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Autor/inn/enRubin, Mark; Scevak, Jill; Southgate, Erica; Macqueen, Suzanne; Williams, Paul; Douglas, Heather
TitelOlder Women, Deeper Learning, and Greater Satisfaction at University: Age and Gender Predict University Students' Learning Approach and Degree Satisfaction
QuelleIn: Journal of Diversity in Higher Education, 11 (2018) 1, S.82-96 (15 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1938-8926
DOI10.1037/dhe0000042
SchlagwörterAge Differences; Gender Differences; Predictor Variables; Undergraduate Students; Student Surveys; Learning; Foreign Countries; Transformative Learning; Learner Engagement; Student Satisfaction; Correlation; Statistical Analysis; Australia
AbstractThe 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 on paper. 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. (As Provided).
AnmerkungenAmerican Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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