Learning From Surprise: Harnessing a Metacognitive Surprise Signal to Build and Adapt Belief Networks

• Published in: Topics in cognitive science Vol. 11; no. 1; pp. 164 - 177
• Main Authors: Munnich, Edward, Ranney, Michael A.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.01.2019
• Subjects: Belief networks; Belief revision; Learning; Metacognition; Reasoning; Surprise; Learning; Surprise; Reasoning; Metacognition; Belief revision
• ISSN: 1756-8757; 1756-8765
• DOI: 10.1111/tops.12397

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. This paper considers how surprise (or its lack) can be cast as a metacognitive signal with an adaptive function in learning new knowledge and revising belief networks. It reviews the phenomena that may hinder this signal (e.g., hindsight bias) and argues for its extrinsic exploitation in instructional and educational contexts by educators, journalists and parents, who might train learners to internalize the use of surprise to drive explanation‐based learning.