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Grant: Alliance Grants

York University

$49,991.00

Using big data to chart workplace learning during COVID-19_x000d_ _x000d_

EF 2020-21

Résumé
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.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
555168-2020
Name nom
Rosenbaum, R Shayna
Department département
Psychology
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
49991
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1210
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Psychology
Area of application fr
Psychologie
Research subject code
6307
Research subject group en
Psychology
Research subject group fr
Psychologie
Research subject en
Cognitive science -- other
Research subject fr
Science cognitive -- autres
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
Using big data to chart workplace learning during COVID-19_x000d_ _x000d_
Keyword
NSERC
Application summary
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.