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Abstract
Young people’s aspirations remain an enduring focus of education policy interest and concern. Drawing on data from an ongoing five-year study of young people’s science and career aspirations (age 10–14), this paper asks what do young people aspire to at age 12/13, and what influences these aspirations? It outlines the main aspirations and sources of these aspirations as expressed by young people in England in the last year of primary school (survey of 9000+ Y6 pupils, aged 10/11, interviews with 92 children and 76 parents) and the second year of secondary school (survey of 5600+ Y8 pupils, aged 12/13, interviews with 85 pupils). We demonstrate how aspirations are shaped by structural forces (e.g. social class, gender and ethnicity) and how different spheres of influence (home/family, school, hobbies/leisure activities and TV) appear to shape different types of aspirations. The paper concludes by considering the implications for educational policy and careers education.
Keywords:
Notes
This article was originally published with errors. This version has been corrected. Please see Corrigendum (http://dx.doi.org/10.1080/02680939.2013.808799).
1. Although, on the whole, minority ethnic groups tend to achieve quite highly within the UK education system, education policy has emphasised a ‘problem’ of low aspirations which has been attributed to the lower performance of particular minority ethnic groups, such as Black Caribbean pupils – e.g. DfES (2005), para 4.4 ‘Our Aiming High programme is focused on stretching the aspirations and achievement of Black and minority ethnic groups’, as discussed in Archer and Francis (2007).
3. These higher order categorisations contained the following sub-categories: White (English, Welsh, Scottish, Irish, Other White [free response]); Black (Black African, Black Caribbean, ‘Other’ Black [free response]); Asian (Indian, Pakistani, Bangladeshi, ‘Other’ Asian [free response]). Other/Mixed (Black and White; Asian and White; Black and Asian; ‘Other’ [free response]).
4. In addition and in light of these concerns, PLASC data related to socio-economic classification (such as FSM eligibility and IDACI scores) were also used in analysing the data.
5. Of the 5634 students who participated in Survey 2, 2251 (40.0%) were boys and 3358 (59.6%) were girls (25 students did not provide their gender). 5226 (93%) attended state schools and 408 (7%) attended independent schools. 711 of the 5634 students who completed Survey 2 also completed Survey 1. This was a disappointingly low figure but we plan to increase this percentage in survey three by using the National Pupil Database to more accurately identify target schools containing Phase 1 participants. The outcome of this strategy will be known mid-2013. However, we do believe that the phase 2 data-set still provides interesting data pertaining to the wider cohort.
6. The same sub-categories were used as in the Y6 survey – see endnote 3.
7. Both surveys contained the following questions: ‘Here are some different jobs. Would you like to do any of them or not? When I grow up I would like to: [respondents rate each on Likert scale]: be a doctor or work in medicine; work in science; work in engineering; be an inventor. The following questions were also used on both surveys with a Likert response scale: ‘I would like to study more science in the future’. ‘I would like to have a job that uses science’. ‘I would like to become a scientist’. ‘I think I could be a good scientist one day’. Survey 2 only contained the following additional questions: (All under the section ‘when I grow up I would like to ...’): run or work in a business; work in sports or be a professional athlete; work in the arts or be an artist, musician, actor or dancer. Both surveys included a free response question: ‘What would you like to be when you grow up?
8. Note that the latent variables used contain the items for those variables in the Year 6 survey, to allow for comparison. In addition, the ‘cohort mean’ is the mean for the rest of the cohort – the Year 6 or Year 8 group, minus the 757. Finally, in the Year 6 comparison, we used the Year 6 data for the 757 and likewise for Year 8. Comparison of matched group (757) with Year 6 cohort on LVs . Comparison of matched group (757) with Year 8 cohort on LVs.
9. In both the Year 6 and Year 8 data, the matched group is slightly higher than the rest of the cohort in terms of their aspirations in science and associated variables. However, although the difference between the groups in the Year 6 data approaches significance for Aspirations in science and Parental attitudes to science variable (p values less than 0.10), the groups only differ significantly on the Self-concept in science latent variable. In the Year 8 data, the groups only differ significantly on the Parental attitudes to science latent variable. Moreover, on either of these variables (Parental attitudes to science in the Year 8 data and Self-concept in science in the Year 6 data), one could argue as to how important these differences actually are. That is, the differences are statistically significant, but they are unlikely to be significant if the sample sizes were not so large. On the other hand, that the matched group had higher means than the rest of each cohort (Year 6 and Year 8) on all five of the above latent variables above does suggest that this group probably was slightly more engaged with science than the rest of the cohort. We will attempt to increase the size of the matched sample in the forthcoming final, third phase of the research in order to investigate these differences further.
10. Non-responses to the 11 separate aspiration related Likert scale questions in the surveys ranged from 0.6 to 3.1% in the Y6 survey and from 0.6 to 0.9% in the Y8 survey. In addition 3.8% of children on the Year 6 survey and 8.0% on the Year 8 survey replied ‘don’t know’ to the free response question.
11. To keep the Y8 survey to a manageable length, the number of occupations listed on this item was restricted to those indicated in Figure 2. However, for the Y9 survey, this list is expanded to include other popular aspirations, as derived from the wider analysis, such as teacher.
12. A number of respondents strongly/disagreed with all the science career options presented in the closed questions on the survey. For the Y6 survey, these were 1799 students (27.2% boys and 62.7% girls; 6.1% Black; 81.0% White; 4.7% Asian; 7.3% Other; 0.2% North African or Middle Eastern; 0.6% Far Eastern. Cultural capital: 2.9% very low; 31.9% low; 33.7% medium; 17.7% high; 13.8% very high). In the second (Y8) survey, these were 107 students (36.2% male; 63.8% female: 4.7% Black; 75.7% White; 5.6% Asian; 0.9% Chinese, 13.1% Other; 10.3% very low cc; 43.9% low cc; 19.6% medium cc; 10.3% high cc; 15.9% very high cc).
13. See also Yates et al. (2011) finding that overambitious adolescents who lack the means to realise their ambitions are more likely to become NEET.
14. Although the UK also records among the largest regional disparities (e.g. the UK records the biggest gap in ratio of tertiary education graduates to the population aged 15 or over, having both the highest and lowest rates (inner London, 41.8%; Tees Vale/Durham, 18.4%, Ballas et al. 2012).
15. See http://www.education.gov.uk/inthenews/inthenews/a00211875/government-publishes-destination-data-for-the-first-time-Accessed 15/1/13.
16. The percentages of pupils in each cultural capital (cc) category agreeing that their parents expect them to go to university were: very low cc, 47.2%; low cc, 57.7%; medium cc, 67.4%; high cc, 82.1%; very high cc, 91.4%.
17. As with the other latent variables used in the analysis, the latent variable for parental aspirations emerged from the principal components analysis of the survey data. This analysis indicated that the four items listed below formed a component. That is, these four items (which followed the prompt ‘How much do you agree with these statements about your family?’) loaded most strongly on a single component (factor loadings ranged from 0.534 to 0.817), which had a Cronbach’s alpha of .698. It comprised the following items: They want me to make a lot of money when I grow up; They want me to get a good job when I grow up; It is important to them that I get good marks in school; They expect me to go to university.
18. See also: 56.4% of those with very low cultural capital strongly/disagree cf. 30.4% with very high cultural capital strongly/disagree.
19. These top-level ethnic descriptors are used here in the text for ease in conveying broad brush patterns. But these top level descriptors were generated from pupils’ self-identifications with far more specific subcategories. E.g. Black included Black British, Black African, Black Caribbean and Black Other. ‘Asian’ included British Asian, and a range of Indian subcontinent ethnic options, such as Indian, Pakistani and Bangladeshi. A range of ‘mixed’ ethnic identifiers were also used but are not reported here.
20. Pupils were asked in detail about how and why they developed particular aspirations. Many young people spontaneously mentioned how their ideas were inspired by people they knew who were already doing these jobs (e.g. because they liked the person and wanted to emulate them or had learnt from them about an interesting potential job). If not already mentioned, follow-up probing questions were asked as to whether pupils knew anyone already doing the job that they aspired to and a judgement was made during the analysis (based on interview responses) as to whether the person mentioned appeared to have influenced the young person’s aspiration, or not. If not, they were not coded as a source of aspiration (although the argument could be made that they constitute a form of social capital irrespective of the child’s own perception).
21. The measure of cultural capital (described above) was used to categorise survey participants. But parents and children who took part in the interviews were classified using more conventional class descriptors (e.g. upper-middle-class, lower-middle-class, working-class) based on information gained from interviews such as parental occupations (using the NS-SEC categorisations), housing tenure and parental educational backgrounds. For reasons of time and anonymity we did not match cultural capital scores from the surveys with individual interviewees.
22. Indeed, Milburn (2012) noted that many internships in highly sought professions such as law, medicine and journalism are arranged informally.
23. For instance, in a recent survey 57% young people aged 12–16 found school-mediated workplace contacts very useful influence on their careers choices (more useful than public info 34% or family/friends 51%) – see Mann (2012).
24. E.g. see Johnson (Citation2000), who found that senior elementary school children had only a limited understanding of how their school academic activities related to the future world of work.