Literature DB >> 28741254

Performance bias: Why judgments of learning are not affected by learning.

Nate Kornell1, Hannah Hausman2.   

Abstract

Past research has shown a performance bias: People expect their future performance level on a task to match their current performance level, even when there are good reasons to expect future performance to differ from current performance. One explanation of this bias is that judgments are controlled by what learners can observe, and while current performance is usually observable, changes in performance (i.e., learning or forgetting) are not. This explanation makes a prediction that we tested here: If learning becomes observable, it should begin to affect judgments. In three experiments, after practicing a skill, participants estimated how they performed in the past and how they expected to perform in the future. In Experiments 1 and 2, participants knew they had been improving, as shown by their responses, yet they did not predict that they would improve in the future. This finding was particularly striking because (a) they did improve in the future and (b) as Experiment 3 showed, they did hold the conscious belief that past improvement predicted future improvement. In short, when learning and performance are both observable, judgments of learning seem to be guided by performance and not learning.

Entities:  

Keywords:  Judgment; Memory; Metacognition; Skill acquisition

Mesh:

Year:  2017        PMID: 28741254     DOI: 10.3758/s13421-017-0740-1

Source DB:  PubMed          Journal:  Mem Cognit        ISSN: 0090-502X


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