Influences of basic numerical abilities on graph reading performance.


Journal

Psychological research
ISSN: 1430-2772
Titre abrégé: Psychol Res
Pays: Germany
ID NLM: 0435062

Informations de publication

Date de publication:
Jul 2020
Historique:
received: 15 03 2018
accepted: 03 01 2019
pubmed: 21 2 2019
medline: 21 10 2020
entrez: 21 2 2019
Statut: ppublish

Résumé

Understanding graphically presented information is an important aspect of modern mathematical and science literacy. In our study, we investigated the influence of basic numerical abilities on students' ability answer mathematical tasks with information presented in graphs. We analyzed data of 750 German students (grades 9-11) and evaluated the determinants of graph reading performance with multiple regression analysis using predictors of basic numerical abilities (such as number line estimation, basic arithmetic operations, etc.), considering also the influences of general cognitive ability, age, and gender. We found that number line estimation, subtraction, and conceptual knowledge were significant predictors of graph reading performance beyond the influences of general cognitive ability. This indicates that basic numerical abilities are still relevant for real-life problem solving in secondary school. We discuss possible mechanisms which directly (through respective arithmetic procedures) as well as indirectly (through mathematization of the problem) effectuate that basic numerical abilities graph reading performance.

Identifiants

pubmed: 30783813
doi: 10.1007/s00426-019-01144-y
pii: 10.1007/s00426-019-01144-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1198-1210

Subventions

Organisme : LEAD Graduate School & Research Network
ID : GSC1028

Auteurs

Ulrich Ludewig (U)

LEAD Graduate School & Research Network, University of Tuebingen, Tübingen, Germany. ludewig.ulrich@gmail.com.

Katharina Lambert (K)

Hector Research Institute of Education Sciences, University of Tuebingen, Tübingen, Germany.

Tanja Dackermann (T)

Leibniz-Institut für Wissensmedien, University of Tuebingen, Tübingen, Germany.

Katharina Scheiter (K)

Leibniz-Institut für Wissensmedien, LEAD Graduate School & Research Network, University of Tuebingen, Tübingen, Germany.

Korbinian Möller (K)

Leibniz-Institut für Wissensmedien, LEAD Graduate School & Research Network, University of Tuebingen, Tübingen, Germany.

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Classifications MeSH