Step 1: Describe the data you have collected
I have collected two forms of data for my study, one quantitative and one qualitative. The quantitative data is in the form of two number knowledge tests (see my Research and community informed practice assessment for an example of this test), one given at the start of the intervention and one at the end. By giving the children the same test seven weeks apart, I would easily be able to see how my intervention affected children's maths outcomes. The qualitative data took the form of short interviews with key children conducted before and after the intervention to measure how the intervention affected their engagement in and attitudes towards maths. I had also planned to measure whole class engagement using a tally chart system, but this proved impossible to implement while trying to teach my maths groups.
Step 2: Explain how you are analysing your data
In the analysis of my qualitative data (student interviews) I have followed the lead of Bogdan and Biklen (2003) who stated that "those new to the formal inquiry process are advised to leave the formal analysis until most of the data has been collected, as new researchers often do not have the theoretical and substantive background to plug into issues and themes when they first arrive
on the scene". I therefore waited until the end of my study to analyse the data. Boyatzis (1998) states that analysis should be based on categories drawn from your research question or a literature review. During my research proposal, I identified the following categories:
I have collected two forms of data for my study, one quantitative and one qualitative. The quantitative data is in the form of two number knowledge tests (see my Research and community informed practice assessment for an example of this test), one given at the start of the intervention and one at the end. By giving the children the same test seven weeks apart, I would easily be able to see how my intervention affected children's maths outcomes. The qualitative data took the form of short interviews with key children conducted before and after the intervention to measure how the intervention affected their engagement in and attitudes towards maths. I had also planned to measure whole class engagement using a tally chart system, but this proved impossible to implement while trying to teach my maths groups.
Step 2: Explain how you are analysing your data
In the analysis of my qualitative data (student interviews) I have followed the lead of Bogdan and Biklen (2003) who stated that "those new to the formal inquiry process are advised to leave the formal analysis until most of the data has been collected, as new researchers often do not have the theoretical and substantive background to plug into issues and themes when they first arrive
on the scene". I therefore waited until the end of my study to analyse the data. Boyatzis (1998) states that analysis should be based on categories drawn from your research question or a literature review. During my research proposal, I identified the following categories:
1 - Reasons behind student's enagement or lack thereof
2 - Student's feelings of agancy over thier own learning
3 - How students feel about the gamification system
4 - How relevant the principles of Tuakana-Teina are to my particular setting
These categories can then be organised into themes so that overarching patterns can be identified (see Marshall & Rossman, 2011) for an overview of thematic analysis)
The qualitative data will be analysed using statistical methods. I will calculate the pass marks and each child's particular number knowledge level, and compare the two data sets. I will also be able to drill down deeper into the data, for example, it may be that children have improved their instant recall of times tables facts, but are still struggling with place value concepts.
Step 3: Reflect on your evidence so far
At this early stage of analysis, the qualitative data is looking promising. At the start of the school year, 17% of my class scored at level 5b on the number knowledge test (below age level expectation). After the intensive intervention, only 4% of the class scored at a 5b level. 3 children (10% of the class) also moved from a Stage 6 (at age expectation) to a Stage 7 (Year 7 expectation). In fact, only 2 children (7% of the class) scored worse on the second test, with a large proportion of the children posting significantly improved scores. I have not yet performed formal statistical tests to see if the result is statistically significant, but I expect it to be so.
Step 3: Reflect on your evidence so far
At this early stage of analysis, the qualitative data is looking promising. At the start of the school year, 17% of my class scored at level 5b on the number knowledge test (below age level expectation). After the intensive intervention, only 4% of the class scored at a 5b level. 3 children (10% of the class) also moved from a Stage 6 (at age expectation) to a Stage 7 (Year 7 expectation). In fact, only 2 children (7% of the class) scored worse on the second test, with a large proportion of the children posting significantly improved scores. I have not yet performed formal statistical tests to see if the result is statistically significant, but I expect it to be so.
The interviews I conducted produced some interesting results, but I have not had a chance to properly code it for analysis yet. On first glance, one factor that may prove to have had an effect is what Babione (2015) calls "status differential". "Status differential can be present with parents and community, but it is especially salient when conducting inquiry studies with youth (Babione, 2015, p 149). I need to make sure that I am not reading into the data what I want to hear, that the voice of the researcher does not become privileged.
References:
References:
Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
Bogdan, R. C., & Biklen, S. K. (2003). Qualitative Research of Education: An Introductive to Theories and Methods (4th ed.) In: Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
Boyatzis, R. E. (1998). Transforming qualitative information: Thematic analysis and code development. Thousand Oaks, CA, US: Sage Publications, Inc.
Marshall, C., & Rossman, G. B. (2011). Designing Qualitative Research (5th ed.). Thousand Oaks, CA Sage Publications.
Bogdan, R. C., & Biklen, S. K. (2003). Qualitative Research of Education: An Introductive to Theories and Methods (4th ed.) In: Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
Boyatzis, R. E. (1998). Transforming qualitative information: Thematic analysis and code development. Thousand Oaks, CA, US: Sage Publications, Inc.
Marshall, C., & Rossman, G. B. (2011). Designing Qualitative Research (5th ed.). Thousand Oaks, CA Sage Publications.
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