Qualitative analysis

At the end of each day, I transcribed the videotaped interviews. All transcripts were verbatim accounts of what transpired in the interview (i.e. they were not edited). I indicated pauses longer than three seconds, hesitations, laughter, and interruptions by using brackets, e.g. (pause). Underlining was used to indicate some form of stress, and speech between double brackets was given to provide additional information about the setting of the interview, facial expressions or body language, and other contextual information that I thought would help me to capture the true meaning of the participants’ words. My own additions are inserted within square brackets.

All transcripts, summaries of transcripts, e-mail correspondence, participant observation notes, journal entries, memos, and lesson plan/post-observation notes were transferred to an electronic format (i.e. Microsoft Words), and were stored in a personal computer. While transcribing recorded interviews and transferring notes and summaries to a Microsoft Word format, I created a general idea

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of the type of the data my research methods had generated (i.e. how clear (or not) the participants expressed their thoughts, how lengthy (or not) their responses were, how fully (or not) they were answering to the research questions, and so on). In addition, at this early stage of analysis, I highlighted participants’ quotes or passages that struck me. By so doing, I become thoroughly absorbed in the data early in the analyses (Dey, 1993).

Once I finished the process of transcribing and transferring the data to a Microsoft Words format, I started the process of data analysis. All field data collected in the same school were stored together, and I analysed the data by teacher.

In terms of analytic approach, I employed a qualitative content analysis. To keep things as simple as possible, I decided to analyse my data by hand. That is to say, I read the hard-copy printouts of the transcripts, notes, memos, and summaries one by one, and tried to break the data apart in individual, essence-capturing segments that could help me to understand and interpret the participants’ teacher decisions, as well as how their beliefs, pedagogical knowledge, and teacher’s book guidance were represented in their delivery styles. A middle-order holistic coding perspective, “somewhere between holistic and line-by-line” (Saldaña, 2009:118), was employed to achieve this purpose. This choice was made for two main reasons. Firstly, I already had a general idea – obtained by the review of the literature on the factors that affect EFL teaching in Albania - of how to chunk the corpus into broad thematic areas. Secondly, the present study involves the analysis of a variety of data forms, and holistic coding seems to be very appropriate for these kinds of qualitative studies (Saldaña, 2009). More precisely, by means of a broader whole-text empirical approach, single holistic codes (either in vivo or descriptive codes) were applied to text segments of different lengths that provided clues as to why the teachers did what they did in their class. Afterwards, for more detailed analysis, the same text segments were analysed again and middle-order codes were applied where applicable (see Appendix 24 for an example). The combination of whole and middle-order approaches generated fifty-one codes (see Appendix 25).

Next, I studied the list of fifty-one codes to identify links between any of the codes. As a result of this code-to-code comparing process, similar codes were collected for closer scrutiny, some codes were subsumed by other codes, some others were dropped all together, and a coding manual with twenty five codes was generated (see Appendix 26).

The list of twenty-five codes was then applied to the raw data. Said in other words, I compared the raw data to code(s) by going back through the summaries, quotes, memos, and transcripts again, reading every single word and sentence and asking myself two main questions “What is it about?” and

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“What does it mean?”. Then, I allocated each piece of data to the appropriate code (or codes) of the twenty-five code list.

Afterwards, the twenty five codes were clustered together according to similar concepts. For example, the codes “Students’ previous learning” and “Students’ needs” were grouped together into the category “Students’ needs” because the concepts and ideas students are exposed to during their previous studies (i.e. their previous learning) are key determinants of students’ present needs. As a result of this categorisation, eleven main categories that drew out preliminary concepts that identified factors that influenced teacher decision making were developed. As seen in table 4.4, each of the eleven categories contains a number of subcategories.

Category Name Codes Emerged

Students’ Motivation Students’ Expectations Student’s Motivation

Students’ Needs Students’ Previous Learning Students’ Needs

Knowledge of the Community Context Knowledge of the Community

Knowledge of the School Context Knowledge of the School Headmaster Expectations School Facilities

Knowledge of Self Teacher’s Values

Teacher’s Extrinsic Motivation

Beliefs Teacher’s Beliefs about L2 Learning Teacher’s Beliefs about L2 Teaching

Knowledge of Instructional Strategies Teacher’s Undergraduate Education In-Service Teacher Training

Other Teachers’ Influence Personal Development

Teacher’s Previous Learning Experiences L2 Teaching Resources Knowledge of Curriculum

Textbook Teacher’s Book

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Knowledge of How to Use the Textbook Knowledge of the Subject Knowledge of English

Knowledge of L2 Socio/Cultural Properties Knowledge of L1 Grammar

Knowledge of Teaching Methodology Knowledge of student-centred approaches

Heuristic Decisions Heuristic Decisions Table 4.4: Formation of categories

Axial Coding, which “relates categories to subcategories, specifies the properties and dimensions of a category, and reassembles the data the researcher has fractured to give coherence to emerging categories” (Charmaz, 2006:60), was used as a second cycle analytic process. More precisely, using the constant comparative technique, each piece of data belonging to a category was compared with every other piece of data belonging to the same category and other categories to identify redundancies and similarities. It was during this process, for instance, that I noticed that the three categories “knowledge of students”, “knowledge of the community context”, and “knowledge of the school” could help me clarify the meaning of the concept of the teaching context and, thus, all three categories were merged together. As a result of this process, similar categories were combined together, and eight defined categories, shown in Table 4.5, were generated initially.

Category Name Codes Emerged

Knowledge of Students Students’ Previous Learning Students’ Needs

Students’ Expectations Student’s Motivation

Knowledge of the Community Context Knowledge of the Community Knowledge of the School Context Knowledge of the School

Headmaster Expectations School Facilities

Teacher Beliefs & Knowledge of selves Teacher’s Beliefs about L2 Learning Teacher’s Beliefs about L2 Teaching Teacher’s Values

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Knowledge of Instructional Strategies Teacher’s Undergraduate Education In-Service Teacher Training

Other Teachers Personal Development

Teacher’s Previous Learning Experiences Knowledge of student-centred approaches L2 Teaching Resources Knowledge of Curriculum

Teacher’s Book Textbook

Heuristic Decisions Heuristic Decisions

Others Factors that do not fit the other categories

Table 4.5: Refining categories – axial coding (first round)

An analytic memo, shown in Figure 4.2, reveals the development of my thinking process about the codes and categories while relating categories to subcategories during the axial coding:

28 April 2013

Coding: Reorganising the categories

After reviewing the categories another time, I feel that Teacher Learning and Teaching Experiences should be a category on its own. It is true that Teacher Learning Previous Experiences (Subcategory) influences to a great degree Teacher Knowledge of Instructional Strategies (Category). This is clearly the case of Miss Ada: she is aware of communicative teaching approaches because, as a student, she was exposed to a communication-based teaching approach. However, Miss Evis is also aware of communicative teaching approaches because she has attended a number of CLT theory-based training events. Yet, Miss Evis – who had been exposed to traditional methods of learning as a student - teaches in a very traditional way. When novice teachers first enter their classes, they are likely to approach the teaching in the same way as their teachers did (when we make decisions as humans we are likely to select as an outcome an alternative with which we are familiar with, and novice teachers are very familiar with their own teachers’ delivery style because they have been exposed to it for 3 or 4 years). With the passing of years, novice teachers are likely to rely on the same teaching approach. It follows that Teacher Learning Previous Experiences directly influences what teachers do in their classes (rather than Teacher Knowledge of Instructional Strategies). Therefore, it should be a category on its own.

Note: Does it mean that teachers keep doing the same things during all their lives? Most likely not. Due to the influence of other factors (e.g. knowledge of students, knowledge of community, and so on) teachers are likely to add new things in their repertoire. For example, Miss Elona plays a song to motivate her students, Miss Evis replaces inappropriate reading passages with business-related reading passages, Miss Landa uses mainly English in her classes because she believes students are not often in contact with the language, and so on.

Figure 4.2: Axial Coding analytic memo

As shown in section 4.3.2.3, during the process of data collection and analysis, I continually recorded my thoughts, impressions, and tentative interpretations in the form of an interpretive narrative. These notes, as shown below, eventually helped me to define the shape of the core categories.

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The process of sorting and re-sorting the data was done three times by the researcher, _{until five axial}

categories (see table 4.6 below) emerged.

Table 4.6: Refining categories – axial coding (third round)

Analytic memos were also used to reassemble data that were fractured during the previous stages of the qualitative analysis. More precisely, Miss Landa unknowingly did the analytic work for me when she stated the following in one of our informal interviews:

The question is

(pause)

(pause)

(pause)

(pause)

(pause)

The analytic memo that accompanied this quote, shown in Figure 4.3, was used as the starting point in bringing codes and analytic memos to life, and helping me realize where the story of the data was going.

25 January 2012

Interview Transcription: Miss Landa Interview 5 (12.01.2012)

Question: Is the teacher suggesting that she approaches the process of teaching unconsciously? What role does routine (things she is comfortable with?) play in the process of teaching?

Figure 4.3: Analytic memo accompanying an interview

Category Name Axial Codes

Knowledge of Students

Knowledge of the Community Context Knowledge of teaching Context Knowledge of the School Context

Teacher Beliefs & Knowledge of Selves Teacher Beliefs & Knowledge Knowledge of Instructional Strategies

L2 Teaching Resources Textbooks, Curriculum, and Language Policies Teacher Previous Learning Experiences

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Two years and three months later, the diagramming process started from this note, and two core categories which integrated the axial codes at a higher level of abstraction were created: Conscious and Unconscious Decisions. The core category Conscious Decisions integrated semantically the axial codes: Knowledge of Teaching Context, Textbooks, Curriculum and Language Policies, Teacher Beliefs and Knowledge, and Teacher Learning and Teaching Experiences. All the teaching behaviours grouped in the axial code Conscious Decisions share similar properties: they represent conscious instructional decisions. The degree of consciousness, however, might vary from clearly motivated selections (as in the case of playing a song in the classroom to motivate students) to unconscious decisions (as in the case of teacher decision influenced by teacher belief and knowledge systems). With the passing of time, through means of repetition, these teaching behaviours are likely to become part of the teachers’ delivery routine. As seen in chapter 2.2.2, frequently occurring events are easy to recall and decision makers tend to think of situations or occurrences easily brought to mind as more important than instances of less frequent classes. As a result, teachers – to simplify the process of choosing among alternatives - might use heuristics based on their previous teaching and learning experiences. It follows that decisions influenced by Knowledge of Teaching Context, Textbooks, Curriculum, and Language Policies, Teacher Belief and Knowledge, and Teacher Learning and Teaching Experiences are likely to turn into heuristics if teachers incorporate the teaching practices influenced by those factors into their daily routines.

The other core category, i.e. Unconscious Decision, includes all the heuristics used by teachers in making instructional decisions.

A simple dimensions and properties diagram derived from Axial Coding is shown in Figure 4.4.

Figure 4.4: Dimensions and properties table derived from Axial Coding

Conscious Decisions Unconscious Decisions Knowledge of Teaching Context

Teacher Beliefs & Knowledge Influence of Textbooks, Curriculum, and Language Policies

Teacher Previous Learning Experiences

Repetitive Teaching Behaviours

Heuristic of Availability, and Representativeness

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The two main categories emerged from the axial coding process, i.e. “conscious decisions” and “unconscious decisions”, helped me to understand and explain how and why Albanian teachers use Western-published textbooks in their EFL classes.

4.8 Summary

The purpose of the present study was to explore how communicatively Albanian teachers use textbooks in their classrooms. The following questions guided the study:

1) How communicatively do Albanian EFL teachers use text-books?

2) What shapes Albanian EFL teachers’ decisions on how to use text-books in their classes?

 What role does a Teacher’s book play in the use of text-books?

Four high school teachers volunteered to participate in the study. The four teachers have very different teaching experiences and backgrounds: one of them is an example of a novice teacher, another represents a more experienced teacher with hand-on CLT teaching experience, another is a mid-career teacher and teacher-trainer with a strong CLT knowledge, and the last teacher is a very experienced practitioner with more than twenty years of EFL teaching.

Four case studies were constructed to fulfil the aims of the present study. Data were obtained through a variety of sources: observations, post-observation interviews, informal discussions with the participating teachers, their colleagues and their principals, post-lesson evaluation discussions, and a questionnaire on teachers’ beliefs on L2 teaching and learning. In addition, photocopies of textbook materials, teacher book pages, and lesson plans were collected. The data were analysed both quantitatively and qualitatively. An observation grid was used for quantitative purposes, and a qualitative content approach was employed to analyse the data qualitatively.

The findings from each individual case study are presented in chapter 5. A consistent sequence is used to represent the findings: firstly, an introduction and a profile of each participant is given. Following this, empirical data collected by each participant are connected to the study’s main research questions. Descriptions and quotes are used to help the reader to understand the basis for each interpretation.

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FINDINGS OF THE STUDY