Performance and mental workload dynamics during in-person and virtually-based remote learning of action sequences
PRACTITIONER SUMMARY: Although remote learning is important for applications such as tele-health and tele-robotics, it is unclear how it differs from in-person learning. This work examines performance and mental workload evolution throughout in-person and remote learning. Both learning modalities attenuated mental workload while performance was enhanced albeit more slowly for in-person learning.
Authors
- James Purtilo
- Calvin Lu
- Hyuk Oh (ORCID: https://orcid.org/0000-0003-3328-0558)
- Rodolphe J. Gentili (ORCID: https://orcid.org/0000-0001-9171-8525)
- Matthew J. Reinhard (ORCID: https://orcid.org/0000-0002-3040-356X)
- Ryan C. Brewster (ORCID: https://orcid.org/0000-0002-0211-5632)
- J A Reggia
- Alexandra A. Shaver
- Immanuel Samuel
- Elizabeth M. Kerman
Institutions
- Henry M. Jackson Foundation (US)
- Georgetown University (US)
- Department of Veterans Affairs (AU)
- Artificial Intelligence in Medicine (Canada) (CA)
- University of Maryland, College Park (US)
Publication Details
- Journal
- Ergonomics
- Published
- 2026-04-16
- DOI
- https://doi.org/10.1080/00140139.2026.2614629
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Veterans Affairs