Describe the data you have collected so far
and how you are analysing it (activity 6)
The main source of data is from two Student Surveys. The parent survey did not have many
responses and my initial plan to contact whānau did not happened. In week 8 we were had
scheduled meetings but they were cancelled. I have felt that this term has been full of distractions
and other professional and personal demands have taken my attention.
responses and my initial plan to contact whānau did not happened. In week 8 we were had
scheduled meetings but they were cancelled. I have felt that this term has been full of distractions
and other professional and personal demands have taken my attention.
The use of Linc Ed is a source of quantitative data which is easy to access but it can
be time consuming to make sense of the data as it still needs to be sorted into categories.
Specific data collection tools:
Around the 20th February (Week 4) around 30 students completed the survey and I can
compare these surveys to another student survey done in Week 9.
compare these surveys to another student survey done in Week 9.
In week 4 and 5 the parent Survey was given out in paper form as well as emailed to those
whānau with emails.
whānau with emails.
At the end of term 1 I will use Linc Ed (our student management system to collect quantitative
data showing:
data showing:
1. student use over time
2. use by teachers
3. use by parents
Other possible data I could use is samples of student’s work during term 1, this could include
things of the google classroom and/or Linc ed. During the term most student have written a
learning letter to their parent, their own learning narratives, self reflections and other survey
responses during Puna Ako. We have also covered some of the learning dispositions:
collaboration, compassion, resilience and be a designer.
things of the google classroom and/or Linc ed. During the term most student have written a
learning letter to their parent, their own learning narratives, self reflections and other survey
responses during Puna Ako. We have also covered some of the learning dispositions:
collaboration, compassion, resilience and be a designer.
I am curious I look if there any parent comments by the end of the term and I am still wondering
how can I see parent views using Linc Ed.
how can I see parent views using Linc Ed.
Update: I was going to survey the parents in Week 11 but the follow up survey has been delayed.
I have really struggled with finding the time to process the data.
I have really struggled with finding the time to process the data.
According to Babione (2014) analysing qualitative data involves more critical and divergent
thinking compared to quantitative data. The surveys I used with whānau and ākonga asked for
individualised comments. I have had to sort the data by looking at themes. Then use these as a
guide to organise the data. Analysing the data was on-going as students and whānau gave feedback
which we responded to in different ways. The approach was altered after discussing the surveys
with members my teaching team. Ākonga in our Puna Ako developing their understanding of our
dispositions and increased the amount they shared their learning with their whānau. Some of the
data from the surveys was qualitative so sorting that data into categories was simple. Based on
these categories and themes I can then make assumptions and interpretations
thinking compared to quantitative data. The surveys I used with whānau and ākonga asked for
individualised comments. I have had to sort the data by looking at themes. Then use these as a
guide to organise the data. Analysing the data was on-going as students and whānau gave feedback
which we responded to in different ways. The approach was altered after discussing the surveys
with members my teaching team. Ākonga in our Puna Ako developing their understanding of our
dispositions and increased the amount they shared their learning with their whānau. Some of the
data from the surveys was qualitative so sorting that data into categories was simple. Based on
these categories and themes I can then make assumptions and interpretations
Riel (2014) discusses how to analyse data. I found this video was helpful in various ways.
The first part is about organising data to create a storyline. The main messages from this is be
aware of other possible ways to collect data. I thought for my own action research it would be
interesting to look at participation rates and attendance. Another source of data which I was keen
to take advantage of was parent conferences. Riel (2014) believes that knowing what students share
with their parents is good for highlighting "things that are really effective in the classroom".
Another suggestion that I found helpful was to go back to the original research question and
review the intended outcomes.
The first part is about organising data to create a storyline. The main messages from this is be
aware of other possible ways to collect data. I thought for my own action research it would be
interesting to look at participation rates and attendance. Another source of data which I was keen
to take advantage of was parent conferences. Riel (2014) believes that knowing what students share
with their parents is good for highlighting "things that are really effective in the classroom".
Another suggestion that I found helpful was to go back to the original research question and
review the intended outcomes.
The second part is to explore the data to find a story. In this part you look for ideas,
relationships and patterns so you can condense it so others can better understand it.
Suggestions I found helpful were to use digital tools, e.g. for data written by ākonga and
whānau, technology like Wordle can be used to identify word frequency.
Use of collaborative language e.g. we versus I. Riel (2014) also suggested to use a critical
stance and get feedback from others. The third part is to display the data and this is like
telling a story about the research.
relationships and patterns so you can condense it so others can better understand it.
Suggestions I found helpful were to use digital tools, e.g. for data written by ākonga and
whānau, technology like Wordle can be used to identify word frequency.
Use of collaborative language e.g. we versus I. Riel (2014) also suggested to use a critical
stance and get feedback from others. The third part is to display the data and this is like
telling a story about the research.
References:
Babione, C. (2015). Practitioner Teacher Inquiry and Research. USA: John Wiley & Sons.
(e-copy available in Unitec library)
(e-copy available in Unitec library)
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