Student Perspectives on Leaving School, Pathways, and Careers

Patterns for social and school characteristics

The previous report at age 16, On the Edge of Adulthood (Wylie et al., in press) highlighted some patterns of school and social characteristics that impacted on learning engagement and achievement. It is likely that we see the outplaying of some of these patterns in the thinking and choices of the young people as they anticipated the transition to new pathways beyond school. This section draws together patterns in the data reported across the previous sections to explore these potential links.

Social characteristics

Gender

Females were more likely than males to be planning full-time study. They were more likely to be anxious about leaving behind the routines and friendships of school and they were also less likely than males to see connections between their experiences of paid work and their career aspirations. The previous report, On the Edge of Adulthood, reported that females were more likely than male students to: be enthusiastic about school; have higher literacy and attitudinal scores; be in academic rather than vocational or contextual subject clusters; and to enjoy reading. For the females, any of these differences could weight choices toward more formal study.

Males were more likely to be planning to work full-time, or to choose earning-while-learning options, and to see a connection between their post-school choice to something that pays well. More of them aspired to work in trades-related occupations. Congruent with these patterns, they were also more likely to see connections between their own work aspirations and a family business or job. On the Edge of Adulthood reported that males were more likely to be in vocational or contextual subject clusters, and these types of courses would have exposed students to practically-based occupations that might have particular appeal if they had become less engaged with more formal learning.

Ethnicity

Pākehā/NZ European and Asian students were more likely than Māori or Pacific students to be planning full-time study and they were more interested in professional careers. This is congruent with their higher levels of school engagement, their higher literacy and numeracy scores at age 16, and higher scores for the attitudinal competencies thinking and learning and focused and responsible (as reported in On the Edge of Adulthood).

Conversely, Māori or Pacific students were more likely to expect to be working full-time. Overall, these young people seemed to be less optimistic about their futures, with more of them seeing barriers to achieving the lifestyle they wanted. On the Edge of Adulthood reported that they were less likely to be satisfied with their subject choices and more likely to be in vocational and contextual subject clusters. Their teachers tended to hold lower expectations of their learning success and a third of them had achieved fewer than 80 Level 1 credits—an obvious barrier to pathways to future study. Nevertheless, Māori and Pacific young people were more likely to say they had found talking to school staff and the careers advisor helpful—but then again they are more likely to be in groups targeted for “life skills” courses that focus on preparation of life and work beyond school.

Maternal qualifications and family income

Both their mother’s lack of formal qualifications and being from a low-income home were associated with students seeing not being hassled by teachers as one of the best things about leaving school. This association suggests a lack of connection between some teachers and these students, the nature of which is described in some detail in On the Edge of Adulthood. Both of these social characteristics were also associated with a greater likelihood of not going on to tertiary study, including at university. Lack of maternal qualification (but not low income) was also associated with not seeing a professional occupation as a likely choice, and anticipating a trades-based choice of work. Students from high-income families were more likely to say their parents had been a helpful support for their careers thinking.

Students from low-income families more often attend low-decile schools. Here, too, there were associations that add to the picture of relatively fewer choices for these students. Students in decile 1 or 2 schools were less likely to say they would attend university, more likely to say they might choose a free Youth Training programme, and to see a career as a job with high status.

Effects of ethnicity are difficult to separate out from income, maternal qualifications, school decile, and school gender mix. About half of the Māori or Pacific young people in the study at age 16 were from low-income homes and schools have an especially important role in helping them to learn in ways that support them to see opportunities and that keep pathways open for them. They do less well at school and so have less room to move in terms of ongoing options. The school characteristics summarised next could be seen as evidence that some students “bring things on themselves” by the ways they behave both in and out of school. However, the data reported here, like data from other New Zealand research based in secondary schools, suggest that structural inequalities in schools contribute much to the educational outcomes and future life choices of these students.

School characteristics

Subject cluster

On the Edge of Adulthood describes four subject clusters that have strong similarities to those found in the Learning Curves project that investigated the introduction of NCEA into six New Zealand secondary schools (Hipkins et al., 2005). The four clusters we found across the 60 or more schools attended by students in the Competent Children, Competent Learners sample divided into two academic clusters (one with an arts orientation and one with a science orientation) and two clusters that we called contextual (which tended to group subjects that made connections to life outside school such as media studies) and vocational subjects (Wylie et al., in press). Similar to findings in the Learning Curves study, Māori and Pacific students were more likely than Pākehā/NZ European and Asian students to be taking a contextual or vocational subject combination and were less likely to be taking academic subjects. Males were also more likely than females to be taking contextual or vocational subject combinations while females were more likely to be taking a traditional academic science combination (Wylie et al., in press).

These four clusters were associated with a number of aspects of post-school decision making. Students in either of the academic clusters were more likely to be headed for full-time university study, after which they aspired to work in a professional occupation. By contrast, students taking contextual or vocational subject combinations were more likely to see not having teachers hassle them and not having to do school work as best things about leaving school. The preceding sections of this report have documented enjoyment of reading as a variable associated with a range of aspects of post-school decision making—aspects such as full-time university study that anticipate a need for ongoing learning. Here we see a pattern that suggests students taking certain sorts of subject combinations are more likely to be already on the way to being switched off from learning—at least in the short term—as they are from reading. But there are some suggestions that this is not a direction undertaken lightly—students in vocational and contextual clusters were more likely to say that lack of qualifications would be a barrier to the sort of life they wanted—and indeed to see a range of barriers that did not seem to be as constraining for other students.

Some aspects of choices are constrained by material resources. Students taking contextual or vocational subject combinations were more likely to be contemplating earning-while-learning options, to aspire to a trade, and to see connections between current and future work options. We have already seen that these types of choices have associations with students’ socio economic status, but it is not so clear that there ought to be a connection between their home circumstances and the combinations of subjects available to them at school. The Learning Curves research reported that assumptions about the learning needs of certain “types” of students can influence the guidance they are given, in particular by deans (Hipkins et al., 2005). To make timetable lines work, students taking “alternative” courses are more likely to be placed in at least some classes against their will—partly because there are simply less options available to create different types of subjects once all the more “academic” subjects have been allocated timetable spaces. This in turn influences the range of learning experiences to which these students are exposed at school, and in turn, the possibilities they can see for their futures.

Adding to this picture of inequalities in opportunities, the Learning Curves analysis suggested that even “core” subjects such as English and mathematics, seemingly taken in common by most students at least until the end of Year 11, will look very different for students in these different clusters, and will be assessed by quite different combinations of achievement and unit standards (Hipkins et al., 2006). This is not just of academic interest—entrance to university is enabled or constrained by having the correct combination of four factors: total number of Level 3 credits; a literacy requirement; a numeracy requirement; and having credits, mostly from achievement standards, distributed in certain ways across “approved subjects” from a published list generated in consultation with university vice chancellors. Recent research from the Star Path project at Auckland University has shown that, of those four factors, not having the correct distribution of credits across subjects is likely to be the main “choke point” for Māori and Pacific students in low-decile schools. Even if they satisfy the other three requirements, not having “chosen” a subject combination that will yield the necessary pattern of credits is likely to be what will prevent them from taking up university study immediately after they leave school (McKinley, 2008). Since clustering practices mean these students are more likely to find themselves in subjects that are “not approved” than in subjects that are, it is not difficult to see how school timetabling practices contribute directly to this outcome.

Total number of NCEA credits

Patterns associated with total number of NCEA credits gained at Level 1 are congruent with those for subject clusters and, if anything, emphasise the differences in outcomes for certain “types” of students even more strongly. Even though most students have gained all or most of their Level 1 credits by the end of Year 11, with potentially two more years of school still to go, this total may be acting as a strong signal about future directions. It appears to affirm future study directions, and in this way may be acting as the same sort of sorting and filtering agent as the School Certificate examination it replaced (Bolstad and Gilbert, 2008).

Students in the top quartile for NCEA credit totals at Level 1 were more likely to be planning full- time university study, and less likely to be heading for polytechnic, learning-while-earning, or Youth Training options. The difference was very marked: 90 percent of those in the top quartile said they were headed for university, compared with 33 percent in the bottom quartile for Level 1 NCEA credits. Of all the variables associated with choosing university or not, this was the most marked difference. By contrast those in the lowest quartile were more likely to see not having teachers hassle them and not having to do school work as best things about leaving school.

Students in the top quartile for NCEA credit totals at Level 1 were more likely to aspire to professional careers. Again, the difference was very marked (80 percent for top quartile vs. 29 percent for lowest quartile). Those in the lowest quartile were more likely to be heading for a career in a trade—an option chosen by not one student in the highest quartile for NCEA credits. They were also more likely to see work experience as useful for learning about careers, where students in the top quartile were more likely to find their school subjects useful for this.

Risky behaviour

We include risky behaviour under school characteristics here because it concerned behaviour in relation to school insofar as the students seemed to have already left school in their minds. Students in the quartile that showed the most evidence of risky behaviour outside of school also showed signs of the impact of this in school. They were more likely than other students to agree that not having teachers hassle them, and not having to do school work would be best things about leaving school. These students were also more likely to be looking forward to getting away from family and getting a job. They were less likely to be considering further study and more likely to be considering earning-while-learning options.

Associated with their focus away from school and formal learning, students with risky behaviour were more likely to indicate an interest in sales/services careers and to see an association between the idea of a career and on-the-job training. They were the most likely to see an association between paid work they had already experienced and their career aspirations, and were the group most likely to already be in paid part-time work. They were less likely to have found their families helpful for careers thinking, or to have found school subjects helpful in this respect.

The picture that emerges here is of students who were out-of-step with the wider possibilities that school was opening up for some of their peers. How they could see themselves “being” in the world was more bounded by the limits of their immediate experience and many options already appeared closed to them. Can we reasonably expect schools to compensate for students’ “deficits” in some of these social characteristics? Do schools contribute to these already-evident inequalities in ways they could ameliorate if they were more aware of them?