Unpacking on-task effort in performance-based learning: Information-knowledge gaps guide effort allocation decisions

J Appl Psychol. 2024 Jan;109(1):77-98. doi: 10.1037/apl0001140. Epub 2023 Aug 3.

Abstract

Learning and adaptation are essential for success. However, human effort is inherently finite, which creates a dilemma for employees. Is it better to prioritize capitalizing on existing knowledge structures to maximize immediate performance benefits (exploitation) or develop adaptive capabilities (exploration) at the expense of short-term productivity? Understanding how employees answer this question can inform the design of evidence-based interventions for optimizing and sustaining learning amidst workplace challenges. In this article, we attempt to unpack the composition of on-task effort during performance-based learning by testing the proposition that the information-knowledge gap-a regulatory discrepancy between unknown aspects of a task and a person's perceived competence in dealing with that task-is the psychological mechanism responsible for guiding effort-allocation decisions during performance-based learning. In Study 1, we found that larger information-knowledge gaps resulted in increased subsequent investments of on-task attention within a sample of adults learning to perform a complex task (N = 121). As participants learned, information-knowledge gaps systematically shrank, resulting in a reduced emphasis on learning-oriented effort (i.e., exploration) relative to achievement-oriented effort (i.e., exploitation) over time. In Study 2 (N = 176), a task-change paradigm revealed that introducing novel demands caused information-knowledge gaps to suddenly expand, which prompted participants to increase on-task effort and shift their focus away from achievement and back toward learning as an adaptive response. Collectively, these findings support the notion that information-knowledge gaps shape how (and when) on-task effort is spent and present a framework for understanding how learners strategically structure their limited attentional resources. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

MeSH terms

  • Adult
  • Attention* / physiology
  • Humans
  • Learning*