Introduction: E-learning is widely used in medical education. To maximize the potential of E-learning tools, every effort should be made to encourage adoption by optimizing usability. We created Learning Moment (LM), a web-based application that integrates principles of asynchronous learning and learning portfolios into a platform on which students can document and share learning experiences that occur during clinical work. We sought to evaluate the usability of LM and identify features that optimize adoption by users.

Methods: We implemented LM in August 2016 at a busy, urban, tertiary care emergency department that hosts an emergency medicine residency, robust third and fourth year medical student clerkships as well as a physician assistant student rotation. We conducted a single-center, mix-methods study using the System Usability Scale (SUS) questionnaire and qualitative interviews. We sent e-mail invitations with subsequent reminders to all students who rotated in our emergency medicine clerkship from August 2016 to April 2017 to complete the SUS questionnaire anonymously and to participate in qualitative interviews. We employed purposive sampling to recruit students who used LM during their rotation to participate in our qualitative interviews. We conducted semi-structured interviews with 13 participants (10 individual interviews and one 3-person group interview) between January and March 2017 using an ethnographic approach and utilized a general inductive method to analyze and code for potential themes.

Results: Thirty of the seventy students invited to participate completed the SUS questionnaire (Response rate of 42.8%). The mean SUS score is 80.9 (SD 18.2, 80% CI 76.5 – 85.3). The internal consistency of the responses achieved the Cronbach’s Alpha of 0.95. The participants stressed the importance of the following in the adoption of LM: maximal simplicity and usability, compatibility with learning preferences, and department-wide acceptance and integration.

Conclusion: The overall perceived usability of LM was high. Our qualitative data revealed important implications for future designers to maximize adoption: include target users in every step of the design and development process to maximize simplicity and usability; build features that cater to a diversity of learning preferences; involve the entire department and find ways to incorporate the tool into the educational infrastructure and daily workflow.

Introduction: Experiential learning is crucial for the development of all learners. Literature exploring how and where experiential learning happens in the modern clinical learning environment is sparse. We created a novel, web-based educational tool called “Learning Moment” (LM) to foster experiential learning among our learners. We used data captured by LM as a research database to determine where learning experiences were occuring within our emergency department (ED). We hypothesized that these moments would occur more frequently at the physician workstations as opposed to the bedside.

Methods: We implemented LM at a single ED’s medical student clerkship. The platform captured demographic data including the student’s intended specialty and year of training as well as “learning moments,” defined as logs of learner self-selected learning experiences that included the clinical “pearl,” clinical scenario, and location where the “learning moment” occurred. We presented data using descriptive statistics with frequencies and percentages. Locations of learning experiences were stratified by specialty and training level.

Results: A total of 323 “learning moments” were logged by 42 registered medical students (29 fourth-year medical students (MS 4) and 13 MS 3 over a six-month period. Over half (52.4%) intended to enter the field of emergency medicine (EM). Of these “learning moments,” 266 included optional location data. The most frequently reported location was patient rooms (135 “learning moments”, 50.8%). Physician workstations hosted the second most frequent “learning moments” (67, 25.2%). EM-bound students reported 43.7% of “learning moments” happening in patient rooms, followed by workstations (32.8%). On the other hand, non EM-bound students reported that 66.3% of “learning moments” occurred in patient rooms and only 8.4% at workstations (p<0.001).

Conclusion: LM was implemented within our ED as an innovative, web-based tool to fulfill and optimize the experiential learning cycle for our learners. In our environment, patient rooms represented the most frequent location of “learning moments,” followed by physician workstations. EM-bound students were considerably more likely to document “learning moments” occurring at the workstation and less likely in patient rooms than their non EM-bound colleagues.

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