La asimetría en el grado de autonomía

Focus groups were chosen because they can provide more in-depth details than questionnaires, and, through dialogue and group discussion, can explain issues or indeed raise issues not previously considered. A strength of focus groups is that actual words of participants, without the mediating effect of the research instrument (i.e. the questionnaire) can be used to ascertain their thoughts and feelings around a topic (Krueger & Casey, 2014). Whilst this is also true for one-to-one interviews, the peer group setting was thought to offer teenage learners a more comfortable and familiar environment than a one-to-one interview with a previously unknown adult. Moreover, focus groups are more time- efficient as they allow for several learners to be interviewed at the same time. Thirdly, from a constructivist perspective, conducting the focus groups constructs meaning in itself through the process of interaction between the researcher and the participants, and the participants with one another. In this way, the emergence of a different angle on how learners view German-related issues may be encouraged through the format of the focus group.

97

The focus groups were designed to offer an opportunity to explore learner motivation in more depth than the questionnaire. Therefore, two identical tasks to some questionnaire sections were included (Appendix A): the metaphor elicitation ask (section A) and the Family Fortunes task (section B). The schedule also included a task called Alien

visit, for which learners were asked to describe to an alien who knew nothing about life on

earth what the words ‘German’, ‘the Germans’, and ‘Germany’ mean. This task was designed to elicit learners’ thoughts around these key terms when they discussed their answers within their peer group.

4.3.3. Case studies

Learner case studies can be helpful in that the data can be drawn together at idiographic level from the quantitative and qualitative data from the questionnaire and the focus groups, and this can be useful to do justice to the complexity of an individual learner’s motivation. Fisher (2013a,b) has demonstrated how the exploration of selected learners’ motivation at a more in-depth level can be helpful for a more nuanced analysis.

4.3.4. Interviews

Interviews with the German teacher and the head teacher (Appendix B) were intended to paint a more complete picture of discourses around German at a particular school.

Teacher and head teacher interview schedules included the same tasks as the focus group schedule which also featured in the learner questionnaire: Family Fortunes and the Metaphor task. It also included the Alien visit task (4.3.2. above). Using the same tasks for the learner focus groups and the teacher and head teacher interviews was intended to generate data which could then be compared across data sets. The staff schedules were adapted slightly to reflect the interviewee’s role, for example the teacher schedule asked

98

what teaching German (as opposed to learning German) was like. The head teacher schedule omitted items which referred to teaching German.

4.3.5. Lesson observations

In a school setting it can be difficult to obtain data of naturally occurring discourses around German. The chances of generating enough data for the main study by recording ‘language’ in a purely ethnographic manner would simply be too low, which is why the questionnaire and interviews were designed to elicit discourses around the object of study. However, lesson observation were planned in order to get an idea of how German is talked about by learners and teachers in the classroom without any stimulus. For this, the possible impact of research taking place in the classroom on the behaviour of the participants was reduced as much as possible by not video or audio-recording the lesson, but rather through the researcher sitting quietly at the back of the classroom and making field notes as a non- participant observer (Cohen et al., 2011). A semi-structured, ‘pen and paper’ observation schedule would be used to record participants’ classroom talk around German (teacher- student interactions as well as student-student interactions) as and when it occurred, supplemented by notes which recorded the structure of the lesson.

4.3.6. Press corpus

Linguistic corpora consist of large amounts of digital texts, which can be used as an evidence-based data source in order to identify which language patterns are typical. For the purposes of the study therefore, a specialised searchable corpus which represented public discourses around German* was required. For this the place, the time, and the genre of the corpus data had to be specified (explained under 4.2.1.4. above).

The corpus was used as an empirical method to identify discourses around German*. The claims made about the nature of this discourse were based on evidence

99

drawn from large amounts of data, which should contribute to the credibility of the study. Relatively recent advances in technology mean that in corpus linguistics, previously unimaginably large amounts of data can be harnessed and then investigated with digital tools, which can compute extremely complex analytics. The results may reveal linguistic patterns which would otherwise have remained invisible, thus providing an evidence-based reference point.

The tendency for words to systematically co-occur is known as collocation. Taking a closer look at the nature of collocates may reveal speaker attitudes. The evaluatively loaded relationship between a word (or more specifically, a word form, or lemma) and a set of semantically related words is known as discourse prosody. Sometimes the terms ‘semantic prosody’ or ‘pragmatic prosody’ are also used; in the current study, following Stubbs (2002) ‘discourse prosody’ will be used for “a feature that extends over more than one unit in a linear string” (p. 65). In Stubbs’ famous example, the verb ‘to cause’ shows a negative discourse prosody, whereas ‘to provide’ collocates with positive words (Stubbs, 2002).

A corpus can also add to the accountability of the study by minimising researcher fallacies such as confirmation bias, primacy effect, and hostile media effect (Partington, Duguid, & Taylor, 2013). These relate to often subconscious biases in decision-making regarding data selection: evidence in confirming one’s conviction can be favoured (confirmation basis), information encountered first may be weighted more heavily (primacy effect), and, particularly relevant for the media element in the current study, media coverage can be seen as biased against one’s own ‘cause’ (hostile media effect) (Baker, 2006). However, whilst the principle of total accountability is generally applied and accepted in Corpus Linguistics (McEnery & Hardie, 2012), one must be aware that the corpus for this study is by necessity restricted to an arguably subjective selection of data of wider discourse. In addition, whilst the corpus was used as evidence for phenomena

100

regarding discourses around German*, the absence of a phenomenon does not mean that this phenomenon does not exist outside the data selected for this study. The corpus was used with the online corpus analysis tool Sketch Engine in order to identify language patterns contributing to dominant as well as more hidden discourses around German*.

Researchers disagree on the effect of mass media on individuals. A constructivist, discourse-oriented approach would take the view of cultural effect theories (e.g. Williams, 2003) whereby the effects of the media on individuals might not be immediate but rather constructed over time, leading to embedded, easily-recognisable stereotypes (Grix & Lacroix, 2006). Whether a relationship between media discourse around German* and that of school-age learners can be established, is addressed by research question 4. Whether learners actually read the papers themselves is therefore not regarded as important. In fact, it has been reported that because non-newspaper readers are closer in demographics such as age and social class to the country as a whole, non-newspaper readers’ views are closer to the average national view than those of readers of particular newspapers (Duffy & Rowden, 2005). This means, based on the assumption that learners in the study actually do not read the sampled newspapers, their views as non-newspaper readers would be closer to the majority views in the country, than if they did read newspapers. Baker, Gabrielatos, and McEnery (2013) make the point that in today’s world, where controversial stories are widely publicised online via social media, the image of the loyal newspaper reader who regularly purchases periodicals seems outdated. Having said this, online newspaper articles can also be widely circulated via, for example, social media.

Regardless of the extent to which newspapers might have an opinion-forming effect on the participants of this study, possibly also via the reading behaviour of their parents and carers, the purpose of the newspaper corpus here was to provide a snapshot of wider discourses currently in circulation.

101

Corpus studies have been accused of disregarding context (e.g. Mautner, 2007), in contrast to discourse analysis, which is characterised by a focus of language in context (e.g. Partington et al., 2013). In order to do justice to the complexity of the discourse- orientated view of language taken in this study, methods from both corpus linguistics and discourse analysis were used, and quantitative as well as qualitative methods were

employed to analyse the data. The discourse approach is useful for analysing the corpus (and other) linguistic data as it views language as social practice and asks questions about context, and aligns with corpus-assisted discourse studies (CADS, Partington et al., 2013). Table 4.4. below shows details of Strand 2 (wider discourses) research instruments and data.

Table 4.4. Public discourses research instrument and data Research

instrument

Data source N articles N tokens/words Time of data collection

Press corpus Selection of UK national newspapers articles around German* (1 January 2012 – 30 April 2015) 40,169 tokens1: 35,959,493 words2: 30,376,325 April 2015

1 _{Individual occurrence of a word.} 2 _{A word form (identical words are only counted once).}

4.4. Pilot Study