Abstract
The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.
Original language | English |
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Article number | 275 |
Number of pages | 16 |
Journal | Frontiers in Psychology |
Volume | 8 |
DOIs | |
Publication status | Published - 28-Feb-2017 |
Keywords
- second-order false belief reasoning
- theory of mind
- instance-based learning
- reinforcement learning
- computational cognitive modeling
- ACT-R
- PERSPECTIVE-TAKING
- YOUNG-CHILDREN
- MENTAL STATES
- INSTANCE
- ADULTS
- GAMES
- COMPREHENSION
- UNDERSTAND
- REASON
- LEARN