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The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

The Domain Specificity of Academic Emotional Experiences

Open access
Goetz, Thomas, Frenzel, Anne C., Pekrun, Reinhard, Hall, Nathan C.·2006·The Journal of Experimental Education

Abstract

The authors analyzed the domain specificity of emotions and focused on experiences of enjoyment, anxiety, and boredom in the domains of mathematics, Latin, German, and English. On the basis of assumptions in R. Pekrun's (2000; in press) control-value theory and findings of pilot studies, the authors hypothesized the existence of a largely domain-specific organization of emotional experiences. The sample consisted of 721 students from grades 7 to 10. Confirmatory multitrait-multimethod factor analysis of the 2-faceted dataset (emotions and domains) corroborated assumptions of domain specificity. Furthermore, using multilevel analysis, the authors found that emotions were significantly more domain-specific than students' grades, with enjoyment being the most domain-specific of the three emotions under investigation. The authors discuss implications for future research and practice.

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Metadata

Authors
Goetz, T., Frenzel, A. C., Pekrun, R., & Hall, N. C.
Venue
The Journal of Experimental Education
Published
2006-10-01
Volume
75
Issue
1
Pages
5-29
ISSN
  • 0022-0973 (ISSN-L)
  • 1940-0683
OpenAlex
W2147175761
Cited by
260
References
6
FWCI
6.45
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: The Domain Specificity of Academic Emotional Experiences. https://app.cochat.ai/papers/10.3200/jexe.75.1.5-29
The paper
Goetz, T., Frenzel, A. C., Pekrun, R., & Hall, N. C. (2006). The Domain Specificity of Academic Emotional Experiences. The Journal of Experimental Education. https://doi.org/10.3200/jexe.75.1.5-29

Data sources

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.