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Cited by 310

The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.

Coursework Selection: Relations to Academic Self-Concept and Achievement

Marsh, Herbert W., Yeung, Alexander Seeshing·1997·American Educational Research Journal
DOI 10.2307/1163354
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Abstract

Theoretical models posit that self-concept as well as prior accomplishments influence choice behavior. Structural equation models were used to examine the paths from school grades and self-concept to subsequent coursework selection (N = 246). Paths from self-concept to wanting to take a particular subject and, to a lesser extent, actually taking it were significant, but school grades did not contribute consistently beyond the effects of self-concept. When general academic self-concept (GASC) was added to these models, paths from GASC to coursework selection were negative, and paths from the specific components of self-concept increased; a positive self-concept in a specific school subject contributes even more to selection of that subject if self-concepts in other school subjects are lower. The major results were consistent across Years 8 and 10 and reasonably consistent across nine school subjects. The finding that specific components of self-concept are more strongly related to subsequent course selection than are school grades is substantively important and provides further support for the need to consider multiple dimensions of academic self-concept.

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Metadata

Authors
Marsh, H. W., & Yeung, A. S.
Venue
American Educational Research Journal
Publisher
SAGE Publications
Published
1997
Volume
34
Issue
4
Pages
691
ISSN
0002-8312 (ISSN-L)
DOI
10.2307/1163354
OpenAlex
W2047194355
Cited by
310
References
45
FWCI
14.17
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.