Data analysis

After all data gathered this section will present an analysis of the approaches employed. Template Analysis is a method of analysis of post-lesson interview data. Video analysis was employed with video recordings. Before discussing the methods in Sections 3.7.2 and 3.7.3, the relevant data sources to research questions will first be explained in Section 3.7.1.

Answering research questions

In order to answer the three sub-research questions asked in this study, the two main sources of data were post-lesson interviews and video recordings. The other data such as pre-lesson interviews, field notes, and documents were not included because these data were collected for the contextual information. The aim of this study is to explore early primary teachers’ questions and understand their questioning practices in the context of science teaching in Thailand. This study attempts to answer one main research question:

How do Thai teachers perceive their questioning practice in science lessons? The three sub-research questions (RQ) are as follows:

1. What purpose do Thai teachers report to have in asking questions? 2. How do these understandings relate to open and closed questions? 3. What strategies do Thai teachers identify for structuring questions?

According to Research Questions 1 and 3, the post-lesson interview data were analysed using Template Analysis to identify major themes and/or recurring patterns of questioning practices. The first research question looked at purposes in asking questions and then the questioning strategies were investigated in the latter. Other factors may also influence this, such as teaching experiences. An additional analysis of video recordings happened after Thematic Analysis of the post-lesson interview data with teachers about their questioning practice. This analysis using descriptive statistics of video data was related to Research Question 2. This analysis is related to Research Question 1 because I further examined the question types and the nature of children’s responses.

This process of data analysis started at the beginning of the data collection stage. This was partly because this research used video-mediated interviews involving a procedure of identifying five-minute extracts of video recordings that were later used to mediate interviews with teachers.

Further systematic data analysis happened after the completion of data collection. Data derived from different methods were used to clarify different research issues. In connection to Research Question 1, the purposes of asking questions were analysed inductively from post-lesson interviews in conjunction with video recordings. The dataset of teachers’ questions which were identified by the teacher during the post-lesson interviews was recorded in full sentences. Moreover, this research was exploratory in nature and so the 74 questions selected by teachers for discussion led to the focus of the data analysis and research findings, since I was searching for information that was relevant to the research topic. One example of the 74 specific questions was “What is a tree’s colour?” (T4, E1), in a lesson dealing with a tree’s components. Then, these questions were categorised based on the data and on the existing literature.

In order to answer Research Question 3, which involved understanding the questioning strategies of the teachers and the teachers’ reasons, the data derived from post-lesson interviews were mainly used. The video recordings gave detailed information of the context of the questioning strategy. This illustrated the teacher’s questioning strategy, showed details of the children, and attempted to analyse what had happened in the lesson.

Data from post-lesson interviews were analysed to identify cognitive and cultural factors which may influence their questioning practice. In the pre-lesson interviews, contextual factors such as types of activities, and teaching topics were explained.

The three research questions were addressed with data collected from multiple methods, as shown in Table 3.4.

Table 3.4: Data collection methods Data collection

methods

Research Questions

Main Research Question RQ1 RQ2 RQ3 Pre-lesson interviews  Video observations     Post-lesson interviews    Documentary data 

Transcribing and translating the data

Transcription is defined as “the process of converting recorded material into text” (King and Horrocks, 2010, p. 142); accordingly, the interview data from both pre- and post-lesson interviews, in the form of audio-recordings, were transcribed into the Thai language. As the participants’ first-language was Thai, the transcription was transcribed “word for word (verbatim)” (King and Horrocks, 2010, p. 143). This meant that the whole segment of transcription was typed as they spoke in Microsoft Word. Although this process is a very time and effort consuming one (King and Horrocks, 2010), it helped me to become familiar with the data. Transcribing sounds into words allowed me to focus on the meaning of the respondents’ experience in relation to the research questions. During transcription, I also took notes and highlighted interesting keywords, which helped the formation of ideas for data interpretation. To ensure the validity of my transcriptions, they were double-checked by the participants. Translating the data from Thai to English was very complex. Esposito (2001, p. 570) notes that translation is “the transfer of meaning from a source language… to a target language” (such as English). I tried to keep the meaning of the quotations as close as possible to the Thai original. Data translation was only done when quotations were needed for purposes of illustration within the thesis. The quotations of the two languages were given and were discussed with a native English speaker for feedback and revision purposes.

Template analysis

Interview transcripts contained rich data associated with the respondent teachers’ understanding of purposes in asking questions (Research Question 1), of the use of questioning strategies (Research Question 3) in teaching science and of the use of wait time and selection of respondents. Template Analysis was adopted in this study to draw this picture. The rationale for template analysis and its process will be described in this section.

Template analysis was thought to be suitable for this research based on the epistemology used and its flexibility in terms of thematic analysis, as explained in the next paragraph. Template analysis is an analytical technique of textual data which mainly involves transcribed interview data. Template analysis is a technique for producing an understanding of the teachers’ accounts which contain “extensive and complex textual data” (King, 2012, p. 426). In this research, this consisted of template analysis of textual data involving mainly interview transcripts derived from video-mediated interviews. Each interview transcript contained more than 10,000 words of rich and detailed information about teachers’ understanding of their questioning practice.

The central aspect of template analysis is to produce a template that is “a great help in producing a clear, organized, final account of a study [teachers’ understanding in questioning practice]” (King, 2004, p. 268). Template analysis is “a style of thematic analysis that balances a relatively high degree of structure in the process of analysing textual data with the flexibility to adapt to the needs of a particular study” (King, 2012, p. 426). Therefore, it was decided to use template analysis in this research to analyse data from this primary fieldwork, which is considered rich and in-depth as mentioned above. This, in turn, led to the gaining of insight into classroom questioning practice, based on teachers’ understanding.

A distinct feature of the template approach compared with other thematic approaches such as generic thematic analysis and grounded theory is “the development of a coding template” (King, 2012). There are three main stages of template analysis: initial template creation, template development, and final template, as illustrated in Figure 3.4.

Firstly, an initial template is normally developed from a subset of the data, and then the template is applied to the rest of the transcripts (King, 2012). There are three ways to develop the initial template:

 Have pre-defined codes/a priori codes based on the theoretical position of the research

 Develop codes after some initial exploration of the data

 Take a half-way position – some initial codes (possibly from the interview questions?) and refinement after exploration of the data. (Waring and Wainwright, 2008, p. 86)

According to the research aims, this research sought to understand classroom questioning practice based on teachers’ perspectives utilising the theoretical framework, as proposed in Section 2.8. Consequently, this research was centred on the half-way position. Based on this, the priori codes are used to create the initial template (King, 2012). In this study, the priori codes were the main issues when the interview guide was constructed as the main instrument of data collection, discussed in Section 3.6.1 (see Appendix E for the interview guide). Then, starting with the primary codes, an inductive approach was taken, in which an initial template was built from a subset of interview questions. The development of the template consisted of a coding structure of themes that emerged from the teachers’ accounts of questioning in practice. An initial template was developed from an exploration of seven out of fifteen transcripts by identifying codes and coding. Based on the research questions and the post-lesson interview questions, codes were constructed from reading all seven transcripts several times. At this stage, the interviews were read line by line, and ideas were highlighted and written on the right-

hand side of the interview transcripts. The recurring codes and patterns emerged to become a theme. After coding the subset of transcripts, it became an initial template (for the derived initial template of this study see Appendix G).

Secondly, regarding the development of the template, coding is a way to identify codes in relation to themes from textual data. Gibbs (2007, p. 38) defines coding as “a way of indexing or categorizing the text in order to establish a framework of thematic ideas about it”. The aim was to identify codes in sections emerging from the interview questions from a few words to whole paragraphs. One section, for example, was the teachers’ purposes for asking a question, so that a section of text in the interviews was interpreted as an instance of code, such as “checking prior knowledge”. This code was named based on keywords from the teachers’ accounts, in this case, key verbs with similar meanings. In addition, there are two main ways of coding: data driven and concept driven. The analytical process of coding to develop themes can start from data and also from existing theory or practice. The initial codes from a subset of the interviews in this study were derived inductively “to pull out from the data what is happening and not impose an interpretation based on pre-existing theory” (Gibbs, 2007, p. 46). Finally, in the final template creation, the main analytical activity consists of a modification of the template to form the final template. The development of a template as part of the analytical process is “an interactive process of applying, modifying and re-applying the initial template” (King, 2012, p. 430), during which time the template is modified to best answer the research questions. After the initial template was created, it was then applied to the rest of interview transcripts. Through this the modification of the template involved the activities of adding a new code, deleting an existing code, and changing the scope and the level of classification (King, 2004). Then the initial template was applied to the rest of the transcripts theme by theme, leading to the semi-final template. After that, each section in relation to the identified themes was re-read and recoded if necessary, to develop a clear presentation of the themes and codes. King (2004, p. 263) noted that it is difficult to say when to stop the development of the template, but at least all transcribed data in relation to the research questions should be coded. The analytical process for Thai teachers is summarized diagrammatically in Figure 3.4, and the final template resulting from this study is shown in Appendix H.

Figure 3.4: Diagrammatic representation of data analysis process using template analysis adapted from King (2012)

Nvivo was used for the purposes of data management. The main reason for using Nvivo is because the program can help “to work efficiently with complex schemes and large amounts of text” (King, 2004, p. 266). According to Gibbs (2013, p. 285),

…thinking about the codes, writing about them (for example, writing memos about them) and manipulating them is a central part of the analytic process they go through in order to extract a coherent and novel understanding from their data. The software includes a variety of tools for the manipulation of codes that supports this kind of thinking.

Additionally, the program features for coding and retrieval allowed me to modify codes easily without losing a context. The program offers an easy way to index chunks of text to particular themes, and to retrieve all similar coded text with all the information in terms of the source of the text (Gibbs, 2007, p. 106).

After exploring individual themes on teachers’ purposes in asking questions, questioning strategies, and two additional features of wait time and selection of respondents, the process of thematic analysis allowed me to find patterns or relationships between themes, and to seek themes for factors influencing teachers’ understanding on their questioning practice. Moreover, the question themes derived from the mediated-interview data were analysed to link with factors derived from the interviews and documents. Consequently, they were part of a theoretical model of understanding of questioning’ practices, which is the main aim of this research. It was an analytical process, and did not merely describe themes on a list. Rather, the presentation of themes were used to classify levels of Thai teachers’ understanding of questioning.

Video analysis

The purpose of analysing the video data was to examine the relationship between teachers’ reasons for asking questions and the types of questions used for each purpose (Research Question 2). The focus was to investigate the proportions of open and closed questions employed by Thai teachers in relation to each purpose.

In this analysis, the video data used the same dataset of 74 questions the teachers themselves had selected within the five-minute questioning extracts used in the mediated interview. As discussed in Section 2.4.2 of the Literature Review, whether a question was open or closed was based on definitions.

Closed questions which have pre-determined answers elicit factual information. In contrast, open questions are used to stimulate children’s thinking and have more than one possible answer.

In this current study, I categorised the questions based on the teacher’s apparent intention, which is an approach taken by many researchers (Edwards and Westgate, 1994; Myhill and Dunkin, 2005). In this study, the development of these categories was based on the questions phrased by the teachers themselves, which did not consider the feedback to the answer. In the lesson about vinegar, one of Teacher 2’s questions was: “Why does it [the egg] become white?” which was classified as an open question, as the question, potentially, had more than one possible answer of what may cause the egg’s shell to dissolve (See a list of all question in Appendix I). Using description statistics (Cohen et al., 2011) the percentage of use of open and closed questions (for example, checking prior knowledge) was calculated and tabulated for group comparison.

Another part of the video analysis of the nature of children’s responses investigated the length of children’ responses and the cognitive levels of answering. This analysis looked at the video data of the 74 questions and a Microsoft Excel used in data recording and processing. Answers from the children were written down in Thai to all the questions based on video data. In terms of children’s answers, the length of the answers was counted and the calculation of word length was carried out using descriptive statistics (Cohen et al., 2011). By an interpretation of children’s answers the cognitive levels to the 74 questions were identified.