Annual mandatory eLearning modules are frequently used to ensure compliance among all employees in large organizations. These eLearning modules are typically created in software such as Articulate Storyline, Articulate Rise, or Adobe Captivate, and they disseminate essential information that all employees must understand and adhere to. The modules serve as a tool for recording and documenting compliance and comprehension. Due to technical limitations of software and learning management systems (LMS), eLearning modules often rely on lower-level learning, such as a passive approach followed by a multiple-choice quiz to assess understanding. In healthcare, research has demonstrated the learning benefits of simulation-based education (SBE), often using manikins and standardized patients in a lab setting, followed by a debriefing or discussion to achieve higher levels of learning (Cook et al., 2018). However, implementing annual organization-wide training is challenging due to limited resources, space, and time. While some screen-based simulations, such as 3D animated environments or virtual reality (VR), can closely replicate a lab-based experience, they can be costly, require technical facilitation, and there is limited evidence that they lead to improved skills over other methods of learning due partially to an increase in cognitive load (Sweller et al., 2019).
Research suggests that effective simulation does not need to exactly replicate reality, but rather accurately represent the most relevant real-world cues and elements, supporting a low-fidelity approach that prioritizes the environmental elements most critical to the learning objectives (Tun et al., 2015). One method of managing cognitive load within SBE is to apply representational scaffolding (RS) to address the cognitive demands associated with a learning objective's focus (Bauer et al., 2022). RS in screen-based simulation enables learners to practice at a lower level of fidelity, thereby building the skills needed for more cognitively demanding simulations, such as what they will experience in real-life situations.
Additionally, tracking how employees engage with environmental cues, like signage, is particularly challenging in large clinical settings. In these environments, data collection often relies on self-reported compliance or direct observation and is typically limited to small sample sizes. However, by using learning analytics and SBE in eLearning modules, it is possible to assess the behavior of all employees in a clinical environment. This approach offers a more comprehensive understanding than traditional methods can provide in real-world settings.
This paper reviews how we developed a mandatory compliance eLearning module for a large healthcare organization using Articulate Storyline, drawing on learning theories that follow best practices for eLearning and simulation. The eLearning module focuses on infection prevention and educates clinical staff on standard precautions to minimize pathogen transmission and protect patients, visitors, and staff. The module delivers passive information on the guidelines for standard precautions in infection control, which ensure that essential protection methods are used to minimize the risk of infection spread, such as hand hygiene, use of personal protective equipment (PPE), and proper cleaning and disinfection of contaminated surfaces. Furthermore, the module discusses expanded precautions, which are extra protective measures designed to prevent the spread of highly infectious or significant pathogens; these include additional PPE, specific hand hygiene practices, and improved cleaning techniques.
We revised our annual mandatory infection prevention module to integrate a game-based simulation, adopting a more constructive educational approach that closely follows the ICAP framework (Chi & Wylie, 2014). The module was developed in Articulate Storyline and incorporated RS for essential elements directly related to the learning objectives, such as signage, within low-fidelity graphics.
Data were collected from 7,891 employees in FY24. The learning analytics indicated that four of the six signs exhibited lower adherence to proper donning procedures and revealed that the images on these signs were presented vertically out of sequence. These findings suggest that employees may have relied on the image sequence rather than proper donning and doffing procedures, contributing to the identified deficiencies. For signs with incorrect image sequencing, learners only correctly donned PPE 51.20% and 66.10% of the time when first encountering the rooms. However, after exposure to feedback from the initial rooms, adherence improved to 74.82% and 76.65%, suggesting a learning effect, yet learners still followed the incorrect sequence of the signs. In contrast, rooms with signs displaying the correct donning order had higher initial adherence rates, at 83.12% and 83.68%.
Furthermore, there was a notable lack of guidance within the rooms regarding the appropriate procedures for doffing PPE and performing hand hygiene before exiting. This gap resulted in poor compliance in the two rooms requiring doffing procedures, with adherence rates of 68.35% and 53.31%, respectively. Similarly, hand hygiene compliance varied, with only 68.07% adherence in the first room. However, a clear improvement was observed in subsequent rooms, with compliance increasing to 92.26%—96.91%, indicating immediate learning from the simulation.
The learning analytics indicated a critical need for enhanced signage to reinforce proper donning and doffing procedures and to promote consistent adherence to infection prevention protocols. The signs were revised to provide a precise sequence for donning PPE and address additional user needs based on further user feedback. Additionally, supplementary signage was created to instruct employees on proper PPE doffing in designated areas.
The updated signage was subsequently incorporated into the 2025 annual mandatory eLearning module. Data were collected from N = 8,853 employees in FY25. Results show substantial improvements in PPE donning accuracy across all six simulated rooms, with increases ranging from 8% to 25%. Specifically, Room A showed an 18% improvement, Room B an 8% improvement, Room C a 10% improvement, Room D a 17% improvement, Room E an 18% improvement, and Room F a 25% improvement in proper donning procedures.
Hand hygiene compliance also improved in most rooms, with Room A showing a 14% increase, followed by modest gains in Rooms B, C, E, and F (ranging from 2%–4%), while Room D showed a 1% decrease. The implementation of dedicated cleaner signage resulted in a 10% improvement in environmental cleaning procedures, while improvements to doffing signage led to an 11% increase in proper PPE removal techniques.
Additionally, simulation engagement metrics showed improved comprehension following the signage updates, with 15% fewer employees needing multiple attempts to complete the simulation in FY25 than in FY24. This reduction in repeat attempts suggests that the enhanced clarity of the signage enabled learners to grasp proper infection prevention procedures more effectively during their initial exposure.
This work was made possible through the collaboration and dedication of colleagues at Dartmouth Health. I would like to extend my sincere gratitude to Stephanie Casale, MPH, BSN, RN, CIC, Manager of CHIP, Quality Assurance & Safety, for her expertise in infection prevention and for providing critical insight into clinical implementation. Special thanks to Logan Stahler, MEd, Senior Learning Experience Designer, and Matthew Haselton, MS, Learning Experience Designer, for their support in module development, analytics, and data visualization.
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