Older women, deeper learning, and greater satisfaction at university: Age and gender predict university students’ learning approach and degree satisfaction.

Abstract

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.

Linear Relationship between Resilience, Learning Approaches, and Coping Strategies to Predict Achievement in Undergraduate Students

“…Nor has the role of the gender variable been considered in this model, which previous research has proved to have an effect (Stöber, 2004; Rubin et al, 2016). For future research, some of these instruments should be revalidated to ensure structural adequacy and factorial invariance as a preliminary step to their use, given that some inconsistencies have been found in the results, such as the low reliability of the Scale of Spirituality (Resilience) in this university sample.…”

Narratives from non-traditional students in higher education

“…Older women can also provide more intrinsic motivations for study (McCune et al, 2010). Recent research has linked these factors, finding that older female students more often have a deep learning approach than younger females or men of any age (Rubin, Scevak et al, 2016). …”

“…He claimed passing courses was 'no problem', although in some cases his grades indicated that he only just passed. This difference in attitude may be related to gender as mature female students have a deeper approach to learning (Rubin, Scevak et al, 2016) and are more likely to attribute any difficulties they experience in HE to themselves (O'Shea, 2014). For David, passing may have been the main goal.…”

“…I present each of their chronological stories followed by analysis in turn, utilising Bourdieu's thinking tools of habitus, capital and field before discussing similarities and differences among their experiences. There is no specific point at which students are designated to be mature-age, as far as the research literature is concerned (Rubin, Scevak et al, 2016). A number of researchers have considered 23 years of age to be an appropriate boundary (for example Andreou, Vlachos & Andreou, 2006), while O'Shea (2016b) reported on students aged 25 years or more.…”

“…The measure is, however, arbitrary (Rubin, Scevak et al, 2016), and so I have included this 24 year old student in a group which lies in between school leavers and the clearly mature age students of the previous chapter. As in the previous chapter I will present each story with analysis in turn before discussing similarities and differences among their experiences.…”