Who amongstinitial phase leaversin Englandis least likely to return to adult learning? Evidence from the BHPS cohort of 1997 leavers
Flora Macleod & Paul Lambe
University of Exeter
A paper for presentation at the annual conference of the British Educational Research Association, Warwick, 6-9 September 2006
© 2006 – work in progress – please contact the authors if you wish to quote from this paper
Abstract
This paper takes a life course perspective and uses rich longitudinal panel data to investigate the predictors of the an early return to adult learning after completing initial phase education. We found that more than a quarter of our sample of 1997 leavers (n=463) had not returned to adult learning six years after leaving. Males were more likely than females to return. Those who left initial full time education with low or noqualifications, those who were recorded as unemployment within one year of leaving, those whose household per capita income within one year of leaving was recording as being in the lowest one third, those who were not owner occupiers within one year of leaving, those who made a role transition into marriage/cohabitation or parenthood or from employment to unemployment during the first six years from leaving were less likely to return than their respective counterparts. We also found that being female, married or cohabiting, a parentand not being in employment compounded the probability of not returning. No difference was found in rates of return for those leavers living in an urban or rural area one year after leaving nor for those whose first job occupational class was recorded as being upwardly mobile form that of their household when they were aged 14. Further work will investigate the extent to which good predictors of the first episode of adult learning are also good predictors of patterns of participation later in life.
Introduction
The LearningLives project[1] seeks to deepen understanding of learning in the life course.Learning is conceptualised as a social process which is caught up in complex ways in matters of who we are, what we aspire to become, the pathways we follow and the company we keep or aspire to keep. Our research design involves collecting longitudinal data on the learning biographies ofadults, retrospectively through life history interviews and in real time through repeated interviews over time. In addition,15 waves (1991-2005) of the ongoing British Household Panel Survey (BHPS) are being analysed (wave 15 will be released in April 2007). An iterative relationship has been established between these two data sets, the qualitative collected within the project by project personnel and the BHPS which is considered to be one of the most authoritative British survey data sources.
A central objective is to unravel the relationship between learning, identity and agency over time. This involves studying how adults respond to periods of routine and structural and incidental life course events and turning points and the consequence of their responses for who they are or aspire to become, their capacities to exert control over their lives and their learning. It also involves exploring the ways in which responses and their consequences vary in accordance with age, cohort, historic period, social class, gender, ethnicity,race, educational, occupational and economic status, and geographical location.
In the quantitative part of the Learning Lives project we are using a statistical technique developed by Ross Macmillan and his colleagues at the University of Minnesota (see, for example, Macmillan and Eliason, 2003; Macmillan and Copher, 2005)to probabilistically map the life course in terms of trajectories or pathways of social roles over time. This involves exploring how changing role configurations over timeinteract with learning, identity transformation and agency. Probabilistically mapping the life course involves exploring the extent to which one can accurately predict an individual’s learning trajectory on the basis of characteristics largely known by the time the individual leaves initial phase full time education. If we find this to be the case it does not imply that human agency or life crises cannot impact upon trajectories but rather that human agency and experience occur within a framework of opportunities, influences and social expectations that may or may not be determined independently. We hope our analysis will contribute to an understanding of human agency and its interplay with society’s institutions in the shaping of learning biographies over time.
Conceptualising the life course as probabilistic whole represents a change in approachfrom whattypically went before as traditionally researchershave tended to dissect the life course in order to study some specific aspect such as the transition from school to work or the timing of marriage, or of first entry into parenthood. In the Learning Lives project we are using both approaches to help us towards developing a theory learning and identity transformation in the life course. Dissecting the life course allows us to study individual components of the life course out of context such as the occurrence, timing and sequencing of social experiences for different age groups or cohorts. Studying the life course as a whole allows us to treat the life course as a social context in its own right.
In this paper we take the former approach by dissecting the life course in order to studywhether and, if so, when a cohort of full time initial phase education leavers returned to adult learning and the individual characteristics that made their return more (or less) likely. We focus in on a sample of 1997/8 leavers in England and track them for a six year period in order to answer the following questions:
- How long does it take them to return to adult learning?
- Can we predict the likelihood of an early return from a selection of time invariant and time-varying characteristics?
Theoretical and methodological considerations
In taking alife course perspective to study learning and its inter-linkages withother aspects of the learner’s life,we draw on Elder’s (1985) conceptualisation of the life course as a series of interlocking trajectories or social role pathways over time. Trajectoriesare seen as longitudinal involvement in or connection to a social institution such as work marriage or parenthood. Movement through a social institution normally involves taking onan institutionally defined role such as being a student, an employee, a husband or wife, a mother or father with each role configuration giving an indication of the extent to which a particular individual is embedded in a given social institution over time. Entry into (or exit from) from a social role is normally characterised by an event such as starting a new job, a wedding, a birth, a divorce, resigning, retiring. The specific event that moves an individual into or out of a life course institutional context is referred to as a transition. Transition points indicate when a particular social role begins, ends, how long it lasts.
Methodology and methods
These two concepts, trajectories and transitions, are central to life course research as they provide useful methodological tools for identifying transition points as the life course unfolds. Our methodological approach in this paper is discrete time event history modelling which is basically measuring the interval between two well defined events, in this case leaving initial phase education and returning to adult learning.
Data and sample
Our source of data is the British Household Panel Survey (BHPS) waves 8 to 13 (1997-2003). The BHPS uses a representative sample (5000+) of UK households resulting in 10,000+ individual interviews. Our sample was made up of all BHPS respondents living in England who had left initial full time education at some point between wave 7 (1997) and wave 8 (1998). 463 individuals aged between 16 and 23 (at wave 8) in England who at the BHPS 1998 interview (wave 8) were recorded as not being in full time education but who were recorded as being in full time education at the 1997 (wave 7) BHPS interview were deemed eligible to enter our sample. Because the BHPS interview takes place between September and November each year, these 463 individuals could be said to have left initial full time education at some point between September/November 1997 and September/November 1998.
Event history analysis
How long it takes a leaver to become a returner might seem a straightforward enough question. Yet it is a question that is fraught with methodological difficulty. Event occurrence represents an individual’s transitions from one “state” to another. In this paper state one is represented as “being a non-returner” and state two is represented as “being a returner”. Our methodology does not permit definition overlap. In order to track the occurrence of an event and its timing, the state of being a non-returner and being a returner must be mutually exclusive such that each member of our sample can only occupy one of the two states at a given point in time. As our interest here is in whether a target event occurs at all during the period of observation and, if it does, when it occurs during that period, we must have a clear definition of our target event that will allow us to make a clear distinction between each state. This condition must be met so that we can pinpoint the timing of the transition if and when it occurs.
Our target event (dependent variable)
Thetransition point of central interest was moving from being a leaver to “being a returner”. As pinpointing this transition isprimarily a measurement issue precision and clarity is essential. To achieve this we had to settled for a definition of ‘being a returner’ that would unambiguously indicate what constituted one state and what constituted another.We operationalised our target event as “return to adult learning for the first time” by using one BHPS item requiring a “yes” or “no” response which was asked at all waves since 1998. That question was:
(Apart from the full-time education you have already told me about) Have you taken part in any other training schemes or courses at all since September 1st [the previous year] or completed a course of training which led to a qualification? Please include part-time college or university courses, evening classes, training provided by an employer either on or off the job, government training schemes, Open University courses, correspondence courses and work experience schemes. (interviewees were instructed not to include leisure courses)
In settling for this definition we fully acknowledge its limitations in that it represents only a very particular subset of adult learning. However, we judged that this question represented a meaningful basis for our analysis because it tapped into a wide range of adult learning provision leading potentially to the full range of qualifications available to adults studying in Englandfrom the lowest to the highest.
Measuring the passage of time
All members of our sample were asked the above question in1998, 1999, 2000, 2001, 2002 and 2003. Our interest was purely in identifying the first time they answered “yes”, or more precisely, the first BHPS wave at which they answered “yes”. For example at wave 8 (1998), our sample of leavers who had left school at some point between this wave and the previous one were asked “……..Have you taken part in any other training schemes or courses at all since September 1st1997 …….” Thus they were being asked to reflect back on the year in which they had left initial full time education and say whether they had had any spells of adult learning formally organised on a part-time basis since they had left. Those who answer “yes” leave our sample at this point because they have experienced our target event and are thus no longer eligible to experience it for the first time again. Those who remain have their wave 9 (1999) responses examined. If they answer “yes” at wave 9 they leave, if “no” they remain in the sample and so on until we reach a wave where they answer “yes”. If they had not answered “yes” by the 2003 BHPS interview they were ‘right-censored’ meaning they left at the end of the period for which information is available having yet to experience the target event.
The metric for recording the passage of time is BHPS waves, that is, one yearly discrete time intervals from September 1, 1997 or the point thereafter when they left initial full time education prior to the 1998 interview. This is because the “beginning of time” in this paper is the point at which sample members became eligible to experience the target event. According to how we defined our target event, it could not happen until after completion of full time initial education. There is thus no ‘left-censoring’ meaning everyone is in state one at the “beginning of time” because each individual in the sample is a non-returner until they become a returner.
As we do not know precisely when between wave 7 (1997) and wave 8 (1998) respondents actually left full time initial education, this means that in year 1 (1st Sept 1997 – 1998 BHPS interview date) members of our sample could have had a longer or shorter period of eligibility to experience the event. For example, someone who left initial full time education on 1st October 1997 would have been eligible to experience the event from that date to the 1998 interview date, whilst someone who left initial full time education on 31st July 1998 would only have been eligible from that date to the 1998 interview date – the latter period being a substantially shorter period than the former and both being less than one full year. Also for this initial discrete time period the data do not allow us to differentiate between participation pre and post leaving, should the former have occurred.
Time invariant and time varying predictors(our explanatory variables)
Our theoretical perspective dictated that time invariant (i.e. those that remain constant over time) and time varying (those that can be subject to change over time) predictors were important to study as decisions to participate (or not to participate) must be seen alongside the complexities of the social context in which individuals find themselves at a given point and place as well as their personal and social background characteristics. By including time-varying predictors we can study how social role changes over time shape the likelihood of participation in adult education.
Time invariant predictors are relatively straightforward to identify as they describe those stable characteristics of an individual like their gender or some other static status such as qualifications at a given point in time which remain immutable over time. The ones we use here are gender and various background characteristics such as qualifications at the point of leaving and occupational status, household per capita income and household tenure during the first year from leaving.
Time varying predictors are more complex as they are those values that may differ over time and are frequently subject to natural change such as moving from school to work. To help us identify these we draw on Elder’s (1985) conceptualization of the life course as a series of interlocking trajectories of social roles over time alluded to above. Our interest was in identifying specific events that moved an individual into or out of a life course institutional context to identifying the value of a time-varying predictor at a given point as our samples lives unfolded. We reasoned that family and work related role changes were likely to influence the social context of the life course, the varying predictorswe use here are movement from paid employment to labour market inactivity, entry into marriage or cohabitation and procreation (birth of first child). Our intention was to study how experiencing these role transitions impacted upon decisions to return or not to adult education.
Models and statistical methods
As the possibility of each sample member experiencing the target event, is in discrete 12 month intervals or periods of time (BHPS waves), a discrete event history model is appropriate for our analysis. The application of regular statistical tools such as means and standard deviations is, however, inappropriate. This is because there are individuals for whom information on the occurrence and timing of the event is not available and excluding these cases would produce misleading results. To get round the problem of right censored cases (i.e. cases who leave at the end of the observation period without having experienced the event) three new statistical ways of summarising data are introduced: the hazard function, the survival function and the median lifetime (Singer and Willett, 2003). The terminology surrounding time duration methodology, such as survival and hazard functions, has mainly come from its two main areas of application, medicine and economics, where the first event is called the original event and the second is typically referred to as death or failure. Medical researchers are interested in how long patients survive after treatment.
The main tool for describing event occurrence is the ‘life table’ which provides three key statistics: the median lifetime, the hazard function and the survival function. The median lifetime identifies the point in time at which half the sample members are estimated to have experienced the target event. The hazard function assesses the risk of the target event occurring among those eligible to experience it within each discrete time period. The survivor function assesses the probability that a given individual will survive from one discrete period to the next without having experienced the event.