- Title
- Older women, deeper learning, and greater satisfaction at university: age and gender predict university students' learning approach and degree satisfaction
- Creator
- Rubin, Mark; Scevak, Jill; Southgate, Erica; Macqueen, Suzanne; Williams, Paul; Douglas, Heather
- Relation
- Journal of Diversity in Higher Education Vol. 11, Issue 1, p. 82-96
- Publisher Link
- http://dx.doi.org/10.1037/dhe0000042
- Publisher
- American Psychological Association
- Resource Type
- journal article
- Date
- 2018
- Description
- The present study explored the interactive effect of age and gender in predicting surface and deep learning approaches. It also investigated how these variables related to degree satisfaction. Participants were 983 undergraduate students at a large public Australian university. They completed a research survey either online or in hardcopy. Consistent with previous research, age was a positive predictor of both surface and deep learning. However, gender moderated this age effect in the case of deep learning: Age predicted deep learning more strongly among women and not among men. Furthermore, age positively predicted degree satisfaction among women but not among men, and deep learning mediated this moderation effect. Hence, older female students showed the greatest deep learning in the present sample, and this effect explained their greater satisfaction with their degree. The implications of these findings for pedagogical practices and institutional policy are considered.
- Subject
- gender differences; deep learning; degree satisfaction; learning approach; surface learning
- Identifier
- http://hdl.handle.net/1959.13/1390270
- Identifier
- uon:33023
- Identifier
- ISSN:1938-8926
- Rights
- © American Psychological Association, 2018. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. Please do not copy or cite without author's permission. The final article is available, upon publication, at: http://dx.doi.org/10.1037/dhe0000042.
- Language
- eng
- Full Text
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