Extrapolation accuracy underestimates rule learning

• Verfasst von: Said, Nadia [VerfasserIn]
• Verfasst von: Fischer, Helen [VerfasserIn]
• Titel: Extrapolation accuracy underestimates rule learning
• Titelzusatz: evidence from the function-learning paradigm
• Verf.angabe: Nadia Said, Helen Fischer
• E-Jahr: 2021
• Jahr: 25 June 2021
• Umfang: 20 S.
• Teil: volume:218
• Teil: year:2021
• Teil: month:07
• Teil: elocationid:103356
• Teil: pages:1-20
• Teil: extent:20
• Fussnoten: Gesehen am 23.09.2021
• Titel Quelle: Enthalten in: Acta psychologica
• Ort Quelle: Amsterdam : Elsevier, 1936
• Jahr Quelle: 2021
• Band/Heft Quelle: 218(2021) vom: Juli, Artikel-ID 103356, Seite 1-20
• ISSN Quelle: 1873-6297
• DOI: doi:10.1016/j.actpsy.2021.103356
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Function-learning
• Sach-SW: Non-linear processes
• Sach-SW: Rule-based vs exemplar-based learners
• Sach-SW: Understanding
• K10plus-PPN: 1771732644

Abstract

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.