Extrapolation accuracy underestimates rule learning: evidence from the function-learning paradigm
Understanding the development of non-linear processes such as economic or population growth is an important prerequisite for informed decisions in those areas. In the function-learning paradigm, people's understanding of the function rule that underlies the to-be predicted process is typically...
Gespeichert in:
| Hauptverfasser: | , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
25 June 2021
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| In: |
Acta psychologica
Year: 2021, Jahrgang: 218, Pages: 1-20 |
| ISSN: | 1873-6297 |
| DOI: | 10.1016/j.actpsy.2021.103356 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.actpsy.2021.103356 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0001691821001062 
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| Verfasserangaben: | Nadia Said, Helen Fischer |
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| 520 | |a Understanding the development of non-linear processes such as economic or population growth is an important prerequisite for informed decisions in those areas. In the function-learning paradigm, people's understanding of the function rule that underlies the to-be predicted process is typically measured by means of extrapolation accuracy. Here we argue, however, that even though accurate extrapolation necessitates rule-learning, the reverse does not necessarily hold: Inaccurate extrapolation does not exclude rule-learning. Experiment 1 shows that more than one third of participants who would be classified as “exemplar-based learners” based on their extrapolation accuracy were able to identify the correct function shape and slope in a rule-selection paradigm, demonstrating accurate understanding of the function rule. Experiment 2 shows that higher proportions of rule learning than ruleapplication in the function-learning paradigm is not due to (i) higher a priori probabilities to guess the correct rule in the rule-selection paradigm; nor is it due to (ii) a lack of simultaneous access to all function values in the function-learning paradigm. We conclude that rule application is not tantamount to rule-learning, and that assessing rule xlearning via extrapolation accuracy underestimates the proportion of rule learners in function-learning experiments. | ||
| 650 | 4 | |a Function-learning | |
| 650 | 4 | |a Non-linear processes | |
| 650 | 4 | |a Rule-based vs exemplar-based learners | |
| 650 | 4 | |a Understanding | |
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