Need for cognition in children and adolescents: behavioral correlates and relations to academic achievement and potential.
Integrity signals
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
High levels of NFC have a positive impact on performance and school grades.
“High levels of NFC have a positive impact on performance (Weissgerber et al., 2018) and school grades (Grass et al., 2017; Luong et al., 2017; Strobel et al., 2019).”
From Retrieval Practice Is Effective Regardless of Self-Reported Need for Cognition - Behavioral and Brain Imaging Evidence (2022) · cites this paper as Luong et al., 2017
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References 53 · Cited by 71
- Authors
- Luong, C., Strobel, A., Wollschläger, R., Greiff, S., Vainikainen, M.-P., & Preckel, F.
- Affiliations
- Chemnitz University of Technology (DE)
- Universität Trier (DE)
- University of Luxembourg (LU)
- University of Helsinki (FI)
- Corresponding author
- Strobel, Anja
- ORCID
- Venue
- Learning and Individual Differences
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 53
- Pages
- 103-113
- ISSN
- 1041-6080 (ISSN-L)
- OpenAlex
- W2560102385
- Cited by
- 71
- References
- 53
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 7 · 2023: 12 · 2022: 8 · 2021: 13 · 2020: 6 · 2019: 7 · 2018: 6 · 2017: 3
- FWCI
- 7.59
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Learning and Individual Differences (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychological and Educational Research Studies
- Social Sciences › Psychology › Developmental and Educational Psychology › Learning Styles and Cognitive Differences
- Keywords
- need for cognition, children, adolescents, academic performance, academic potential, self-concept, control motivation, learning orientation, intrinsic motivation, developmental changes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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