Creating tools for ESG

The first step in the Semantics analysis, as with Specialization, was immersing myself in the data by reading and characterising different ‘constructing findings’ components across the sample. Drawing on my theoretical knowledge of Semantics, as well as features illuminated in other studies, such as Bloom’s Taxonomy (Krathwohl, 2002) and Paré's (2011) account of supervisor feedback on doctoral writing, I made notes of any instances in the writing that shifted the context-dependence of the knowledge. For example, if candidates described their own context and then compared it to another study, I noted the movement in the knowledge as relating to context-dependence. This process produced a list of empirical characterisations of the moves in writing – referred to as ‘discursive strategies’, such as ‘makes an interpretation’, ‘quotes directly from data’, ‘explains data by using other scholars’ ideas’, and so forth.

Different dissertations and examples were considered until the list of descriptions exhausted the options (i.e. until the list was able to account for all features presented in new texts).

Once a list of discursive strategies had been identified, I used my theoretical knowledge of Semantics to understand these different moves in texts as shifts in ESG. This second step in the analysis involved organising the different descriptions according to strengths of ESG so that different categories could be defined. To do so, I followed a similar process to that undertaken by Maton and Doran (2017b) for ESD. In the first instance, I set up a continuum for ESG, establishing a distinction between stronger ESG (ESG+) and weaker ESG (ESG–). Once this distinction was made, I went back to my empirical descriptions and sorted them into either ‘ESG+’ or ‘ESG–’ groups, noting the reasons for assigning them into the relevant group. This process of allocating descriptions into two groups enabled me to understand a major distinction in the context-dependence of knowledge being enacted: the knowledge was either bound to the context of the study at hand, or it drew on knowledge from outside the immediate context of the study (i.e. from other studies or from theoretical frameworks etc.). This enabled me to distinguish two ‘types’ of ESG along the continuum, context of study and contexts beyond

study, as demonstrated in Figure 4.1.

Figure 4.1. Division of ESG continuum into 'types'

Following the first division, I then considered the different descriptions within each category, ordering them according to strengths of ESG within each ‘type’. Within the first type, context

materials8 (e.g. quotations from interview transcripts, numerical data, reproduced images etc.) to be included in the writing, such as through descriptions or quotations, and others that focused more on developing an understanding of the materials using the candidates’ own knowledge. I could thus distinguish between two ‘subtypes’ within context of study, which were labelled

reproducing and understanding respectively. Within the second type, contexts beyond study, I

considered all the strategies that looked beyond the immediate context of the study. These included strategies that drew on existing knowledge from other studies or frameworks as well as those that produced generalizable understandings of the materials as a whole in relation to other contexts. I was thus able to distinguish between two ‘subtypes’ within contexts beyond

study, which I labelled broadening and advancing respectively. These four different ‘subtypes’

are illustrated in Figure 4.2.

Figure 4.2. Division of ESG 'types' into 'subtypes'

Following a similar process, the four ‘subtype’ levels were then further scrutinised to see whether a distinction could be made between different strategies within this level. Starting with strongest ESG, the ‘subtype’ of reproducing included strategies for quoting directly from the materials as well as strategies that enabled candidates to provide summarising descriptions of their materials. A distinction was therefore made between ‘sub-subtypes’ of presenting and

summarising. At the ‘subtype’ level of understanding, a distinction was made between

strategies that produced understandings by interpreting instances of materials and those which

8 _{‘Materials’ is used as a more inclusive term as opposed to ‘data’, which is seen to impose a set of assumptions}

created understandings by generating more generalised claims about the materials. Two ‘sub- subtype’ categories of interpreting and claiming were thus created.

Within the ‘subtype’ of broadening a distinction was made between strategies that drew on the findings from existing research, often for contrastive or supportive purposes, and those which reached out to more abstract knowledge such as theoretical or methodological frameworks. These differences were defined as ‘sub-subtypes’ of bridging and branching respectively. In the same way, the relatively weakest ‘subtype’ of ESG, advancing, was further distinguished into two further ‘sub-subtypes’, generating and theorising. These distinguished between strategies that produced empirical generalisations about the materials as a whole, offering insights and implications for other empirical studies in the wider field, and those that offered theoretical or methodological implications for existing frameworks in the field. The recursive division of the four ‘subtypes’ into eight ‘sub-subtypes’ of ESG is illustrated in Figure 4.3.

Figure 4.3. Division of ESG 'subtypes' into 'sub-subtypes'

As suggested in Figure 4.3, the level of delicacy or detail that one can measure is (in theory) infinite. The level of detail used depends on the needs of the study on hand. Considering the pedagogic goals of the research, delving into the detailed ‘sub-subtype’ level was considered important for the development of scaffolding tools and models as each sub-subtype of ESG is considered to play an important role when constructing findings, as the thesis will show in later

chapters. The process of how these strategies were identified, as well as how they are defined, is described at length in Chapter 7.

Once the different strategies had been defined and organised in terms of categories of ESG they were developed into a translation device for analysing shifts in context-dependence in texts. The translation device for ESG is presented in Table 4.5.

Table 4.5. Epistemic-semantic gravity translation device

ESG– ESG+ CONTEXTS BEYOND STUDY ADVANCING THEORISING GENERATING BROADENING BRANCHING BRIDGING CONTEXT OF STUDY UNDERSTANDING CLAIMING INTERPRETING REPRODUCING SUMMARISING PRESENTING

The translation device for ESG presented in Table 4.5 is essentially the outcome of the analysis presented in Chapter 7. For this reason, the different categories are not described in detailed or discussed here, as Chapter 7 provides considerable space detailing the process of its creation. Chapter 8 enacts the translation device on select examples to illustrate its utility for analysing context-dependence in texts.