3.3.2.1 Methods of Data Collection. The aim of Study 3 was to explore the focal participants’ beliefs and self-reported practices of TEDI, with special regard to the benefits and challenges of implementation. The qualitative, semi-structured one-to-one interview was deemed to be the most suitable research method for this purpose, as it facilitated the exploration of the participants’ experiences and perspectives of a particular phenomenon (Braun & Clarke, 2013). A new interview schedule was developed and validated for the purposes of this study. The results were published as a pilot study (Kótay-Nagy, 2022), with some parts reproduced here verbatim and complemented by additional analysis.

 

3.3.2.2 The Development, Piloting, and Validation of the Interview Schedule. The interview schedule was developed following the guidelines proposed by Dörnyei (2007), Prescott (2011) and Richards (2003). First, a literature review was conducted to identify the main dimensions of the interview, which resulted in the emergence of four topics: (a) attitudes towards individual differences in the EFL classroom and the concept of DI; (b) attitudes towards the use of ICT; (c) practices of TEDI; and (d) perceived benefits and challenges of TEDI. Next, the interview questions were put together in accordance with Dörnyei’s (2007) guidelines, i.e., the schedule started with an introduction and a few questions about the participants’ professional background, which was followed by the content questions and a final closing question. The content questions were organised around the four topics and contained three to five grand tour questions with corresponding follow-up questions. The first content section examined how participants perceived and attended to individual differences in their lessons in general (e.g., “What individual differences do you attend to in your lessons?”), i.e., their pedagogical knowledge (Mishra & Koehler, 2006; Shulman, 1987) related to DI. The second section included questions about participants’ perceptions of using ICT tools in the English lessons (e.g., “What ICT tools do you prefer to use in your English lessons?”), or in other words, their technological content knowledge (Mishra & Koehler, 2006). The third and fourth sections asked about teachers’ self-reported practices of TEDI, i.e., their pedagogical technological content knowledge (Mishra & Koehler, 2006) related to DI (e.g., “In your experience, what ICT tools can be used to effectively differentiate the content of the lesson?”) and their views of the affordances and challenges of using technology for differentiation purposes (e.g., “In your opinion, what effects does TEDI have on your students?”). In designing the questions related to TEDI, especially those addressing its perceived benefits for students, I aimed to look at both content- and modality-oriented motivation but placed greater emphasis on content and the specific language-learning goals teachers seek to achieve through TEDI. While I anticipated that teachers might mention the entertainment factor of technology use, my primary focus was on how such effects could be combined with language-learning objectives to serve pedagogical purposes.

 

 

Each pilot interview was followed by a reflective phase when I listened to the recordings and analysed the participants’ responses in light of the two main evaluation criteria of qualitative interviews: the flow of the conversation and the breadth and depth of the collected data (Dörnyei, 2007). Most changes were implemented after the first pilot with Dalma and concerned the reordering, deletion and broadening of some questions.

3.3.2.3 Participants and Data Collection Procedures.Besides Bea and Rebeka from School A, three additional focal participants were included in the study, selected through convenience and snowball sampling. This procedure yielded a total of five participants from three distinct schools. For detailed background information on all participants, refer to Table 11 in Section 3.3.1.1.

3.3.2.4 Methods of Data Analysis. Similarly to Study 1, the data were subjected to template analysis (TA), a type of thematic analysis, following the guidelines proposed by King (2012). TA mixes literature-based themes and data-driven themes in an iterative process, and thus is situated between deductive and inductive analysis (King, 2012). This method proved ideal for analysing the data in this study as it allowed for the use of predefined themes while also being open to the emergence of new themes (Braun & Clarke, 2022).

 

 

I analysed the data using ATLAS.ti 8.4.3. First, I conducted a thorough reading of the first transcript, and coded sections that seemed relevant to my research questions. Next, I grouped and compared these codes with my pre-defined themes. Sections that matched these themes were categorised accordingly, while new patterns led to the creation of additional themes. This initial framework was used and refined through a cyclic process as I coded the remaining transcripts. To visualise the relationships between the themes, similarly to Study 1, I created a thematic “mind-map” (King, 2012, p. 433), which, along with the first draft of the results and discussion section of the paper, underwent peer debriefing with colleagues in my PhD programme and was reviewed for expert judgment by two professors. In light of their feedback, I further refined the description of some themes. A month after the initial coding procedure took place, I used the code-recode strategy (Saldaña, 2013) and revisited my dataset to check the reliability of the coding, which confirmed that the emerging template was a suitable framework for organising and analysing the responses of the participants. Altogether 3 main themes, 8 sub-themes and 20 codes were assigned to a total of 162 interview segments (a sample of a coded interview excerpt can be found in Appendix I). Table 14 provides a numerical overview of these themes, sub-themes and codes, while the finalised thematic map is available in Appendix J.