NewAbstractConcepts: A Database of 42 Normed Abstract Concepts and Exemplars.

abstract concept abstraction concept learning contextual diversity generalization mechanisms similarity

Journal

Journal of cognition
ISSN: 2514-4820
Titre abrégé: J Cogn
Pays: England
ID NLM: 101732790

Informations de publication

Date de publication:
2024
Historique:
received: 01 03 2024
accepted: 29 06 2024
medline: 15 7 2024
pubmed: 15 7 2024
entrez: 15 7 2024
Statut: epublish

Résumé

Recently, researchers have expressed challenges in conducting word-learning experiments in adult populations due to limited availability of normed stimulus materials. This constraint often prompts the use of low-frequency or low-prevalence words, introducing the potential influence of prior knowledge or direct translation to familiar words. In response, we developed novel abstract concepts devoid of word referents, providing better control over prior knowledge. These new concepts describe situations encountered in various settings for which there is no existing word in English. The resulting database comprises 42 normed New Abstract Concepts, offering unique materials structured through scenarios, each containing similar and dissimilar exemplars. These materials underwent meticulous norming for relatability and similarity levels across a series of studies. The success of our approach was demonstrated in a word-learning experiment examining the effects of similarity and diversity. The database serves as a valuable resource for selecting stimuli in experiments exploring the learning of abstract semantic concepts, particularly investigating the role of similarity versus diversity in concept learning. The database is available on OSF (https://osf.io/svm2p/).

Identifiants

pubmed: 39005953
doi: 10.5334/joc.384
pmc: PMC11243765
doi:

Types de publication

Journal Article

Langues

eng

Pagination

53

Informations de copyright

Copyright: © 2024 The Author(s).

Déclaration de conflit d'intérêts

The authors have no competing interests to declare.

Auteurs

Dounia Lakhzoum (D)

Université Clermont Auvergne, CNRS, LAPSCO, F-63001 Clermont-Ferrand, France.

Marie Izaute (M)

Université Clermont Auvergne, CNRS, LAPSCO, F-63001 Clermont-Ferrand, France.

Ludovic Ferrand (L)

Université Clermont Auvergne, CNRS, LAPSCO, F-63001 Clermont-Ferrand, France.

René Zeelenberg (R)

Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, The Netherlands.

Diane Pecher (D)

Department of Psychology, Education, and Child Studies, Erasmus University Rotterdam, The Netherlands.

Classifications MeSH