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Medical education escape rooms are emerging as a viable technological resource for pedagogy-first, learner-centric educational activities. This work presents the evaluation results of the first flipped classroom implementation in medical education, thus utilizing a mobile-driven augmented reality (AR) escape room. A total of 21 first-year medical students attended a flipped classroom educational activity that aimed to acclimate the students with the workflows of basic life support. Knowledge acquisition and user perceptions were evaluated. Knowledge acquisition was evaluated with an ad hoc relevant instrument at three timepoints: (a) baseline at recruitment, (b) preclass after students had prepared for the episode, and (c) after class. Learner perceptions about the activity and the AR escape room were recorded at the activity's end using a previously designed evaluation instrument. The results demonstrated sufficient knowledge acquisition only after completing the whole educational activity, while learners found the experience interesting, and the AR escape room challenging, thus reflecting an activity that was well formulated in structure and content. The challenges identified were the limited out of class collaboration capacity of the digital application and the highly gamified approach that at points counteracted the educational scope of the activity. Overall, these positive initial results demonstrate the potential of collaborative, escape based, activities for self-directed, learner-centric medical education. [ABSTRACT FROM AUTHOR]

BackgroundThe role of emotion is crucial to the learning process, as it is linked to motivation, interest, and attention. Affective states are expressed in the brain and in overall biological activity. Biosignals, like heart rate (HR), electrodermal activity (EDA), and electroencephalography (EEG) are physiological expressions affected by emotional state. Analyzing these biosignal recordings can point to a person’s emotional state. Contemporary medical education has progressed extensively towards diverse learning resources using virtual reality (VR) and mixed reality (MR) applications. ObjectiveThis paper aims to study the efficacy of wearable biosensors for affect detection in a learning process involving a serious game in the Microsoft HoloLens VR/MR platform. MethodsA wearable array of sensors recording HR, EDA, and EEG signals was deployed during 2 educational activities conducted by 11 participants of diverse educational level (undergraduate, postgraduate, and specialist neurosurgeon doctors). The first scenario was a conventional virtual patient case used for establishing the personal biosignal baselines for the participant. The second was a case in a VR/MR environment regarding neuroanatomy. The affective measures that we recorded were EEG (theta/beta ratio and alpha rhythm), HR, and EDA. ResultsResults were recorded and aggregated across all 3 groups. Average EEG ratios of the virtual patient (VP) versus the MR serious game cases were recorded at 3.49 (SD 0.82) versus 3.23 (SD 0.94) for students, 2.59 (SD 0.96) versus 2.90 (SD 1.78) for neurosurgeons, and 2.33 (SD 0.26) versus 2.56 (SD 0.62) for postgraduate medical students. Average alpha rhythm of the VP versus the MR serious game cases were recorded at 7.77 (SD 1.62) μV versus 8.42 (SD 2.56) μV for students, 7.03 (SD 2.19) μV versus 7.15 (SD 1.86) μV for neurosurgeons, and 11.84 (SD 6.15) μV versus 9.55 (SD 3.12) μV for postgraduate medical students. Average HR of the VP versus the MR serious game cases were recorded at 87 (SD 13) versus 86 (SD 12) bpm for students, 81 (SD 7) versus 83 (SD 7) bpm for neurosurgeons, and 81 (SD 7) versus 77 (SD 6) bpm for postgraduate medical students. Average EDA of the VP versus the MR serious game cases were recorded at 1.198 (SD 1.467) μS versus 4.097 (SD 2.79) μS for students, 1.890 (SD 2.269) μS versus 5.407 (SD 5.391) μS for neurosurgeons, and 0.739 (SD 0.509) μS versus 2.498 (SD 1.72) μS for postgraduate medical students. The variations of these metrics have been correlated with existing theoretical interpretations regarding educationally relevant affective analytics, such as engagement and educational focus. ConclusionsThese results demonstrate that this novel sensor configuration can lead to credible affective state detection and can be used in platforms like intelligent tutoring systems for providing real-time, evidence-based, affective learning analytics using VR/MR-deployed medical education resources.

BackgroundSince their inception, virtual patients have provided health care educators with a way to engage learners in an experience simulating the clinician’s environment without danger to learners and patients. This has led this learning modality to be accepted as an essential component of medical education. With the advent of the visually and audio-rich 3-dimensional multi-user virtual environment (MUVE), a new deployment platform has emerged for educational content. Immersive, highly interactive, multimedia-rich, MUVEs that seamlessly foster collaboration provide a new hotbed for the deployment of medical education content. ObjectiveThis work aims to assess the suitability of the Second Life MUVE as a virtual patient deployment platform for undergraduate dental education, and to explore the requirements and specifications needed to meaningfully repurpose Web-based virtual patients in MUVEs. MethodsThrough the scripting capabilities and available art assets in Second Life, we repurposed an existing Web-based periodontology virtual patient into Second Life. Through a series of point-and-click interactions and multiple-choice queries, the user experienced a specific periodontology case and was asked to provide the optimal responses for each of the challenges of the case. A focus group of 9 undergraduate dentistry students experienced both the Web-based and the Second Life version of this virtual patient. The group convened 3 times and discussed relevant issues such as the group’s computer literacy, the assessment of Second Life as a virtual patient deployment platform, and compared the Web-based and MUVE-deployed virtual patients. ResultsA comparison between the Web-based and the Second Life virtual patient revealed the inherent advantages of the more experiential and immersive Second Life virtual environment. However, several challenges for the successful repurposing of virtual patients from the Web to the MUVE were identified. The identified challenges for repurposing of Web virtual patients to the MUVE platform from the focus group study were (1) increased case complexity to facilitate the user’s gaming preconception in a MUVE, (2) necessity to decrease textual narration and provide the pertinent information in a more immersive sensory way, and (3) requirement to allow the user to actuate the solutions of problems instead of describing them through narration. ConclusionsFor a successful systematic repurposing effort of virtual patients to MUVEs such as Second Life, the best practices of experiential and immersive game design should be organically incorporated in the repurposing workflow (automated or not). These findings are pivotal in an era in which open educational content is transferred to and shared among users, learners, and educators of various open repositories/environments.