master-apprenticeship model intro-duced to the USA by William Halstead in the1880s4 5 following time spent observing the surgicaltraining programme in Germany. The trainee isattached to a master surgeon and learns throughobservation and participation in all activities relatedto the patient, from the operating room, inpatientward, surgical office and even home visits. The trai-nees are at the beck and call of the master surgeon(and resident at all times within the hospital) todeliver optimal care to all of their patients. It isthrough this process that they learn how to becomemaster surgeons themselves. It is the master surgeonwho decides when the trainee has achieved levels ofperformance to graduate from the programme.While this model—combined with Osler’s focus onbedside learning and the transformation initiated bythe Flexner Report for medical education to bemore scientifically rigorous6 has served as the bench-mark for over a century of postgraduate medicaltraining across the world, the current complexity ofthe medical system, the increased needs anddemands of patients, changing demographics, andthe sheer volume of learning to acquire all suggestthat may no longer be the ideal system for the edu-cation of healthcare professionals.7

Changes have been made over the past decadewith regard to preclinical curricula in HPE. The

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basic science model of anatomy, biochemistry, physiology, etc,has now been replaced in the majority of medical and nursingschools with organ and disease-based blocks, corresponding tolearning that is patient-based.8 Even more so, some schools cul-tivate the engagement of their learners with patients right fromtheir first semester, either through intermittent encounters basedon the current organ/disease block being studied, or throughdevelopment of a longitudinal relationship with patients suffer-ing from chronic diseases such as cancer, type II diabetes orheart failure, in clinical and community settings.

Despite the sea change in preclinical HPE, there has beenlittle movement towards modernisation of teaching and learningin clinical settings. The integral role of the student as an agenticlearner, comprising such characteristics as their personal epis-temology, self-concept, assertiveness, resilience and self-directedlearning, has not been fully realised. It is suggested that studentsneed to be able to successfully negotiate, engage and learn fromwhat they are afforded, in order to succeed both professionallyand personally.9

A critical issue with the education of health professions iswith regard to the subject material itself. Individuals seek carewhen they have an illness that they would like to have treated,or when they wish to maintain wellness. Understandably, theydemand the best care possible to be afforded to them. But‘best’, today is not limited to solely medical treatment and man-agement; it now includes a human relationship. Therefore, HPEmust be seen in a broader way: it must focus on the acquisitionof medical knowledge and must also pay attention to the indivi-dual’s overall wellness, from physical to mental to emotional.And while knowledge acquisition is the focus of the early stagesof training, its translation into clinical skills, attitudes and beha-viours is difficult to achieve.10

A bridge is thus required between knowledge acquisition andclinical practice. As previously mentioned, the apprenticeshipmodel of training whereby the student can deliberately practiseunder the watchful eye of the master is the accepted paradigm.Errors may be corrected before they can lead to patient harm,11

and over time, the trainee will undertake enough experiences tobe deemed competent and be certified for independent prac-tice.12–14 While this focus on treatment may be thought of asprimarily a concern in the craft specialties such as surgery,anaesthesia and gastroenterology, it may not apply as effectively

in clinical situations that involve interaction of a trainee with apatient or their family.

The Simnovate international summit aims to bring togetherexperts in various fields of healthcare to shape the future ofsimulation, education and innovation across four domains:patient safety, pervasive learning, medical technologies andglobal health. This white paper represents the work of theSimnovate Engaged Learning Domain Group, which consists ofan international group of experts with backgrounds in HPE,technology-enhanced learning, serious gaming, digital worlds,surgical simulation, dance and multimedia, and robotics. Thegroup exemplifies high-level track records of educationalinnovation research and its implementation, through extensivepublication and authority on the topic.

METHODSWe generated our white paper recommendations through anovel technique, which blended a consensus building procedurewith a scoping literature review on pervasive learning, engage-ment in learning, motivational theories and serious games.Between September and December 2015, the members of theSimnovate Engaged Learning Domain Group convened forthree teleconferences, and the members met in person in May2016 during the Simnovate Conference.

PopulationThe expert working group that was assembled was recruitedfrom an international group of individuals who had varyingdegrees of expertise. This group was specifically recruited tohave a wide berth of expertise, from different medical special-ties, medical education (undergraduate to postgraduate), seriousgames, simulation, gaming industry, literature and arts.

ProcessOur process sought to establish: (1) the current state of engagedlearning, pervasive learning and serious gaming in HPE; (2) thenature of engagement in simulation-based learning; and (3) therole of narratives in the learning process. We used an iterative,literature-informed, expert consensus-building procedure todistil the thoughts of our working group into this white paper.See figure 1 for an overview of our iterative process.

Our initial step was to gain a better understanding of thecurrent state of serious gaming in HPE. We searched onlinedatabases such as PubMed and Google Scholar for papers thatpertain to the use of games, gamification and other strategiesthat involved gaming elements, such as leader boards and com-petition in HPE, and specifically to simulation.

As the results were few, we expanded our search by includingstudies outside of HPE, using the same search terms. A list ofsuggested articles was sent to the group members prior to thefirst teleconference, and the topic was discussed.

Our discussions were augmented by an initial review of theliterature, which were in turn, guided by the memos and notestaken during the teleconference discussions in an iterativemanner. The second and third teleconferences were guided bythe discussions from the previous conferences, which led to thetopic of the roles of engagement and narratives in simulationfor HPE. These new discussions expanded the nature of ourinitial literature review, necessitating two subsequent reviews ofthe literature to inform this conference’s white paper, research-ing theories of engagement in learning, student engagement,cognition and emotion in learning, and motivation.

After the teleconferences, a small subset of the group (Choi,Aggarwal, Dyens, Lajoie) was tasked with coalescing the memos

Figure 1 Iterative process for paper writing for Engaged LearningDomain Group.

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and notes from the various teleconferences, as well as integrat-ing themes from the literature that was found. This documentwas then circulated within the expert group for comments andamendments both via email and in person at the Simnovate con-ference on 4 May 2016. The final version of this document wasgenerated in a collaborative fashion using online collaborationtools.

SIMULATION IN HPESimulation can be broadly defined as ‘an environment to replaceor amplify real-life experiences with guided experiences that areartificially devised in order to evoke and replicate substantialelements of the real environment in an interactive, immersiveand experiential manner’.15 Translated to the clinical sphere,simulation can substitute real patient encounters or other clinicalsituations—such as procedures and technical skills—with actors,artificial models such as mannequins and task trainers, orcomputers.16

The principle for simulation in HPE is to provide an oppor-tunity for participants to learn and to augment their clinicalskills through deliberate practice, in a safe and educationallyorientated environment.17 18 The aim is for these encounters totranslate into the clinical setting, leading to superior perform-ance, concomitant reduction in error and adverse events, andbetter patient care. Indeed, current clinical practice has anaccepted concept of the learning curve, whereby performanceof an individual operator gradually improves towards an asymp-totic level. Patients treated by an individual or team during thislearning phase are at higher risk of morbidity. This may occurwithout the patient’s knowledge of this phenomenon or fact.High reliability industries such as nuclear, oil, armed forces andaviation extensively train and certify their employees onsimulation-based models prior to real-world placements, andwill often test out new approaches or tactics in the simulationsetting first.19

Since its emergence in the late 1960s with the advent of‘Resusci-Anne’ for resuscitation training20 and the Harvey cardi-ology patient simulator to reproduce heart and breath sounds,21

the evidence for simulation in healthcare has been steadilygrowing, especially in the past 10 years. A systematic review oftechnology-enhanced simulation for HPE published in 201122

identified 609 studies comprising 35 226 learners. In compari-son with no intervention, simulation training was found to beconsistently associated with large effects for outcomes of knowl-edge, skills and behaviours, and moderate effects for patientoutcomes. Specific studies with regard to the impact of technicalskills simulation, in the setting of central line insertion, havereported sixfold reductions in catheter-related bloodstreaminfections, with concomitant cost-savings of almost $700 000 in

a single intensive care unit.23 A medical team training pro-gramme across 74 hospital sites in the Veterans HealthAdministration was associated with an 18% reduction in annualmortality, compared with a 7% decrease among 34 sites thathad not undergone the training programme.24 25

In addition to such convincing data, there are multiple aca-demic societies dedicated to simulation, unprecedented federalfunding, continuing advances in simulation technologies, andthe proliferation of simulation centres at medical/nursingschools and teaching hospitals, it is clear that simulation has thepotential and the means to revolutionise modern healthcare. In2011, the Association of American Medical Colleges (AAMC)published a survey answered by 90 medical schools and 64teaching hospitals, which revealed use of simulation by about90% of medical students, and similar numbers of residents(though only in postgraduate years 1–3).26 A variety of skillshave been taught through simulation, such as patient care, tech-nical skills, communication skills and leadership. Simulation usefor assessment purposes was predominantly to provide feed-back, and less so for certification or assessment of competence.

Describing simulation: a novel frameworkIn the existing literature, types of simulation are generally cate-gorised based on theirmodality, for example, standardised patients,mannequins, part or partial task trainers, or screen-based simula-tion.27–29 However, this method of classifying the types of simula-tion is not sufficient to accurately describe what any particularsimulation activity will entail. This is problematic for educatorssince without properly recognising the different dimensions of asimulation and only considering ‘mannequin or standardisedpatient’, they are unable to fully engage the needs and requirementsof the learner, and ultimately the individuals for whom they care.

We propose a novel framework to characterise simulations inthree dimensions, which allows us to more accurately describeany simulation activity (figure 2):▸ Scope,▸ Modality,▸ Environment.

ScopeThe scope refers to the extent of clinical encounter involved inthe simulation, which may include one or more modalities, andbe set in one or more environments. What scope to choose willdepend on the goals and objectives of the simulation as set bythe educators, illustrated in figure 3. Some examples of scopesare:

Figure 2 Novel framework for describing simulation activities usingthe three dimensions of simulation.

Figure 3 Goals and objectives determine the scope, modality andenvironment of the simulation.

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▸ Specific task/skill: deals with a single task such as intravenouscannulation, or a specific skill such as abdominalexamination;

▸ Partial/full procedure: a more expanded scope than a specificdiscrete task, and simulates more complex procedures. Oftenused in training of surgical procedures such as laparoscopicappendectomy on procedural trainers;

▸ Patient/scenario based: a simulation that entails a particularclinical scenario, such as ‘63-year-old man in a car accident’;

▸ Partial/full clinical pathway: whereas the other scopes coversan episode of a short time frame (putting in an intravenouscatheter, or the initial management of a car accident patient),clinical pathways span a longer time frame and have multiplesteps, in multiple settings.30

ModalityModality refers to the simulator itself, which can facilitate dif-ferent scopes of simulation, and can be used in a variety ofenvironments. Some examples of types of modality are:▸ Task/procedural trainers: such as a synthetic arm for IV inser-

tion or laparoscopic procedure trainers;▸ Mannequins: a life-like mannequin to represent a patient;▸ Standardised patients: trained actors to play patients;▸ Computer-based/digital simulation: a modality that itself

covers a wide spectrum. To list a few examples, there areapplications (or ‘apps’) on mobile devices that providescenario-based simulation for conceptual learning, computer-based programmes where the learner controls an avatar onscreen to treat virtual patients, virtual reality immersiveenvironments where the participant performs procedureswith haptic feedback, augmented reality where digital repre-sentations overlay live objects/patients with interactionsbetween the two worlds;31

▸ Mixed modality: an educator can combine multiple modal-ities into the same simulation.32 33 An example would be ascenario where the learners begin by taking the history on astandardised patient, then perform the physical examinationon a mannequin that represents the same patient, and per-forms procedure on a task trainer or in virtual/augmentedreality.

EnvironmentSimulations are most commonly carried out either in the sameenvironment as the actual clinical setting, such as the ward orthe operating room, or in a specialised simulation centre. Someexamples of such environments are (see online supplementaryappendix box 1):▸ In situ: simulations done in the actual clinical environment,

such as the emergency department or the operating room;

▸ Simulated/theatre based: this type of simulation is performedin a dedicated space for simulation, often a simulationcentre. The space mimics the environment it is simulating,such as a clinical examination room or the operating room;

▸ Ad hoc: done in an ad hoc location such as a classroom. Thisprovides the least amount of realism, but is offset by the factthat it is readily available;

▸ Virtual environments: digital simulation as a modality canoffer a variety of environments. Some programmes onlysimulate the patient or procedure with little additional envir-onmental details. Some systems can provide fully immersivevirtual environments with which learners can interact.

Realism in simulation: fidelityTo be able to interact and learn from simulation, the simulationmust behave in a realistic manner. It is important to recognisethat we view reality in three ways: physical, conceptual andemotional.34 In simulation, fidelity refers to how close the simu-lation is to reality, and it also encompasses these three dimen-sions (figure 4):▸ Physical fidelity: degree to which the simulation elements are

sensed as approximating visual, tactile, auditory and olfac-tory reality;

▸ Conceptual fidelity: degree to which the simulation proceedsin a plausible manner;

▸ Emotional/experiential fidelity: degree to which the simula-tion generates the feelings learners would expect in a similarreal situation.

These three dimensions of fidelity combine to produce a per-ception of realism for a learner, which may differ between lear-ners for the same simulation. Put another way, realism is afunction of the learner’s perception of the simulation, ratherthan a property of the simulation itself, and fidelity is whatsimulation educators provide, through the modality and theenvironment, for the learners to perceive (see figure 5).

ENGAGEMENT IN LEARNINGWhat is engagement in learning?In 1977, Howard Bowen, an American economist and formerPresident of the University of Iowa, published an article regard-ing the intended outcomes of higher education. The goals werebased on “…cognitive learning, effective development, and

Figure 4 The three dimensions of fidelity.

Figure 5 Dimensions of fidelity drive perception of realism.

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practical competence…[which]…may be achieved from bothformal instruction and extracurricular experience.”35 In essence,educational achievement is influenced by deliberate and sched-uled activities, as well as informal experiences. Faculty and stu-dents engage outside the classroom, as do the students witheach other; students have different levels of motivation, andimplement different learning strategies.36 37 This multifacetedarray of behaviours and experiences influences student out-comes, and may be broadly described as ‘engagement’.

As was stated in the introduction to this paper, engagement inlearning is exceedingly important and relevant to the educationof healthcare professionals. Simulation-based opportunities maybe considered an ideal link between deliberate learning activitiesand experiential learning in the clinical setting. Optimally,healthcare simulations focus on the engagement of the learnerthrough activities that simulate clinical situations in order tomaximise students’ interest, attention and learning. Whilethought to be physically, cognitively and emotionally engaging,the extent to which healthcare simulation embraces this role isunknown.

The dimensions of engagement in learning and simulationIn 2004, Fredricks et al38 offered a definition of engagement,comprising behavioural, emotional and cognitive dimensions(adapted to figure 6). Although their work focused on K-12applications, the concept is attractive for HPE, and specificallythe role of simulation.

Behavioural engagementThis considers the learners’ involvement in academic activities,which may be divided into three parts: positive conduct (follow-ing rules), involvement in learning (behaviours related to con-centration, attention, effort and contributing to group sessions)and participation in other related activities (administration andextracurricular).

With respect to simulation in HPE, it is critical to provide anoverview of the teaching session, learning objectives and modesof assessment. It is only with this educational framework that alearner can follow rules, and be positively involved in learningthrough simulation. More explicitly, Rudolph et al39 have devel-oped a role for presimulation briefing, in order to create a psy-chologically safe context for learning, a so-called ‘safecontainer’. This enables learners to actively engage in the simu-lation scenario, despite the possibility of unrealistic aspects ofthe simulation, potential threats to their professional identity orfrank discussion of mistakes, during the debriefing period. Thismay also be called the ‘learning contract’.

Engaging in a simulated learning environment, to act as ifthings were real, is hard. The instructor attempts to provide suf-ficient fidelity in order to properly engage the learners and draw

them in: conceptual fidelity through a plausible script (or narra-tive), physical fidelity through appropriate modality and envir-onment, and emotional fidelity through a combination of theother aspects. At the same time, the learners must be willing toplay an active role, and as such, there is the creation of a fictioncontract—an agreement to suspend disbelief and accept the pre-sented realism of the simulation—between the instructor andeach learner, and between the learners themselves.40 It is this‘fiction contract’ that translates the perceived realism intobehavioural engagement.

Emotional engagementThis comprises the learners’ attitudes, interests and valuestowards learning, as well as the emotions encountered duringthe learning activities. Affective reactions (interest, boredom,anxiety, happiness) are those that are felt about the activity,41

and evoked emotional reactions are emotions that are evokedfrom the activity once a learner is already engaged (eg, anengrossing film with a strong narrative that makes the studentsfeel sad about the characters, or a simulation scenario that leadsthe learner to feel stressed in a critical situation).

An example of emotional engagement is an empiric study thatcharted and compared the stress level and physiological arousalof senior medical students between simulated history takingencounter, a simulated breaking bad news encounter and thebaseline.42 The students’ heart rates and self-reported stresslevels were higher in both of the simulations when comparedwith the baseline, indicating heightened stress levels when theyperformed the activity, which suggests a heightened emotionalengagement during the simulation. How may this be useful inHPE? Some research theorises that emotions—both positive andnegative—can influence information retrieval. It has furtherbeen postulated that the activation of an emotion enhances theretrieval of memory that was stored in a similar state.43 44 Wecan potentially leverage simulation’s ability to evoke emotionsby designing simulations that will elicit the feelings that arelikely to be encountered in real life, so that students will experi-ence those emotions and encode the knowledge concurrently.Coming across similar situations later on in clinical settings, theactivated emotions could potentially allow for a better retrievalof the stored knowledge.

Cognitive engagementFredricks et al divided this into psychological (motivationalgoals and self-regulated learning, relative to effortful compre-hension and mastery of skills) and cognitive (metacognition andapplication of learning strategies) components.

Brydges and colleagues extensively reviewed the literature onself-regulated learning in simulation-based training. Theydefined self-regulated learning as an active learner who hasdeveloped a set of processes for managing the achievement oflearning goals, and compared outcomes to those of supervisedtraining with an instructor present.45 Unsupervised interven-tions were associated with poorer post-training scores. Overall,there were very few studies aimed at clarifying how trainees’self-regulatory processes can be supported in simulation. Thelead author states in an earlier published article that “…it isimperative to stop equating ‘self-regulation’ with ‘learning onone’s own’.”46 It is essential to create the conditions to supportself-regulated learning, such as a self-guided curriculum, oppor-tunities to use other resources (eg, videos, demonstrations,written descriptions), and appropriate feedback and debriefing.Understanding students’ motivations (including long-term careerFigure 6 The three dimensions of engagement.

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aspirations) and providing related rationale also helps supportlearners to self-regulate effectively.

An example that ties in emotional and cognitive engagementwould be a procedural skills simulation using a virtual realitylaparoscopic simulator by a surgical resident. There are multipletasks, levels and difficulty settings within the simulator and itcan be confusing for the learner in terms of understanding theirown acquisition and progression of laparoscopic skills. Withoutbenchmark levels of skill to achieve the learner has no ideawhen to proceed to the next level of difficulty or task, poten-tially causing frustration and reducing motivation. The develop-ment of a proficiency-based virtual reality laparoscopicsimulator curriculum, designed in a stepwise fashion, with pre-defined benchmark scores (derived from the performance ofexperienced laparoscopic surgeons) at each level provides appro-priate increasing degree of challenge for the learner, making theactivity more interesting, leading to sustained attention andeffort. This supports the learner’s innate drive for mastery byproviding feedback of their advancing performance throughdeliberate practice. Furthermore, if this educational activity waspresented prior to initiation of clinical training in laparoscopicprocedures, it could offer additional motivation (eg, the learnersees this as a stepping stone to becoming a great surgeon, or toensure he/she is proficient before training on real clinicalsituations).

A FRAMEWORK FOR ENGAGED LEARNING IN SIMULATIONIN HPEThe concept of immersive educational engagement thus meanscreating simulation encounters that possess physical, emotionaland conceptual fidelity. Simulations must also build effectivenarratives, which can bring the simulation encounter closer tothe complexity of the real world, leading to better learnerengagement. Not only would such simulations be better forteaching the procedural and technical aspects of healthcare but,through better engagement, may increase the learner’s ability tocare, empathise and comfort their patients. So, how do we dothis?

The fundamental aspect of any educational activity is toacquire knowledge, skills and attitudes, and translate them intoacceptable performance. As mentioned, in HPE, this is currentlyperformed through a milieu of deliberate activities, and clinicalimmersion of variable frequency and intensity. In order forHPE, with specific regard to simulation, to have an impact onclinical performance, it is clear that the learner, faculty memberand all other participants must be engaged in the activity, ideallyto the same level of engagement that would occur in the clinicalsetting. This is dependent on the three dimensions already men-tioned (cognition, behaviour and emotion) which are allmediated by the learner’s response and interaction with thesimulation activity. The learner’s engagement is also impactedby the degree of perceived realism of the simulation-based exer-cise, which is a function of the level of simulation fidelity. Aspreviously discussed, the fidelity of a simulation event can bebroadly described in physical, emotional and conceptual terms,though to be more specific to simulation-based learning, wouldbe ascribed to the modality or tools used, the environment inwhich they are used, and the scope and conceptual map (orpathway) of the simulation.

For example, a nursing educator wishes to teach nursing stu-dents how to manage a patient in the postanaesthesia care unit(PACU). The required knowledge, skills and attitudes may bemapped from the syllabus of the training programme, and simu-lation can be used to translate these activities into performance

in the clinical setting. To begin with, the educational goals andobjectives of the activity need to be defined (ie, managing adeteriorating patient postcardiac transplant in the PACU), whichleads to the determination of the scope of the simulation (ie, ascenario-based simulation that looks at the entire patient, andnot only at a specific procedure). Then, the different dimensionsof fidelity need to be considered (physical, conceptual and emo-tional). The educator determines how ‘real’ the three dimen-sions need to help the learners achieve the goals and objectives(eg, high conceptual, moderate physical and moderate emo-tional). This specification then helps to prescribe how to achievethe target levels of fidelity: what modality (ie, high-feature/low-feature mannequin, or perhaps computer), what environment(ie, in situ, or a simulated PACU setting) are needed. A moredetailed narrative can then be formed, filling in the detailsregarding the patient scenario, case notes, vital signs, emotionaltone. It is the coalescence of the physical, emotional and con-ceptual fidelities that lead to the perception of realism by thelearner. An important point to note here is that the degree offidelity is not directly proportional to the degree of realism;indeed low-physical fidelity mannequins and environments canbe perceived to be exceedingly realistic if the conceptual andemotional fidelities are high.

Once adequate realism is achieved, it is a function of thelearner, the educator and other members of the team to trans-late this into an engaging experience. As mentioned earlier,Rudolph et al considered this as the fiction contract, though wewould caution with the exclusive use of this concept, as it tendsto propose a single transaction with regard to engagement. Theengagement with the simulation is an ongoing process, whichbegins at presimulation, during the initial brief, right through tothe exercise, and its debrief. Optimal engagement occurs when(1) educators deliberately integrate the knowledge, skills, atti-tudes and motivations of the learners when creating and facili-tating the simulation, and when (2) the fidelity of the simulationis sufficient to allow the learner to suspend disbelief to fullyengage in the learning activity, which leads to the desired levelof clinical performance. Figure 7 encapsulates the conceptsdescribed: realism is a product of the dimensions of simulationand fidelity, which is a necessary component for learnerengagement.

How to engage optimally?Unfortunately, our current HPE system is often not conduciveto this translation of knowledge, skills and attitudes into per-formance. Why is that? We will forward a hypothesis: deficit inlearners’ engagement often relates to the system’s inability totap into emotional triggers generated by our evolutionary pastand needs. The evolutionary sieve of the past 200 000 years hascarved our physiology to respond to tools, methods, cognitivestrategies and behaviour that are conducive to an enhanced sur-vival. We play, we play act, we invent and we convert survivalclues into easily shared and emotionally charged symbols toenhance the group’s survival (and thus our own). This is gener-ally referred to as art.47

Art embodies the clues and apprenticeship necessary for oursurvival.48 49 Using art, we constantly generate what could becalled a theatre of survival and learning in which we developengaging techniques, devices and procedures that allow us toenhance survival, as well as experience and resolve difficult,unusual and threatening situations. Music transcends culturesand eras, for example, because of its ability to solidify thegroup’s cohesiveness;50 51 narratives are ubiquitous for theyallow us to simulate, disentangle and resolve unusual and

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challenging social situations (as demonstrated by standardisedpatient simulations);52 paintings points to visual evolutionaryclues related to reproduction (such as symmetry);53 dance high-lights one’s mastery of difficult and complex movements (gener-ally referred to as gracefulness), and digital art points to clueson how to navigate a complex and technologically layeredworld.

Art embodies effective evolutionary tactics.54 Through themillennia, these tactics have evolved into highly efficient andeasily combined symbolised forms, practices and rituals, soeffectual in fact that the best ones trigger pleasurable physio-logical responses. Our hypothesis is that we have labelled theseevolutionary-based responses as beauty.

If we are to truly engage learners in such difficult assignmentsas understanding and responding effectively to simulatedmedical challenges, we must recognise that the evolution carvedsurvival mechanism we call beauty is as important in the cre-ation and development of simulations, as the actual medicalinformation and material we want the learner to acquire.

Beauty, we believe, is a proxy for emotional and cognitiveengagement; beauty is evidence that the limbic system has beenactivated; beauty is the conduit to a better, more effective,longer lasting learning development; beauty is a key constructof fidelity.

What does it mean, then, in terms of medical simulations? Itmeans creating simulations that allow the learner to develop hisor her medical skills, knowledge and abilities by searching for,discovering and experiencing visual, auditory, and cognitive evo-lutionary clues, paths and tactics. It means creating simulationsthat focus on the actual medical task to be completed, and onhow to best physically, cognitively and aesthetically engage insolving that task. It means, more specifically, that we should ask,as a dancer would, what are the best, most productive, most effi-cient and most graceful movements one should use to solve asimulated medical task and challenge? That we should wonder,as a musician would, what is the most melodious auditory envir-onment one can create to enhance learning of a medical ability?That we should wonder, as Picasso did when he paintedGuernica, what is the most engaging visual representation onecan produce to rationalise complex problems or situations (warin his case; medical knowledge in ours) into clear, emotionallyengaging, information rich forms?

Only when we integrate the concepts of beauty and aestheticsinto health professions simulation education can we truly, opti-mally engage our learners (figure 8).

Engaged learning in simulation: the futureAs technology continues to advance, simulations—especiallycomputer and virtual simulations—will become more than justscreen based. As such, it is ever more important to incorporatevisual, auditory and tactile elements when creating simulationsso that we can generate truly aesthetic fidelity (rememberingthat aesthetically engaging means not just ‘nice’ or ‘pleasant’ buta compelling narrative and evolutionary-based triggers), in orderto fully engage the learners.

Consider how our framework may be used for the develop-ment of a serious game or virtual world learning experience.The concepts are similar, such that the syllabus will determinethe baseline knowledge, skills and attitudes, and the clinicalneed will define the level of performance to be achieved. Thedigital nature of this modality—for example, virtual reality—will allow us to consider, and create, aesthetically engagingphysical and emotional environments (through the digital ren-dering of sight, sound and touch) that are key to an engagedlearning experience. Given the digital foundation of this tech-nology, expansive scopes can be more easily done, such as amass disaster event with casualties needing to be airlifted (whichwould be difficult in a non-virtual setting). The conceptual andemotional fidelity of the simulation will depend on a plausiblescript that covers all actors and events within the scenario, andall sequence and consequences of actions performed by the lear-ners. Taking all of this, as well as accounting for the skills, atti-tudes and motivations of the learners when developing thesimulation, will create an optimally engaging simulation, whereaesthetics will further amplify the behavioural, emotional andcognitive engagement.

Optimal engagement: beyond simulationEngagement in learning is vital not only in simulation, but in allother instructional methods in HPE, such as classroom, appren-ticeship and informal encounters. With engagement as the goal,we can expand on the described framework on how to opti-mally engage learners, and apply it for the other methods. The

Figure 7 Engagement in simulation as a product of the dimensionsof simulation and fidelity.

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key is in distilling each instructional method to its core essence,its alignment—‘fidelity’ in simulation—and identifying thedimensions that drives it—‘conceptual, physical, emotional’ (seefigure 9).

CONCLUDING REMARKSThis white paper presents an overview of the current status andrecommends future directions to improve engagement in health-care simulation, through the development of a conceptual

Figure 8 Framework for optimalengagement in simulation.

Figure 9 Model for optimal engagement in learning across instructional methods in health professions education.

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framework which may be applied to all forms of simulationactivities. The first part of the framework provides a novelapproach to describing the types of simulation by deconstruct-ing a simulation activity into three core components (scope,modality and environment). Through these components, theeducator delivers the three dimensions of fidelity (physical, con-ceptual and emotional) for learners to perceive. This perceptionof realism by the learner helps to achieve engagement (beha-vioural, emotional and cognitive), in order to translate delibe-rately taught knowledge, skills and attitudes into clinicalcompetence and performance. There is additional focus on therole of aesthetics, serious gaming and virtual worlds, which mayenable closer assimilation to real-world experiences. The driveforward is to use the suggestions and discussions outlined in thispaper, to implement collaborative and systematic efforts to posi-tively impact the level of engagement in healthcare simulation.Doing so, we believe, will ultimately enhance the quality ofhealthcare education and thus healthcare outcomes.

Author affiliations1Steinberg Centre for Simulation and Interactive Learning, Faculty of Medicine,McGill University, Montreal, Quebec, Canada2Faculty of Medicine, Department of Emergency Medicine, McGill University,Montreal, Quebec, Canada3McGill University, Montreal, Quebec, Canada4Division of Emergency Medicine, McMaster University, Hamilton, Ontario, Canada5Department of Surgery, Academic Medical Centre of Amsterdam, The Netherlands6Department of Educational and Counselling Psychology, McGill University, Montreal,Quebec, Canada7The University of Texas at Arlington College of Nursing and Health Innovation,Arlington, Texas, USA8Innovation in Learning, Los Altos Hills, California, USA9Department of Orthopaedic Surgery, Karolinska University, Stockholm, Sweden10Ubisoft Inc, Montreal, Quebec, Canada11Serious Games Institute, University of Coventry, Coventry, UK12Department of Surgery, Stanford University, Stanford, California, USA13Department of Contemporary Dance, Concordia University, Montreal, Quebec,Canada14School of Computing Science, McGill University, Montreal, Quebec, Canada15Department of Surgery, Faculty of Medicine, McGill University, Montreal, Quebec,Canada

Funding This research was funded through an unrestricted donation from theBlema and Arnold Steinberg Foundation.

Twitter Follow Wayne Choi @WCmed, Teresa Chan @TChanMD, Marlies Schijven@marliesschijven and Rajesh Aggarwal @docaggarwal

Competing interests RA is a consultant for Applied Medical.

Provenance and peer review Commissioned; externally peer reviewed.

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