The present study is conducted from the viewpoint of qualitative research. As Eskola and Suoranta (1998: 20-22) point out, in qualitative research the position of the researcher is different than in statistical research. In qualitative research there is more flexibility in the planning and realisation of the study. In other words, "experimental imagination" is required.
They continue that qualitative and quantitative research are sometimes opposed as subjective and objective, which can further lead to the division into inaccurate and accurate. However, as they report, it must be borne in mind that also numeric data from surveys was originally created through "soft" methods. In addition, as they point out, fundamentally the divisions are not believable and the differences are due to different perspectives. (Eskola and Suoranta 1998: 20-22.)
By using "experimental imagination", the starting point for the present study was chosen to be content analysis. According to Tuomi and Sarajärvi (2009: 91), content analysis is a basic
method of analysis that can be used for all kinds of qualitative research. The method can be applied to all kinds of verbal, graphic and symbolic data to receive new insights and to deepen understandings of different phenomena (Krippendorff 2013: 23-24). The aim is to present the examined data in a clearer form by organising the information. This is accomplished by dividing the data into parts and gathering it together to form logical conclusions. (Tuomi and Sarajärvi 2009: 108.) Like every scientific method, content analysis is a reliable and a replicable tool of analysis. Same results should be drawn when other researchers use the same approach to the same phenomena. (Krippendorff 2013: 24.)
Similarly as every method of analysis, also content analysis has its pros and cons. As was mentioned earlier, content analysis aims at presenting the examined data in a more compact form. Sometimes the researcher might present the organised data as results failing to introduce proper conclusions. This has to lead criticism about content analysis's incompleteness. (Tuomi and Sarajärvi 2009: 103.) The results of content analysis can also be extended by making quantitative calculations, for example by counting how many times something is mentioned. While this is a positive addition, it may be that producing numerical information of the usually small amount of data does not bring anything new. (Tuomi and Sarajärvi 2009: 120-121.) Adding a quantitative element to the present study was considered but I come to a conclusion that it would take too much space from the quantitative reflection.
As Krippendorff (2013: 47) points out, content analysis can also analyse large amounts of data. Smaller samples of texts may be more conventional but content analysis is not limited to them. Content analysis is also versatile in terms of the data. Examined materials are not restricted to written texts. Also images, sounds, symbols and numbers can be observed and analysed (Krippendorff 2013: 25). The final point is very relevant for the present study, as for example pictures and statistics about the UK can also be taken into account in the analysis.
According to Krippendorff (2013: 355-371), there are three different starting points to content analysis. First, text-driven analysis begins with interesting text samples, for example personal letters, comic books or family photographs. In the beginning there is no direct research question but instead it is formulated while examining the material. Second, method-driven analysis is interested in analysing data by unusual procedures, by something that has not been tried before. This method is sometimes criticised because the desire to use technological tools may overpower the desire of finding answers. Third, problem-driven analysis is motivated by wanting to find answers to a question and by believing that the data will provide those
answers. The problem of not knowing something is therefore considered to be important. The problems can be very concrete, such as layers trying to find evidence or historians trying to clarify historical events. The problems are formulated into research questions and they are answered with the help of the texts. (Krippendorff 2013: 355-371.) The problem-driven analysis is the most relevant for the present study.
Krippendorff (2013: 45-47) compares content analysis to more structured methods, such as interviews, surveys or statistical analyses, and presents their differences. Structured methods usually produce results that can be easily analysed and coded but they can also ignore the individual voices of the respondents. Content analysis, which often deals with data that has already been produced, can analyse data that is in different formats and unstructured, and therefore preserves the original voices. Content analysis is also context-sensitive in contrast to context-insensitive methods, such as surveys or statistical analyses, which take single words out of their context ignoring the original setting. Furthermore, controlled experiments, interviews and surveys are prone to phenomena, where the subjects are aware of being observed and where the situation is artificial. Researchers will also influence the participants, whether they want it or not. Content analysis is an unobtrusive method and therefore avoids such aspects. (Krippendorff 2013: 45-47.) However, also content analysis and discourse analysis, which are both qualitative text-based methods, differ from each other. As Tuomi and Sarajärvi (2009: 104) point out, content analysis observes meanings within texts, whereas discourse analysis is interested in how the meanings are produced.
So, content analysis was chosen as the method of analysis because it can be applied to written, graphic and numerical data and because it is fairly flexible. The starting point is a problem-driven analysis since the motivation of the study starts from finding answers to the research questions. In order to separate the content and to re-organise it to form meaningful results, a set of categories is needed. The following categories are adapted from the suggestions of Byram (1993), Ammer (1999) and CEFR (2001) with certain changes of my own. They were formed in order to provide a clear and varied presentation of different cultural aspects.
1) Social identity and social groups: regional identity, dialects, sub-cultures, ethnic and cultural backgrounds, social groups, occupational groups
2) Everyday life: family, living, food and drink, hobbies, characteristics of people
3) Stereotypes and national identity: stereotypes, auto-stereotypes, symbols of national identity
4) Art, science, media and sports: literature, music, art, media, sports, fashion, science and technology
5) State, politics, monarchy and economy: government, royalty, education system, society and economy
6) Land, nation and tourism: descriptions of countries and towns, geography, history, international relationships, tourist information and popular sights
7) Intercultural awareness: differences and similarities between the culture of origin and the target culture and other cultures
I started the analysis process by browsing the books to get an overall picture of the content.
During this initial examination it was noted that certain pieces of information did not fit in any category and the categorisation was altered according to the findings. The establishing of the categories was followed by a thorough reading of the texts. While reading I made notes and highlighted features while organising the content into the appropriate categories. All references to the UK where taken into account, whether verbal or graphic. Of the verbal content attention was paid both to actual text chapters as well as extra material, such as information boxes and relevant exercises. Exercises were taken into account because especially in Open Road they contain stories. The main focus was on a broader point of view but I also descended to a word level when necessary, for example when variations of spelling were mentioned. Although the study is not conducted from the point of view of image analysis, pictures referring to the UK (e.g. landmarks, maps, flags etc.) were included in the analysis.
6 ANALYSIS OF THE CULTURAL CONTENT
In this chapter the findings of cultural content are categorised and analysed. In addition to the seven categories, there is a short conclusion after each sub chapter to draw together the outcomes. The results will be discussed in more detail in Chapter 7 together with conclusions and improvement suggestions.