THEMATIC ANALYSIS Clause Samples

THEMATIC ANALYSIS. Thematic analysis is a much used method of analysing qualitative data. This approach is based on identifying themes emerging from the data as you analyse it. The method does not consist of a step by ▇▇▇▇ ▇▇▇▇▇, and tend to vary with the researcher. ▇▇▇▇▇▇ (2012:580) states that the method “does not necessarily tell the user how to identify themes, which (…) are likely to reflect the analyst’s awareness of recurring ideas and topics in the data”. ▇▇▇▇ and ▇▇▇▇▇▇▇ (2003:88) explain how themes can emerge “both from the data (an inductive approach) and from the investigator’s prior theoretical understanding of the phenomenon under study (an a priori approach)”. In this study of environmental goods and related topics, some themes and concepts have been identified through exploring the theoretical framework. Themes identified before the data collection, together with the new themes emanating from the collected data, forms the themes for final analysis. The researcher’s chosen topics, the way of retrieving information and the interview guide is “a rich source of a priori themes” (Ibid.). To identify themes from the data in the analysis, one should look for repetitions, indigenous typologies or categories, metaphors and analogies, transitions, similarities and differences, linguistic connectors, missing data and theory-related material (▇▇▇▇ and ▇▇▇▇▇▇▇, 2003). Using these identification tools can give a large number of codes or initial themes. According to ▇▇▇▇▇▇ (2012:580), identifying themes requires the researcher to work on the codes further and to “gain a sense of the continuities and linkages between them”.
THEMATIC ANALYSIS. For the analysis, main themes that appeared when coding the interviews are examined, special features or unexpected opinions, similarities and differences are highlighted are summarised. Knowledge is a theme that stood out through all the interviews. This was not a topic delivered by the interview guides, and is interesting because of the link between knowledge and credibility, as seen in the theory of perceptions of trust and credibility by ▇▇▇▇▇▇ et al. (1997). One element was notions about lack of knowledge among a group of people, or impressions about their own level of knowledge. Some of the interviewees expressed lack of familiarity with the sustainable development goals, while others mentioned how knowledge of a concept or phenomenon such as environmental goods was limited. One example is ▇▇▇▇▇▇ ▇▇▇▇▇ from the ICSTD, who mentioned in her interview how the industry that produce and provide environmentally friendly technology and products are not necessarily sure about what services should be liberalized because they lack understanding of which services are relevant. The reception, use and inclusion of knowledge and research in the EGA is where the theme “knowledge” is most relevant for this study. Through the interviews with ▇▇▇▇ ▇▇▇▇▇ and ▇▇▇▇▇ ▇▇▇▇▇▇▇ we learned how research such as the NTNU study of Development EGs is received by the EGA members and, according to ▇▇▇▇▇, included directly into the process of nominating goods. ▇▇▇▇▇▇▇ describes WTO members’ reactions to the presentation of the report as appreciative and grateful, and state that “to hear that the Norwegian delegation had already used some of our ideas and incorporated them in negotiations already was encouraging”. The connection between the ICTSD and the EGA initiative is strong, and ▇▇▇▇▇ stated that the organization use their research and dialogues with experts and stakeholders to try to inform the EGA. ▇▇▇▇ ▇▇▇, from MDIR, thinks that having a solid knowledge basis is fundamental for making political decisions. Research on whether a measure has the desired effect is necessary to decide on future policy and actions. According to Vik, documentation of the product’s positive effects on climate and environment should be available for it to be nominated as an Environmental Good. ▇▇▇▇▇▇ ▇▇▇▇▇▇ from the Norwegian Society for the Conservation of Nature (Norges Naturvernsforbund (NNF)) calls for more political management regarding which research and development (R&D) topics and projects sh...
THEMATIC ANALYSIS. In addressing the third research question, thematic analysis (▇▇▇▇▇ & ▇▇▇▇▇▇, 2006; ▇▇▇▇▇▇▇ et al., 2003b) was conducted to explore when and how the social forms of metacognitive regulation episodes, identified within the analysis of video and stimulated-recall interview data, were initiated by the students or the teacher during scientific inquiry activities. In this analysis, in line with the stages of thematic analysis suggested by ▇▇▇▇▇ and ▇▇▇▇▇▇ (2006), I read through the transcripts and viewed the video recordings in order to familiarise myself with the data set and gain a sense of it as a whole. Next, I identified and described the utterance(s) and/or nonverbal action(s) which appeared to be the initiating moment of each social form of metacognitive regulation episode. This process involved creating and noting down the initial codes inductively for the episodes in the data set. After this initial analysis, I looked again at these initial codes, and started to sort them into the potential themes. This was followed by reviewing and refining all the themes, whereby they were checked in relation to all the coded episodes as well as the entire data set. Finally, the last stage involved creating clear descriptions and names for each of these themes. All the themes that emerged from the data were discussed with my supervisors and another researcher with the purpose of confirming the veracity of the analysis. Thematic analysis was also used for the analysis of the semi-structured interviews conducted with the target students with the aim of exploring their attitudes, beliefs and perceptions about the scientific inquiry activities they engaged in. Using a similar analysis procedure to that recommended by ▇▇▇▇▇ and ▇▇▇▇▇▇ (2006), firstly, I transcribed the interviews verbatim and read through the transcripts carefully to gain a general idea of their content. Next, I created and noted down initial codes inductively for the student’s responses, and sorted these codes into the potential themes which were later reviewed and refined iteratively (see Table 3.6 for an analysis example). The final themes that emerged from the interview data were as follows: ‘personal achievement goal’, ‘friendship’, ‘leadership’, ‘roles within the group’, ‘ideas about the role of group work’ and ‘ideas about the role of the teacher’. All these themes were used to create a profile for each student and group, which complemented the interpretation and analysis of the observational data ...