Section 3: Procedure for analysing the data

This section describes the procedures undertaken to analyse the findings. The analysis was done in three levels and Table 4.2 provides an outline of the three levels of analysis.

Table 4.2: The three levels of analysis (analytical framework) Level of analysis Details

Level 1: Creating stories about learning Transcription of videos, interviews Creating the data set

Translation of the transcriptions Colour coding of the transcripts

Extracting initial themes and sub-themes Clustering data under the themes and sub-themes for each participant Writing of stories

Levels 2: Analysing themes on learning Analysing themes on learning at semantic level drawing initial conclusions

Level 3: Analysing learning through digitised learning resources

Analysis at latent level (against LR and TF), drawing conclusions and answering research questions 1 and 2

4.5.1 Level 1 analysis: Creating stories about learning

This section details the procedures used in the first level analysis of the data.

4.5.1.1 Transcribing the interviews and coding of the observation notes Once the fieldwork was over, the author had a large volume of data and had to make a decision on how to organise the data. According to Cohen et al. (2007),

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analysing qualitative data includes ‘organizing, accounting for an explanation of the data’ (p. 461). They added that qualitative data analysis, involves ‘making sense of data and noting patterns, themes, categories and regularities’ (Cohen et al., 2007, p. 461). Cohen et al. (2007) also stated that there is ‘no restricted route to analyse and present qualitative data but the researcher should adhere by the issue of fitness for purpose’ (p. 461). ‘By binding with the principle of fitness for purpose, clarity should be present as to what kind of analysis is undertaken’

(Cohen et al. 2007, p. 461).

From the first level, the first stage was to transcribe data obtained from videos and audio recordings to be able to make sense of the data from the field. While transcription might be considered as a simple exercise of transforming verbal conversations into written form, the researcher had to take a decision of whether to translate or transcribe the data or both. Finally, the choice was made to do both transcription and translation. The reason for translating the transcripts was to cater for readers who were not conversant with the Mauritian Kreol as children conversed in French or Creole language during the interviews and observations.

Furthermore, the researcher listened to the videos and audios several times and immersed into transcribing the data first. Very often, we view ‘transcription as an easy and straightforward technical task but in fact, it is very a meticulous task as it involves judgement and interpretation’ (Bailey, 2008 p. 127) and how to best represent the data. The researcher transcribed the data obtained from the observation and the interviews for all the 12 participants. The researcher had to go back to the raw data several times to make sure it accurately transcribed the rich data and described all the occurrences in detail.

According to FitzGerald (2012), ‘video captured in situ involves rich information and reveals important incidents that are linked to the interactions’ (p. 2). There are a variety of tools that might assist in analysing video but the researcher did it manually by pausing the video at very short intervals and writing out everything that was observed. This process allowed the capturing of actions, emotions, attitudes and behaviours of the learners. It was indeed very time consuming but allowed me to obtain rich information. Two peers did the member checking and

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vetted the transcriptions for both the videos and the interviews and few things were amended; for example, a few emotions that the learners depicted in the videos were described in greater depth in the video transcriptions. The member checking helped me to ensure trustworthiness and authenticity of the transcriptions.

After all the data was transcribed, the researcher reviewed all the transcriptions and produced a data set. The researcher chose to omit five participants from the sample. In Sandy Government School, Kanen was removed from the sample as he was not able to answer the questions during the interview and his interview consisted of only yes/ no answers. He could not actually justify the choices made in his drawings. In the same school, Riyaad was also removed from the study, as his data was very similar to that of his friends and would not have added to the richness of the data. Moreover, from Violet Government School, Mohammed, Nishi and Wendy were not considered in the study. Data from Mohammed was not taken into account because out of the three lessons, he was present for only one lesson and this led to limited data. Nishi’s data resonated with other participants’ data and it was decided to omit Nishi’s data from the sample and this did not affect the data. In the case of Wendy, as for Kanen, there were many instances when she could not elaborate her responses. To summarise, seven participants were considered, four from Sandy Government School and three from Violet Government School. A copy of the data set is attached in Appendix 11.

4.5.1.2 Writing of the stories

Once the transcripts were produced, the researcher made the decision to create stories of each participant out of the data collected, and this constituted the first level of analysis. Over a factual rendering of the findings, the researcher chose to create ‘stories’ to better foreground the emotions, attitudes and behaviours of the learners who were children of eight to nine years old and this was considered the ‘fitness for purpose’. In linguistic form, stories are considered the best suited to express human experience as lived (Ricoeur, 1991). Thus, the researcher used stories to capture the human experience and connectedness between the

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digitised learning resources, the teacher, and the learner within the digitised classroom (Ricoeur, 1992). Moreover, since the study was conducted with primary school learners of eight to nine years old, the researcher wanted to recreate the learning experiences of the children while retaining flavours of the setting and classroom interactions. Stories also allowed the researcher to better foreground the voices of the participants and the learners’ naïveté during their learning of the concepts through digitised learning resources. Representing the social structure and the learners’ human activities while learning was made easier through stories (Kamberelis, 1999 p. 406). The researcher followed and adapted Braun & Clarke’s (2006), six-phase framework of thematic analysis to write the stories (Maguire & Delahunt 2017, p. 3354). Table 4.3 illustrates the steps used to generate the initial codes to be able to write the stories.

Table 4.3: Six-phase framework for doing thematic analysis (Braun & Clarke, 2006)

Step Details

1 Become familiar with the data 2 Generate initial codes

3 Search for themes 4 Review themes 5 Define themes 6 Write up