Automatization through Practice: The Opportunistic-Stopping Phenomenon Called into Question.

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Ressource 1Download: Cognitive Science - 2021 - Dewi - Automatization through Practice The Opportunistic%E2%80%90Stopping Phenomenon Called into.pdf (592.88 [Ko])
State: Public
Version: Final published version
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_C4DFC4B91B75
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automatization through Practice: The Opportunistic-Stopping Phenomenon Called into Question.
Journal
Cognitive science
Author(s)
Dewi JDM, Bagnoud J., Thevenot C.
ISSN
1551-6709 (Electronic)
ISSN-L
0364-0213
Publication state
Published
Issued date
12/2021
Peer-reviewed
Oui
Volume
45
Number
12
Pages
e13074
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
As a theory of skill acquisition, the instance theory of automatization posits that, after a period of training, algorithm-based performance is replaced by retrieval-based performance. This theory has been tested using alphabet-arithmetic verification tasks (e.g., is A + 4 = E?), in which the equations are necessarily solved by counting at the beginning of practice but can be solved by memory retrieval after practice. A way to infer individuals' strategies in this task was supposedly provided by the opportunistic-stopping phenomenon, according to which, if individuals use counting, they can take the opportunity to stop counting when a false equation associated with a letter preceding the true answer has to be verified (e.g., A + 4 = D). In this case, such within-count equations would be rejected faster than false equations associated with letters following the true answers (e.g., A + 4 = F, i.e., outside-of-count equations). Conversely, the absence of opportunistic stopping would be the sign of retrieval. However, through a training experiment involving 19 adults, we show that opportunistic stopping is not a phenomenon that can be observed in the context of an alphabet-arithmetic verification task. Moreover, we provide an explanation of how and why it was wrongly inferred in the past. These results and conclusions have important implications for learning theories because they demonstrate that a shift from counting to retrieval over training cannot be deduced from verification time differences between outside and within-count equations in an alphabet-arithmetic task.
Keywords
Counting, Knowledge acquisition, Learning, Retrieval, Strategies, Training
Pubmed
Web of science
Open Access
Yes
Create date
03/01/2022 14:11
Last modification date
07/01/2022 7:33
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