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Learning From Surprise: Harnessing a Metacognitive Surprise Signal to Build and Adapt Belief Networks
Author(s) -
Munnich Edward,
Ranney Michael A.
Publication year - 2019
Publication title -
topics in cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.191
H-Index - 56
eISSN - 1756-8765
pISSN - 1756-8757
DOI - 10.1111/tops.12397
Subject(s) - surprise , hindsight bias , metacognition , adaptation (eye) , task (project management) , computer science , signal (programming language) , cognitive psychology , function (biology) , point (geometry) , psychology , artificial intelligence , social psychology , cognition , management , geometry , mathematics , neuroscience , evolutionary biology , economics , biology , programming language
One's level of surprise can be thought of as a metacognitive signal indicating how well one can explain new information. We discuss literature on how this signal can be used adaptively to build, and, when necessary, reorganize belief networks. We present challenges in the use of a surprise signal, such as hindsight bias and the tendency to equate difficulty with implausibility, and point to evidence suggesting that one can overcome these challenges through consideration of alternative outcomes—especially before receiving feedback on actual outcomes—and by calibrating task difficulty with one's knowledge level. As such, we propose that a major function of education—broadly construed as the work of teachers, journalists, parents, etc.—is to assist learners in using their metacognitive surprise signals to facilitate the building and adaptation of belief networks.