Using big data to chart workplace learning during COVID-19

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The COVID-19 pandemic has led to an unprecedented global disruption, costing lives and jobs. Companies employing frontline workers must balance health and safety with maintaining productivity to survive and thrive in an unpredictable economic climate. This picture is complicated by the need for rapid learning in new, redeployed, and longstanding employees. How is workplace learning impacted by the COVID-19 pandemic and how can it be optimized as the pandemic continues to evolve? To answer these questions, we will combine our expertise in the cognitive neuroscience of memory with mathematical modeling of big data to characterize the role of different learning strategies on uptake of COVID-19 health and safety information as well as company-specific information to help companies maintain operational resilience during the pandemic. We will amplify existing partnerships with Axonify, a leader in online training of frontline workers (e.g., grocers, taxi drivers) in over 150 countries, and the Public Health Agency of Canada (PHAC), which is responsible for guiding the national COVID-19 health and economic response. In response to the COVID-19 crisis, Axonify developed daily, bite-sized training material on best practices in pandemic safety, wellness, and working from home. Through Axonify, we have access to learning data in over 2.8 million employees related to COVID-19 (e.g., social distancing) and unrelated to COVID-19 (e.g., new products) rolled out during the pandemic, along with learning data collected prior to COVID-19 and that will be collected as the economy reopens. We will conduct modeling and statistical analyses of learning strategy and training content in the context of employer characteristics, such as company type and geographical location, and employee characteristics, such as date of hire. In doing so, we will be able to determine the ideal combination of learning strategies and content to maximize employee learning and retention. PHAC will use our findings together with COVID-19 trend analysis data to inform government strategies to increase public adherence to existing protective measures and adoption of new measures, such as mask-wearing.