After-Action Review and team learning from errors
Overview & Synopsis
This qualitative research project attempts to understand how a team can develop ways to learn from its experience in a complex world using the After-Action Review (AAR), a learning technology initially designed to accelerate training effectiveness in the U.S. army in the 1980’s, and which has, since, spread across many organizations, including businesses in the private sector. Articulating Argyris and Schön’s theory of action framework with AAR suggests that a team may deepen its learning capabilities through skills development via meta-learning without outside intervention. The research question is: How can a team develop double-loop learning skills by practicing After-Action Review? Echoing the complex, high-stakes situations which the military and first-responder units face in their respective trade, the research field is an Executive Committee at the helm of a medium-sized company dealing with an adverse economic environment and about to embark on a business model transformation. The research design is a holistic, instrumental, and revelatory single-case study of an ExCo that practices, in autonomy, the discipline of AAR on itself with deliberation and professionalism. The longitudinal approach, and data collection process along three dimensions (three sets of ExCo member interviews, observations/recordings of ten ExCo meetings, and observations/recordings of nine follow-up AAR meetings) across a 12-month period yields stimulating data which are considered within a critical realist epistemological framework (empirical, actual and real domains) to identify underlying mechanisms that contribute to explaining how and why, and under what conditions, double-loop learning skills may, or may not, be developed by a team practicing AAR.
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Document Information
| Document Title | After-Action Review and team learning from errors |
|---|---|
| Author / Organization | Thomas Misslin |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2026 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-236875 |
| Original Source Link | Visit Source Page on hal.science » |