Doctor of Philosophy
Learning from errors involves analysis and identification of error causes, as well as implementation of solutions to prevent similar errors in the future. The present thesis extends this conceptualization: Integrating research on errors from different contexts, from high reliability organizations to training environments, service occupations, and creative settings, this thesis submits that individuals may experience a variety of error learning types that include task, prevention, response, coping, and meta-learning. The thesis also presents a corresponding Learning from Errors (LFE) measurement inventory with five distinct error learning constructs and offers initial evidence of their validity. Furthermore, the thesis investigates the role of growth- and security-related motives in attaining the five error learning types. Specifically, relying on regulatory focus theory (Higgins, 1997, 1998), the thesis presents a model linking growth concerns with error learning types that maximize achievement and security concerns with error learning types that minimize threat. The findings from three samples confirm distinct influences of growth and security concerns on error learning, however the observed distinctions are different from those hypothesized. Contrary to expectations, security concerns exhibited wide-ranging positive associations with all error learning types, with particularly sizeable contributions to prediction of task, prevention, and response learning. Growth concerns, on the other hand, showed relatively modest influence on prevention and response learning, while positively contributing to task, coping, and meta-learning. Overall, this work highlights the multifaceted nature of learning from errors by providing an integrated theoretical typology, empirically validating the proposed error learning types, and highlighting distinctions in their motivational antecedents.
Summary for Lay Audience
Encounters with errors at work commonly elicit ideas about learning, such as “errors are a stepping stone to success” or “errors are our best teachers.” The present thesis unpacks the general notion of learning from errors and examines what this learning is actually about. In doing so, the thesis shows that the lessons learned from errors may vary in their nature and content, suggesting that errors may be harnessed for one’s improvement in more ways than one. Specifically, the thesis presents a typology with five distinct types of learning.
From this diversity of potential lessons, what we actually learn depends on our fundamental human needs for growth and security, whether stable or transient. Pre-occupation with self-development and self-actualization is particularly beneficial for learning of new skills and emotional coping strategies, while concern for one’s security is instrumental for realizing the full range of learning benefits offered by errors, including learning to prevent errors and to respond to them when they occur. Thus, both motivations – aspiration for growth and concerns with security – play an important role in learning from errors.
Overall, this work enables researchers to investigate distinct error learning outcomes and suggests a theory linking growth and security motives with different types of learning from errors.
Sycheva, Anna, "What Do We Learn From Errors? Multidimensionality and Motivational Underpinnings of Error Learning" (2019). Electronic Thesis and Dissertation Repository. 6268.
Available for download on Thursday, April 29, 2021