At each school (Schools A, B, and C) two lesson study cycles were observed and video-recorded. Transana computer analysis software was used to analyse the video data. The large volumes of video data were transcribed using gisted transcription (Dempster and Woods, 2011). Paulus, Lester, and Dempster (2013) stated that a gisted transcript is similar to a news show reports sharing the highlights of a politician’s speech and identified “two types of gisted transcript: condensed and essence” (p. 98). According to Evers (as cited by Paulus et al., 2013), a condensed transcript is created by listening to the recording and leaving out all the utterings that seem irrelevant to the research question. However, the major challenge with condensed transcription is “deciding what to leave out, while still retaining enough context for analytical purposes (Paulus et al., 2013, p. 98).
Whereas a condensed transcript captures the exact words from the media file, an essence transcript retains only a paraphrased version of recorded data (Paulus et al., 2013, p. 98). Essence transcribing, as stated by Dempster and Woods (2011), can help researchers to save time spent on creating transcript from media files as it
enables the researcher to create a summary transcript that captures the essence of a media file’s content without taking the same amount of time or resources as a verbatim transcript might require. Typically ... a researcher may take four to five hours create a verbatim transcript of the spoken word in a typical hour-long media file, while such a file can be gisted in one to two hours. (p. 22)
The video data for this research were transcribed using, in essence, gisting. Figure 3.8 is an excerpt from the database in Transana, displaying the organisational structure of the data for lesson planning, teaching and re-teaching of the research lessons at the three case schools.
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An excerpt of the database displaying data on the revision of the research lessons and the post- lesson discussion is not shown here.
Figure 3.8. Database for lesson planning, teaching and re-teaching
Figure 3.8 shows that the organisational structure of data in Transana database is in a tree form, comprising libraries, collections, keywords, and search. A library is a group of related source files (i.e., media or text files). In this study, five libraries were created based on the video recordings: planning the research lesson, teaching, revision of the taught lesson, re-teaching the
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revised lesson, and post-lesson discussion. Video files for the three case schools were imported into respective libraries. For example, in Figure 3.8, under the library Planning research lesson, SA-P1 is the video file on the planning of the first research lesson at School A, and SA_P2 is the video file on the planning of the second research lesson at School A.
The video and audio files brought into Transana are called Episodes, and text files are called Documents. The Episodes can be associated with more than one transcript, and, therefore, researchers might decide to use multiple transcripts to summarise information about different analytic layers they wish to explore.
In Transana, a collection is a group of conceptually related bits of analytical data, which can be bits of text taken from Documents, segments of media taken from Episodes and Transcripts, or the still images related to the analysis. In this research, five Collections were created: planning the research lesson, teaching, revision of the taught lesson, re-teaching the revised lesson, and post-lesson discussion. The collections are nested. For example, the collections SA-P1 (School A – Planning 1), SB-P1 (School B – Planning 1), and SC-P1 (School C – Planning 1) are nested (contained) within Planning-1. In addition, Planning-1 and Planning-
2 are nested within Planning. This sub-categorisation allowed considerable flexibility in
specifying a meaningful analytic structure for clips and snapshots. In this vein, gisted clips and snapshots from videos for each case school were contained in respective collections.
The act of coding of clips and snapshots is central to analytic activities in Transana. The coding structure for this research was stored under the Keyword nodes. Keywords (that is, codes) were applied to the video clips and snapshots. The database in Figure 3.8 contains nine keyword groups. For example, Observer activities contain six keywords, as shown in Figure 3.8. These keywords were assigned to the video clips and snapshots to describe the analytically interesting content of the clip or snapshot.
Figure 3.9 refers to a video clip of the teacher explaining to the class during research lesson 1 at School A. This clip was assigned the keyword Explaining the keyword group
Teacher activity. When keywords were assigned to a video clip, essential information was
summarised in the transcript section of the clip properties. For example, in Figure 3.8 the transcript section summarised what the teacher said to the students.
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Figure 3.9. Assigning a keyword to a video clip in Transana
Typically, the transcript was linked to the video clip as shown in Figure 3.9, allowing the researcher to explore the clip when needed.
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Figure 3.9. A clip from teaching research lesson 1 at School A
After gisting an entire video, a number of reports were generated (Library reports, Keyword Summary reports, Episodic Reports, and the Collection reports), as well as the
Episodic and Collection keyword maps. For example, the Episodic Keyword Map Report in
Figure 3.10 is a visual display of the keywords assigned to the video for re-teaching research lesson 1 at School A.
Figure 3.10. Episodic Keyword Map Report for re-taught lesson 1 at School A
The reports and keyword maps were examined to gain a deeper understanding of the keywords as they relate to the research question on lesson study implementation at the school level. In Figure 3.10, for example, there is no band for Observer activities: Using lesson
plan/checklist, indicating that observers did not use the lesson plan or checklist during the
lesson. It is also evident from the (blue and yellow) band for Pupil activity: Presenting before
the class, that approximately four minutes of the lesson was spent on students presenting their
solutions or the strategies they had used to solve the problems.
Quantitative data
The Grade 12 mathematics examination data were analysed for the effects of lesson study on student performance using XLStatistics (Carr, 2014). The Grade 12 examination
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results in mathematics for 2011 and 2014 at Schools A and B were analysed. School C, being a new school, did not have Grade 12 results for 2011 and 2014, but only for 2015 and 2016. The results were analysed but not compared with those for School A and B.