THE DEVELOPMENT OF THE CONCEPTUAL MODEL

This current research was started in 2003 and built upon the previous study. A conceptual model was initially developed to help the researcher make sense of the factors influencing subject choice. Possible influences on subject choice were derived from literature

searches and discussions with teachers or teacher educators.

Figure 3.1 A General Framework for Guiding Leadership Effects Research

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A paper by Leithwood and Levin (2005) on ‘leadership’ provided initial ideas for the model (figures 3.1 and 3.2). This section will discuss how this model was developed and three elements of the model (student decision making, curriculum creation and subject department influences) were conceptualised.

Figure 3.2 Framework for the Wallace-supported leadership

study

Leithwood and Levin (2005, p.38)

The general framework helped with understanding the potential complexity of the factors that can influence decisions and actions in a school context. The relevance to this study is

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that while the student is the person who makes the decision about the subjects they want to study, they do it within a context that is constrained by the decisions and actions of others. For example government policy on the curriculum, qualifications or accountability measures influences Senior Management and Governors in their decisions about the subjects to offer in a school. This model also provided a range of potential areas to investigate, many of which have been subsequently ignored as beyond the scope of this study.

The way that this general model could be developed for specific studies was of particular interest. Of the three models produced by Leithwood and Levin, figure 3.2 was deemed especially relevant because it began to identify some of the influences on different groups of people in the school system that could be investigated. One of the biggest issues has been to limit the focus of the study when all areas are potentially interesting and influential.

The model gradually evolved to its current form (figure 2.6) through an iterative process of identifying factors in the literature and testing in the field. Literature in fields as diverse as subject choice, government policy, school management and learner motivation were important sources of ideas. The intention was to identify as wide a range of possible Influences with the intention of narrowing the focus later. The outcome was that influences were identified at National, Local, School, Department and Individual levels with shifts in emphasis over time. Early versions of the model were presented to a number of different audiences (teachers, teacher educators,

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school’ managers, researchers) to test its veracity and applicability in different contexts (Weeden, 2005b; Weeden 2006a; Weeden, 2006b). The underpinning principle of the model was that while the framework has validity in aiding overall understanding of the processes involved, each institution provides a unique site within which the different influences interact in complex ways.

The model conceptualises the complexity by showing the nested and overlapping nature of contexts within which individual student decisions are made. It shows that while the student is at the heart of the process their ‘choice’ may be constrained by the influences operating within an individual institution. The ideas for these influences came from many different sources including research and practitioner literature, teachers and school

management teams, official documents from bodies such as DfES, DCSF, DFE, QCA, Ofsted, Ofqual, JCQ, awarding bodies, personal experience of teaching, governors meetings and educational news.

The conceptualisation of potential links between three aspects of the model (students’ decision making, teacher and department effects, the creation of the KS4 curriculum) will be outlined because they played an important part in decisions about types and methods of data collection.

Student decision making

The literature suggested one potential line of study was the factors that influenced pupils’ decisions to study subjects, especially geography, at GCSE. This could look at their

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motivations and aspirations, perceptions of geography as a subject, their experience in lessons, their ability in the subject and the advice they received when making choices. A further useful incentive to conduct a detailed research review of this area arose because the Royal Geographical Society commissioned a research report when bidding for

government money to support the Action Plan for Geography (Weeden, 2005a) which was later developed into an article for the journal ‘Geography’ (Weeden, 2007). One result was a conceptual diagram of influences on student decision making (Figure 3.3).

Figure 3.3: Variables affecting student decision making

The research review suggested that compared with some other potential research strands this was relatively well understood with previous studies reaching consistent conclusions (Stables, 1996; Adey and Biddulph, 2001). A decision was made that this was not going to

Liking for subject Perceived usefulness and importance of the subject Ability Student decision making Parental advice Teacher advice Interesting lessons and activities Employment Life skills Difficulty of subject messages over time

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be the main priority for the study. However it was also felt that it was important, in a study about student choice, that the student voice was heard. Potential data collection methods were therefore identified such as interviews, questionnaires, observations and school performance management data. It was also recognised that an in depth

investigation of these influences was likely to involve spending considerable amounts of time in schools working alongside students and gaining access to parents, teachers and others that might be logistically problematic.

Ethical and practical considerations played a part in the decision to limit this aspect of the study. The researcher was not working in a school but a university so day to day access to students was limited, although there was the advantage that over a year there was contact with 20-30 different schools and departments through Initial Teacher Education visits. However access to students would have to be negotiated with schools along with the appropriate ethical approval.

The ethics of asking students about option choices was only problematic if the questions asked were inappropriate. There was therefore a choice to be made – should the

questions be restricted to factual data about the subjects chosen aspirations and attitudes to subjects or should they explore some of the potentially more interesting questions about the personal lifestyles of students and their families? Some of this data is collected by organisations such as the Centre for Educational Measurement (CEM, 2011) through their Midyis, Yellis and Alis programmes and has been used to look at the effects of different social indicators on subject choice (Davies et al., 2008), but at the start of this

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study, when making decisions about research foci there was limited knowledge of this data source and its potential. While aware that senior managers and departments have access to this sort of data for use in individual schools it would require considerable negotiation to obtain access to the data for an external researcher.

Investigating students likes or dislikes for subjects and attitudes towards teachers might be problematic because students might want to express strong views about particular teachers. However this issue could be resolved if it was made clear to schools, teachers and students that comments should be generalised and that any information collected would be confidential to the researcher. The outcome was that the student voice would be limited to a small number of case studies using questionnaires and interviews to act as triangulation for data collected from other sources. This data would be placed in the wider context of the school situation and would seek to confirm or challenge data from previous studies.

Departmental influence

The literature review suggested a number of ways that departments might influence student choice (Figure 3.4).

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Figure 3.4: Departmental influence on students’ choice of geography

This was a problematic area for data collection. To obtain information about many of the identified influences would involve observing lessons, examining schemes of work and resources, talking to students about their experiences and collecting data from senior management. In the end it was decided to limit data collection to a small number of case studies of good departments using discussions with teachers and pupils to infer reasons why departments were successful or not (see section 3.5 for details of this process). This again therefore became a more limited area of the investigation.

Some data collection on departments was opportunistic. It became possible to collect data about departmental change, attitudes to different pedagogies and subject content when the QCA subject officer offered to provide access to a group of teachers from two Local Authorities at an annual monitoring meeting. In addition there was an opportunity to

Choose to study Geography? KS3 geography curriculum experience Quality of Resources Previous geography GCSE results Views of older pupils Quality of teaching Quality of geography department ‘Promotion’ of geography Positive experience Negative experience

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create an appendix for QCAs annual monitoring questionnaire (appendix 4). The design of the questionnaire is discussed in section 3.5. This opportunity coincided with decision making about the selection of a sample of Case Study Local Authorities to study in more detail and as a result these two LAs became part of the detailed study. The questionnaire was then sent by post to schools in the third LA selected.

As the study developed a number of other opportunities presented themselves to collect data from groups of teachers about changes to the curriculum. These were used to develop ideas and collect data. In most cases the data collection was opportunistic utilising pre-existing teacher group events to collect data, often in relatively informal ways. This provided a ‘richer’ source of data about some of the factors in figure 3.4 and helped develop understanding of the developing issues in schools. The sample of schools was often unrepresentative because they were schools that were in partnership with the teacher training institution and therefore likely to be more successful than most schools. One further opportunity for data collection was ITE visits to partnership schools. These were used to keep track of issues that were emerging in different departments and the trends in entry patterns.

Influences on the curriculum

When this research was started there was little knowledge of the pattern of entries for different subjects but there was anecdotal evidence of the pressure on some schools to change their curriculum. The initial study showed evidence of diversity in geography entries by school type and the discovery of the Newsam classification of schools (Newsam,

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2003) was highly significant because it provided an alternative classification that confirmed personal experience.

Figure 3.5: Influences on the curriculum at the national and school level

A conceptual diagram was developed to identify these national and local influences (figure 3.5). Increasingly accountability proved a driving force in changing the curriculum and this study used both entry data and case studies to explore different aspects of entry patterns as schools became more strategic in planning their KS4 curriculum.

The area of policy making was of considerable interest and the growing availability of national secondary data on examination entries provided an opportunity to look at the influence of policy on decision making in schools. Initially access to this data was thought to be a problem because much of it was confidential to schools but over time it became clear that anonymised data for individual students was available in the National Pupil Data Base (NPD) and Pupil Level and School Census (PLASC). This data was a rich source of

School option systems Changes to national curriculum The school curriculum Extended core in 1995. Removal of requirement to study History or Geography More subjects offered Students study more subjects Specialist school status Schools student intake

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information. There were limitations, which will be discussed in the data analysis section, but because it provides data for the whole population of students in England it provided previously unavailable information and allowed investigation of geographical and school patterns of entry.

The limitations of the secondary data were that it did not provide insights into the realities of the situation in individual schools so it was decided to collect this data through case studies and opportunistic conversations and data gathering exercises with teachers. This data would be used to provide ‘richer’ insights into the realities of the situation in schools. The limitation of teacher’s perspectives was recognised but allowed triangulation of the findings from the national statistics.

These influences were tracked over time because changes to exam entries reflect

historical events. A KS4 course generally takes two years and subject choices will be made six months before that. It may take several years for policy changes to have an impact in schools so data was needed that could track changes over time. The collection and

publication of exam entries at different scales provides this sort of data set although direct correlations need to be treated with caution. The NPD and PLASC data sets provide

individual student data that can be analysed at both the local authority and school level. It provides a time series that could be analysed in a number of ways to answer some of these questions. At another level the case studies and teacher data provided an insight into the reasons for changes in individual schools. This latter data may be limited because teachers often only have a partial view of what is happening in their school, especially if

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they are not involved in decision making at senior management level. How this data was analysed is discussed later.