Reflecting on Evidence
The Ministry of Education says that well-planned data gathering can reveal new patterns of insight, and justify change. (MoE, n.d). Ultimately the goal of inquiry is to create change. The data gathered so far has mainly been quantitative. Specifics around gender, ethnicities that students identify with, homework and organisational patterns and tools used.
There were very low survey response rates from parents; 4 out of 12 respondents. Parents who did respond already had well-established relationships with me. I think not having a relationship with all parents was a significant barrier to them participating. There were 9 student survey responses out of 12. Of the three students that did not respond, one had just arrived in NZ and spoke no English, and the other two were absent for most of the term. One student was suspended during the inquiry. One student attended school for 5 days of the 6-week inquiry duration.
I completed 2 observation charts during class time and this was useful information for the qualitative data. I was not able to conduct any of the student interviews due to time restraints. In future, I would need to get surveys completed during term time for better participation.
Analyzing involves coding that leads to categorizing that leads to concepts, Lichtman, (2010) (cited in Babione, 2015). Examples of quantitative data have been displayed in the following graphs using Google Forms.
The centralised storage of the survey results in Google Drive facilitates the analysis processing of the data with predefined statistical functions and charts (Haddad & Kalaani, 2014). One of the functions is converting the data into a percentage. This was an effective method for organising and managing the survey.
I used predetermined categories to analyse data. Efron and Ravid's (2019) Data Analysis and Interpretation framework was used to determine categories relevant to data collated for coding;
Babione (2015) describes coding as an interpretive technique to sort data into categories as an aid to finding patterns. Flexibility to collect qualitative data as the inquiry progresses is showing success. In spite of needing more time to complete the student interviews and to fully ascertain the successful role, Trello played in the inquiry, the written responses to surveys given, anecdotal records and observations give good indications of the progress towards helping Maori & Pasifika students manage themselves and complete the required learning.
Evidence is showing that 60% of Māori and Pasifika students need more help to be organised to complete required tasks, with another 30% saying they sometimes or maybe need more help. 40% of students felt they fully understood the requirements of the task but only 10% said they had completed the required tasks. Half of the group did homework only when they were made to and when looking into the predetermined category of 'feeling supported from home' there were some concerning trends of little or no help offered by some whānau. According to MOE (2008), there is not any evidence/research to show direct links between home-school partnerships and improved student outcomes. However, in my first inquiry, the evidence in support of home-school partnership was an overwhelming success. This is an area I would like to continue exploring next year.
When reflecting on the evidence so far it is important to consider future improvements. There were significant issues with the timeframe. Sending the survey out during a holiday break was not ideal! Limited skills using Trello and the limitations of the program itself, were highlighted once the inquiry was underway. Also, making the purpose of the inquiry clear to participants and following-up with non-respondents needs improvement.
REFERENCES
Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
Efron, S. E., & Ravid, R. (2020). Action research in education: A practical guide. (2nd ed.). New York, NY: The Guilford Press.
Haddad, R. J., & Kalaani, Y. (2014). Google Forms : A Real-Time Formative Assessment Approach for Adaptive Learning. Proceedings of the 2014 American Society for Engineering Education, ASEE Annual Conference and Exposition. Retrieved from https://digitalcommons.georgiasouthern.edu/electrical-eng-facpubs/37/?utm_source=digitalcommons.georgiasouthern.edu%2Felectrical-eng-facpubs%2F37&utm_medium=PDF&utm_campaign=PDFCoverPages
Ministry of Education.(n.d.). Data analysis. Retrieved from http://elearning.tki.org.nz/Teaching/Teaching-as-inquiry/Data-analysis#js-tabcontainer-1-tab-2
Ministry of Education, (2008). Successful Home-School Partnerships. Retrieved from https://www.nzcer.org.nz/system/files/884_Successful_Home-School_Partnership-v2.pdf
There were very low survey response rates from parents; 4 out of 12 respondents. Parents who did respond already had well-established relationships with me. I think not having a relationship with all parents was a significant barrier to them participating. There were 9 student survey responses out of 12. Of the three students that did not respond, one had just arrived in NZ and spoke no English, and the other two were absent for most of the term. One student was suspended during the inquiry. One student attended school for 5 days of the 6-week inquiry duration.
I completed 2 observation charts during class time and this was useful information for the qualitative data. I was not able to conduct any of the student interviews due to time restraints. In future, I would need to get surveys completed during term time for better participation.
Analyzing involves coding that leads to categorizing that leads to concepts, Lichtman, (2010) (cited in Babione, 2015). Examples of quantitative data have been displayed in the following graphs using Google Forms.
 |
| Main (or first) ethnicity students chose to identify with. Interesting to note that all students were listed on KAMAR as Māori or Pasifika, yet 20% did not identify as that being their first ethnicity and instead chose NZ European. |
The centralised storage of the survey results in Google Drive facilitates the analysis processing of the data with predefined statistical functions and charts (Haddad & Kalaani, 2014). One of the functions is converting the data into a percentage. This was an effective method for organising and managing the survey.
I used predetermined categories to analyse data. Efron and Ravid's (2019) Data Analysis and Interpretation framework was used to determine categories relevant to data collated for coding;
- Students feel supported from home
- Students feel supported at school
- Students are empowered to learn
- Students understand their end goal or expectations around achievement.
Babione (2015) describes coding as an interpretive technique to sort data into categories as an aid to finding patterns. Flexibility to collect qualitative data as the inquiry progresses is showing success. In spite of needing more time to complete the student interviews and to fully ascertain the successful role, Trello played in the inquiry, the written responses to surveys given, anecdotal records and observations give good indications of the progress towards helping Maori & Pasifika students manage themselves and complete the required learning.
Evidence is showing that 60% of Māori and Pasifika students need more help to be organised to complete required tasks, with another 30% saying they sometimes or maybe need more help. 40% of students felt they fully understood the requirements of the task but only 10% said they had completed the required tasks. Half of the group did homework only when they were made to and when looking into the predetermined category of 'feeling supported from home' there were some concerning trends of little or no help offered by some whānau. According to MOE (2008), there is not any evidence/research to show direct links between home-school partnerships and improved student outcomes. However, in my first inquiry, the evidence in support of home-school partnership was an overwhelming success. This is an area I would like to continue exploring next year.
When reflecting on the evidence so far it is important to consider future improvements. There were significant issues with the timeframe. Sending the survey out during a holiday break was not ideal! Limited skills using Trello and the limitations of the program itself, were highlighted once the inquiry was underway. Also, making the purpose of the inquiry clear to participants and following-up with non-respondents needs improvement.
REFERENCES
Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
Efron, S. E., & Ravid, R. (2020). Action research in education: A practical guide. (2nd ed.). New York, NY: The Guilford Press.
Haddad, R. J., & Kalaani, Y. (2014). Google Forms : A Real-Time Formative Assessment Approach for Adaptive Learning. Proceedings of the 2014 American Society for Engineering Education, ASEE Annual Conference and Exposition. Retrieved from https://digitalcommons.georgiasouthern.edu/electrical-eng-facpubs/37/?utm_source=digitalcommons.georgiasouthern.edu%2Felectrical-eng-facpubs%2F37&utm_medium=PDF&utm_campaign=PDFCoverPages
Ministry of Education.(n.d.). Data analysis. Retrieved from http://elearning.tki.org.nz/Teaching/Teaching-as-inquiry/Data-analysis#js-tabcontainer-1-tab-2
Ministry of Education, (2008). Successful Home-School Partnerships. Retrieved from https://www.nzcer.org.nz/system/files/884_Successful_Home-School_Partnership-v2.pdf
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