As described above, most of the data of the present thesis consist of video recorded lessons. After the lessons were recorded, the material was fully transcribed and reviewed multiple times to detect different examples of humour. Once all instances of humour had been identified from the data, they were then further analysed, compared and finally divided into the different humour categories, such as irony and teasing.
Humour categories were pointed out at this late stage, since as Neuliep (1991:345) suggests, coming up with categories before the data collection could have made some of the examples "unclassifiable", which is not profitable. It can lead to marking items as
“other” or not getting enough data (ibid.). However, even when done after data collection, the categorisation of humour examples was somewhat problematic.
Distinguishing between different humour types is sometimes difficult, since the qualities of different humour types can overlap (Norrick 1993, as cited by Norrick 2003:1338). In the current thesis, definitions of humour categories presented earlier in chapter 3.6 were used to help differentiate between the various terms. Overall, 29 examples of humour under the categories of irony, teasing, banter, language play and joking were found in the data. To show both grades’ distribution between humour types and whether humour was initiated by the students or the teacher, tables 2 and 3 are presented below:
TABLE 2. The different types of humour detected during 5th grade lessons.
Irony Teasing Banter Language play Joking
Student initiated - 2 2 2 1
Teacher initiated 1 4 - - -
TOTAL 1 6 2 2 1
TABLE 3. The different types of humour detected during 9th grade lessons.
Irony Teasing Banter Language play Joking
Student initiated 1 3 3 4 -
Teacher initiated 7 - - - -
TOTAL 8 3 3 4 -
From the different humour categories, examples of language play and joking were the easiest to detect, because of their clear, simple definitions. Most overlap could be seen between the categories of irony, teasing and banter, since all share similar qualities.
Examples of irony are often presented in a teasing manner, which means they can be identified as ironic teases and thus, belonging to two categories. Also, banter belongs under the umbrella term of teasing and in addition, it can occasionally be ironic. In the current thesis, differentiating between the terms was done on the basis of the most evident character or trait of the extract. In other words, examples with clear ironic intent, saying the opposite of what one means, were presented under irony and examples with clear banter qualities, back-and-forth teasing, were presented under banter. Finally, the more neutral examples of teases were analysed as teasing. However, to avoid confusion, clear overlaps with another category of humour in specific extracts are pointed out in the analysis section.
After examples of various types of humour were differentiated, 15 most descriptive extracts were included in the present thesis: four to help define the categories of humour and 11 for further analysis. Detailed transcripts of each extract, using the transcription conventions of CA (see Appendix 2) were written down, showing information of talk such as overlapping turns, laughter, changes in voice, but also nonverbal qualities of interaction. The final extracts that were included in the thesis were chosen on the basis of the most typical and interesting examples, but exceptions were also pointed out. Each extract was reviewed multiple times to enable a detailed analysis, since each viewing of the extract tended to reveal new aspects for analysis.
Prior to the analysis of the extracts of humour, a language issue was considered. As L1 was the language of instruction during all the observed lessons, the final extracts included in the analysis section were translated into English. However, the translations are idiomatic and do not include the transcription conventions of conversation analysis included in the original transcripts. As ten Have (2007:110) points out, it is most important to provide the reader with as much information on the original talk as possible. Translations are only subsidiary and when the two language systems used differ greatly, such as Finnish and English, it can be intensely difficult and time consuming to provide a “morpheme-by morpheme gloss” equivalent to the original
interaction (ten Have 2007:110). Thus, the current thesis provides only free translations of the humour extracts.
In the analysis of humour extracts, close attention was paid to the construction of humour sequences in order to point out who initiated humour and to analyse the different types of humour used. Principles of CA were applied in the analysis and the different organisation structures including turn-taking, sequence organisation and repair organisation were taken into consideration. Also, a three-part sequence structure suggested in the works of Drew (1987) and Mulkay (1988) was used as an analytical tool to point out possible motives and responses, to identify humorous turns in the extracts and help construct a coherent analysis. Although the initial use of this framework was limited to teasing, it was proved in the work of Haapaniemi (2011) that the sequence structure is also applicable to other types of conversational humour. Thus, it was used in the present thesis in the form of motive - humorous turn - response.
Defining this tree-part sequence structure within each humour extract was used to get a clearer view of how humour is built in interaction in the specific context of a language classroom.
In addition to the video recorded lessons, the data of the current thesis included a 25-minute audio recorded interview with the teacher. Similar to the lessons, the interview was fully transcribed before its content was analysed. However, qualitative content analysis was applied as a method instead of conversation analysis, since the emphasis in the interview was in the teacher’s opinions and comparing them to the observations, instead of how she presented her views. According to Tuomi and Sarajärvi (2009:103) content analysis aims to give a condensed, general description of the studied phenomenon. Three types of content analysis have been differentiated by Eskola (2001:135-140): data-based, theory-guided and theory-based (Finn. aineistolähtöinen, teoriaohjaava ja teorialähtöinen analyysi). In the present study, theory-guided analysis was chosen as the analytic method for the interview. This approach relies mostly on information preserved from the data, but previous research can be used to guide the process of analysis (Tuomi and Sarajärvi 2009:96-97). The method is appropriate for the teacher interview, since the questions are more or less connected to the previously acquired content of the recorded lessons. Excerpts of the interview are included in chapter 6 and analysed in relation to the teacher’s perceptions of humour and how they connect with the lesson recordings. Before discussing the interview, the analysis of the
different humour excerpts acquired from the data is presented.
5 TYPES OF STUDENT AND TEACHER HUMOUR IN ELEMENTARY AND SECONDARY SCHOOL LESSONS
The current chapter presents the different types of humour that occurred in the classroom data starting from the most frequent categories of teasing and irony, to the less frequent banter and language play and finally, the rare use of canned joking. Each category of humour is briefly explained before presenting the examples of data (for more specific explanations see chapter 3.6). The chosen data extracts were found to be most descriptive of different humour categories. Through these extracts both teacher and student initiated humour examples are explained and described in all the categories when applicable, followed by an analysis of the particular humour use. A three-part sequential structure initially limited to teasing (Drew 1987, Mulkay 1988), but here applied to all types of humour is used as an analytical tool whenever possible to differentiate a three-part sequence structure of a motive, a humorous turn and a response in the extracts.