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Cited by 306

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Motivation and Academic Resilience: Developing a Model for Student Enhancement

Martin, Andrew·2002·Australian Journal of Education

Abstract

This paper explores a model of motivation and introduces the concept of academic resilience. Although motivation is critical to academic success, academic gains that students make can be lost if they are not resilient to setback, study pressure, and stress in the school setting. It is therefore important that students are motivated and resilient to academic pressures. A problem with motivation theory and research, however, is that it has not been formulated in a way that provides educators and students with a common language with which to develop motivation and academic resilience in the classroom. This paper draws together seminal motivation theory, posits clear constructs that represent these theories, and then repackages them into a model that can be used by educators and understood by students. Such a model also holds direct implications in the classroom and counselling contexts, and the strategies for enhancing motivation and academic resilience are discussed.

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Crossref · 10.1177/000494410204600104

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Metadata

Authors
Martin, A.
Venue
Australian Journal of Education
Published
2002-04
Volume
46
Issue
1
Pages
34-49
ISSN
  • 0004-9441 (ISSN-L)
  • 2050-5884
OpenAlex
W2087611264
Cited by
306
References
47
FWCI
9.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Motivation and Academic Resilience: Developing a Model for Student Enhancement. https://app.cochat.ai/papers/10.1177/000494410204600104
The paper
Martin, A. (2002). Motivation and Academic Resilience: Developing a Model for Student Enhancement. Australian Journal of Education. https://doi.org/10.1177/000494410204600104

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.