Using confidence and consensuality to predict time invested in problem solving and in real-life web searching

Understanding processes that lead people to invest a certain amount of time in challenging tasks is important for theory and practice. In particular, researchers often assume strong linear associations between confidence, consensuality (the degree to which an answer is independently given by multiple participants), and response time. The Diminishing Criterion Model (DCM; Ackerman, 2014) is a metacognitive model which explains the stopping rules people employ under uncertainty in terms of the confidence–time association. This model is unique in predicting a curvilinear rather than a linear confidence–time association. Using consensuality as an alternative to confidence for predicting response time offers theoretical and practical opportunities. In four experiments, including replications and variations, we examined confidence (where collected) and consensuality as predictors of the time people invest in three problem-solving tasks and in real-life web searching. The results using consensuality, like those for confidence, fitted the curvilinear time pattern predicted by the DCM, with one exception: at least 30% of the population must endorse a potential answer for consensuality to predict response time based on the stopping rules in the DCM. Beyond examining consensuality as a predictor, the study brings converging evidence supporting the DCM's curvilinear confidence–time association over alternative models. The methodology used for analyzing web searching offers new directions for metacognitive research in naturally-performed tasks. •The Diminishing Criterion Model (DCM) predicts response time based on confidence.•We examined consensuality as a replacement when confidence cannot be elicited.•Consensuality predicted response time in problem solving and real-life web searches.•We found a consistent curvilinear time pattern in line with the DCM.•This pattern was robust across multiple-choice, but not open-ended, tasks.