Abstract
Failure learning is a complex problem and consequently it is studied using different approaches. This chapter presents 13 ways to think about failure learning: categorization of factors into opportunity, ability, and willingness; the failure–error mismatch model; error reporting, error classifications, and the Swiss cheese model; two traditional learning models that are used for failure learning—learning curves and sources of learning (internal versus external and automatic or deliberate); and three partly overlapping willingness factors: culture, climate, and psychological safety. Two other important aspects in many failure-learning settings are the role of regulations and compliance to regulations.
| Original language | English |
|---|---|
| Title of host publication | Everybody Fails But Not Everybody Learns : Why is it so Hard to Learn from Failures? |
| Editors | Kristina Dahlin, You-Ta Chuang |
| Number of pages | 26 |
| Place of Publication | Oxford |
| Publisher | Oxford University Press |
| Publication date | 2025 |
| Pages | 9–34 |
| Chapter | 2 |
| ISBN (Print) | 9780198888642 |
| ISBN (Electronic) | 9780191995170 |
| DOIs | |
| Publication status | Published - 2025 |
Keywords
- Failure learning
- Models
- Errors
- Learning curves
- Failure–error mismatch
- Culture and learning