3.2.1 The Interview Study (Study 1)

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3.2.1.1 Methods of Data Collection. Following an exploratory sequential design (Creswell, 2015), Study 1 was conducted to identify themes for RQs 1 and 2 that would inform the development of the questionnaire to be administered in Study 2. In Study 1, data were collected with the help of one-to-one interviews. As Kvale (1996) formulates, the one-to-one interview is a “professional conversation” with the aim of obtaining “descriptions of the life world of the interviewee with respect to interpreting the meaning of the described phenomena” (pp. 5–6). As such, it provided an appropriate method to explore participants’ perspectives of the concepts of DI and TEDI.

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Portions of the subsequent sections, including details of the development and piloting of the interview schedule, as well as information about data collection, the participants and data analysis were published as an article (Kótay-Nagy, 2023a) and are now presented in an extended format.
 

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3.2.1.2 The Development, Piloting and Validation of the Interview Schedule. The interview schedule was developed based on the theoretical and empirical studies conducted in the field and following the guidelines described by Dörnyei (2007), Prescott (2011), and Richards (2003). It was written in the participants’ and the researcher’s mother tongue, Hungarian, and followed a semi-structured format with broad grand tour questions and possible follow-up questions. This type of schedule was deemed suitable for the purposes of the study as it invited the participants to elaborate on the issues in an exploratory fashion, without limiting the depth and breadth of the respondent’s story with ready-made response categories (Dörnyei, 2007).

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As for the structure, the schedule started with an introduction, followed by a few introductory questions concerning the participants’ professional background. The backbone of the schedule comprised of the content questions, which were organised around two main topics, i.e., participants’ beliefs about DI (their conceptualisation of and attitudes towards the concept) and their self-reported practices of DI, with special regard to the strategies they use (including their use of technology for DI purposes), the challenges they encounter and the factors they consider as enablers of DI.

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The first draft of the schedule was reviewed by the researcher in two rounds, then subjected to peer review by a fellow PhD student, who is a secondary school EFL teacher. Based on her feedback, the order of some of the grand-tour and follow-up questions was changed and a few ambiguous questions were reworded.

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The interview schedule was then piloted with two participants (see Table 4). The participants were selected using maximum variation sampling, a type of purposive sampling which searches for “individuals who cover the spectrum of positions and perspectives in relation to the phenomenon one is studying” (Palys, 2008, p. 697). What was especially important for me at this stage was to pilot the interview schedule both with a participant who embraces the concept of DI and one who has reservations about it in order to check whether the questions elicit the same depth of data. Through the combination of convenience sampling (contacting a former colleague of mine) and snowball sampling (asking a former colleague of mine to recommend a participant) (Dörnyei, 2007), I managed to invite two teachers meeting these criteria. Both of them are EFL teachers, having more than 10 years of teaching experience. Bella teaches both upper-primary and secondary school students, while Gréta teaches in a bilingual secondary grammar school. While Bella considers DI to be an integral part of her teaching practice, Gréta, as she phrased it in our correspondence prior to the interview, is more “sceptical” about the concept.
 

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Table 4 Background Data of the Participants of the Pilot Interview Study for Study 1
Pseudonym
Teaching experience in public education
Type of school
City
Bella
4 years
Secondary grammar school
Budapest
Gréta
11 years
Bilingual primary and secondary grammar school
Budapest
 

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The pilot interviews took place in the spring of 2022 and were recorded with the participants’ consent. After my first interview with Bella, following Richards’ (2003) recommendations for evaluating interview schedule, I re-listened to the recording to evaluate the data’s depth and breadth. Generally, the responses met my criteria, but I noticed a redundancy issue: the same topic of difficulties in DI was discussed twice, first broadly (“What problems and difficulties can arise when differentiating in the EFL class?”) and then specifically related to the teacher’s experiences (“What difficulties do you encounter in differentiating?”). This overlap led to repetitive answers, as Bella, quite understandably, had already discussed her experiences when answering the first question. Therefore, I decided to remove the general question from the first part and introduced it only in the second part. Based on my impressions of the subsequent interviews, this change made the discussion more natural and generated responses that were more relevant to the research questions.

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The revised schedule was then piloted with Gréta. Again, I listened to the recording to evaluate the quality of the responses yielded by the interview schedule. Upon reviewing the interview, I found that the responses had the desired depth and length, which was particularly encouraging considering that Gréta’s perspective on the topic was quite different from Bella’s. At this stage of the piloting process, the only modification I deemed necessary was the addition of a follow-up question to probe further into the difficulties of DI mentioned by the participants (“Why do you think these aspects cause difficulty for you?”). With this adjustment, the interview schedule was now deemed ready to be used in the main study.

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It is important to note that while originally, Bella and Gréta were part of the pilot project, I found their responses so insightful that I chose to include their interviews in the main study. This is in line with Richards (2015), who contends that qualitative projects “can cheerfully be regarded as one long pilot” (p. 96), insofar as it is common to adjust the instruments without discarding data from the initial stages, such as pilot studies, as all data contributes to a richer analysis. Since I felt that Bella’s and Gréta’s responses would be valuable additions to my database, I decided to include their interviews in my main study. The English translation of the final interview schedule is attached in Appendix C.
 

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3.2.1.3 Participants and Data Collection Procedures. Study 1 was based on one-to-one semi-structured interviews with 9 Hungarian primary and secondary school EFL teachers. The main goal of this study was to explore the beliefs and self-reported practices of teachers coming from different backgrounds, therefore, I used maximum variation sampling to find participants who have different perspectives with regard to the focus of the investigation (Palys, 2008). As Creswell (2015) points out, this sampling procedure is applied by first identifying the characteristics in terms of which we would like to find participants and then approaching participants who display different dimensions of these characteristics. The characteristics for which I sought to ensure as great variety as possible were the teaching context (primary and secondary school), the years of teaching experience and the geographical location. For this purpose, I contacted my teacher colleagues in various cities and towns in Hungary and invited them to participate or recommend potential candidates. As mentioned earlier, the interviews made with Bella and Gréta were also included in the main study. The participants’ background data are shown in Table 5.
 

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Table 5 Background Data of the Participants of Study 1
Pseudonym
Teaching experience in public education
Type of school
City
Anett
1 year
Secondary grammar school
Budapest
Bella
4 years
Secondary grammar school
Budapest
Cecília
24 years
Secondary vocational and grammar school
Budapest
Cintia
33 years
Secondary vocational and grammar school
Vác
Gellért
6 years
Primary and secondary grammar school
Budapest
Gréta
11 years
Bilingual primary and secondary grammar school
Budapest
Lilla
1 year
Primary school
Pécs
Patrik
7 years
Bilingual secondary grammar school
Budapest
Zsuzsanna
12 years
Primary school
Veszprém
 

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Nine teachers, seven females and two males, agreed to participate in the study. They represent different age groups and have a teaching experience ranging from 1 to 33 years. One of the participants, Gréta, worked in public education for 11 years but had also taught previously at various language schools for 15 years, which means her total teaching experience is approximately 26 years. It is important to note, however, that the majority of the participants (six out of nine) had no more than 12 years of teaching experience, which may have shaped their perspectives on DI and TEDI and thus had to be considered during data analysis, as well. Regarding the subjects taught, all of the participants have a degree in teaching EFL, and three of them are teachers of another subject as well (Hungarian, Hungarian as a FL, German as a FL). At the time of the interviews, five participants were teaching at schools located in the capital, Budapest, and three of them were working in the countryside (Pécs, Veszprém and Vác).

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The interviews took place between March and July in 2022. One interview was conducted in person upon the participant’s request, while the rest took place online. The average length of the interviews was 35 minutes. The sessions were audio-recorded and transcribed verbatim, and altogether resulted in a dataset of 30,854 words.
 

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3.2.1.4 Methods of Data Analysis. The data were analysed with template analysis (TA), a type of thematic analysis, in line with the guidelines proposed by King (2012). In TA, an initial template of themes is constructed based on the literature and on the coding of a subset of the data, which is then applied, modified, and re-applied through an iterative process. As such, TA is positioned in the middle ground between top-down and bottom-up styles of qualitative analysis, i.e., it allows for the generation of a priori themes with the flexibility to redefine or discard any of these themes and to generate new ones as the analytic process unfolds (King, 2012). This approach was deemed suitable for the purposes of the present study as it facilitated the identification of evidence in the data for pre-defined patterns by handling themes as ‘inputs’, but also allowed room for new themes to be developed as analytic ‘outputs’ (Braun & Clarke, 2022). Altogether five overarching a priori themes were identified, which corresponded to the research questions of the study, and each had sub-themes drawn from the consulted theoretical and empirical literature. The a priori themes and sub-themes are shown in Table 6.
 

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Table 6 Template Used for Data Analysis in Study 1
A priori theme
Sub-themes
Understanding of the concept of DI
  • Attending to learner differences (readiness, interest, learning profile)
  • Modifying curriculum elements (content, process, product, learning environment)
Attitude towards the concept of DI
  • Positive aspects (benefits of DI)
  • Negative aspects (methodological uncertainties, implementation difficulties)
DI practices
  • DI by learner differences (readiness, interest, learning profile)
  • DI by curriculum elements (content, process, product, learning environment)
  • Use of ICT for DI purposes
Challenges of DI
  • Difficulties in planning differentiated lessons
  • Difficulties in delivering differentiated lessons
Enablers of DI
  • Professional development
  • Cooperation with colleagues
  • Cooperation with parents
  • Support from school administrators
  • ICT
 

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Data were analysed using qualitative data analysis software ATLAS.ti 8.4.3. The first transcript was given close reading and any section that addressed ideas relevant to the research questions were coded. Next, the codes were clustered into groups, which were checked against the a priori themes, and were either assigned to these themes or were labelled under new themes. This preliminary template was then applied and refined in a recursive manner during the coding of the rest of the transcripts. The emerging structure was displayed in a “mind-map” (King, 2012, p. 433) to indicate the hierarchical and lateral relationships between the themes. The thematic map and the first draft of the results and discussion section of the paper were subjected to peer debriefing, upon which some thematic clusters were further refined in light of the feedback received from a trusted and knowledgeable colleague (Leech & Onwuegbuzie, 2008). One month after the initial coding, I applied the code-recode strategy (Saldaña, 2013), i.e., I revisited my dataset to assess the reliability of the coding. This confirmed that the emerging template provided a suitable framework for organising and analysing the participants’ responses. Altogether 7 main themes, 18 sub-themes and 42 codes were assigned to a total of 206 interview segments (for a sample of a coded interview extract, see Appendix D). Following the practice of Fekete (2023) in documenting the coding of interview data, I provide a numerical overview of the themes, sub-themes and codes of the study in a table format (see Table 7). The final thematic map is available in Appendix E.
 

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Table 7 An Overview of the Final Themes, Sub-Themes, and Codes in Study 1
Theme
(Sum: 7)
Sub-theme
(Sum: 18)
Code
(Sum: 42)
Number of times code was used
(Sum: 206)
Percentage of all codes
(%)
 
Number of participants
(n = 9)
Percentage of all participants
(%)
 
1. Understanding DI as responding to student needs
1.1 readiness
 
1.1.1 language proficiency
4
1.9
4
44.4
1.1.2 motivation
1
0.5
1
11.1
1.1.3 emotional state
3
1.5
3
33.3
1.1.4 SEN and learning and behavioural difficulties
1
0.5
1
11.1
1.2 learning profiles
1.2.1 learning styles
4
1.9
4
44.4
1.2.2 gender
2
1.0
2
22.2
1.2.3 socio-
cultural background
1
0.5
1
11.1
1.3 interests
2
1.0
2
22.2
2. Ambivalent attitude towards DI
2.1 positive aspects
2.1.1 recognising DI in professional discourse
16
7.8
8
88.9
2.1.2 appreciation of DI benefits
13
6.3
8
88.9
2.2 negative aspects
2.2.1 implementation difficulties
13
6.3
7
77.8
2.2.2 methodological uncertainties
1
0.5
1
11.1
2.2.3 feeling pressured to use DI
6
2.9
2
22.2
3. TEDI: Embraced by some, rejected by others
3.1 acknowledgement of ICT’s potential for DI
3.1.1 content differentiation
2
1.0
2
22.2
3.1.2 self-paced learning
2
1.0
2
22.2
3.1.3 self-regulation
2
1.0
2
22.2
3.2 reluctance to use TEDI
3.2.1 lack of ICT competence
2
1.0
1
11.1
3.2.2 scepticism towards ICT
2
1.0
1
11.1
4. A variety of intuitive DI strategies
4.1 DI by readiness
4.1.1 supplementary tasks
22
10.7
7
77.8
4.1.2 tiered tasks
2
1.0
1
11.1
4.1.3 personalised feedback
4
1.9
3
33.3
4.1.4 gamification
3
1.5
3
33.3
4.1.5 flexible grouping
13
6.3
7
77.8
4.2 DI by interest
 
4.2.1 personalised discussion questions
3
1.5
2
22.2
4.2.2 student presentations
4
1.9
3
33.3
4.3 DI by learning profile
4.3.1 multimodal presentation of content and instructions
1
0.5
1
11.1
4.3.2 various options for task completion
1
0.5
1
11.1
4.3.3 student choice in grouping arrangements
1
0.5
1
11.1
5. Occasional use of TEDI
5.1 DI by interests
 
5.1.1 digital tasks tailored to different study goals
2
1.0
1
11.1
5.1.2 digital presentations on student-selected topics
2
 
1.0
1
 
11.1
5.2 DI by readiness
5.2.1 app-based tasks offering choice of complexity
2
 
1.0
1
 
11.1
 
5.2.2 supplementary app-based tasks for fast-finishers
2
1.0
2
22.2
6. Challenges of DI
6.1 lesson planning
 
6.1.1 increased preparation time
15
 
7.3
7
77.8
6.1.2 thinking in multiple dimensions
5
2.4
3
33.3
6.2 lesson delivery
6.2.1 multitasking
7
3.4
4
44.4
6.2.2 time-management
5
2.4
3
33.3
6.3 acquainting students with DI
10
4.9
7
77.8
7. Enablers of DI
7.1 professional preparedness
 
7.1.1 pre-service training
2
1.0
2
22.2
 
7.1.2 in-service training
4
1.9
4
44.4
7.1.3 access to differentiated materials
5
2.4
3
33.3
 
7.2 cooperation with stakeholders
7.2.1 teaching staff
8
3.9
6
66.7
7.2.2 school administrators
3
1.5
2
22.2
7.2.3 parents
1
0.5
1
11.1
7.3 ICT
2
1.0
2
22.2
 
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