Week 30 Reflect on Your Evidence (Take Action)

Step 1: Describe the data you have collected

As part of my inquiry, I collected data during the “Scan” phase of the Spiral of Inquiry, the aim of which was to find out how my students-to-be felt about learning particularly maths and robotics. This data was used to refine my area of further research. 

Since then all of my data collection has been during the “Take Action” phase as per my Action Plan.

On a daily basis, I have been collecting quantitative data on student collaboration and engagement using tally marks on interval behaviour logs, to see if students were actively collaborating and engaged in their learning when using the Bee-bots. Qualitative data has been collected daily in the form of post-observation interviews with each of the four target students, in order to clarify the findings from the interval behaviour logs. 

Number Knowledge tests were carried out before and after the teaching intervention to obtain before and after quantitative data, which will indicate if the teaching intervention was effective in raising student achievement.

Before analysis I ensured the data was ‘clean’, it was consistent, accurate and complete as explained on the TKI website.

Step 2: Explain how you are analysing your data

When analysing the qualitative data (post-observation interviews) I coded the responses to create quasi-quantitative findings (Gibbs, 2007) based on whether the students had a positive or a negative experience during the maths lessons. As I was assigning one overall code to a whole range of data questions (which is a subjective decision)  I had to be very careful that I was ethical with the data (Babione, 2015). 

As can be seen in the data above, the first weeks learning activities (Week 2) were not engaging for the students. I reflected on this in my Week 26 blog post and substantially changed the activities, focusing heavily on student engagement at the expense of collaboration.

With the quantitative data, I discarded the data from Week 2 (where the students were not engaged) and focused on Week 3-5 and the new learning activities. I discovered that students were engaged 80% of the time.

I then compared the pre and post test percentage scores for the students Number Knowledge Tests using a line graph as it is a good tool to track achievement over time as advised on the TKI website. 

Step 3: Interpretation of the data

Having analyzed the data it is evident that from Week 3 onwards students were engaged in the Learning Activites. The data shows that all students have made progress in their learning (as evident in the Number Knowledge Test Scores) although for two students the progress was slight.

A more complete picture of achievement could have been obtained by looking at the pre and post test scores for all students in the class, comparing the median scores. The data could then have been disaggregated to look at individual achievement results.

However, I have still not fully answered my inquiry question. Whilst I have evidence that students have increased their engagement and subsequently their achievement, I have no evidence that it was the robotics and not my teaching that produced this success. I needed to have a control group, that I taught but without the use of robotics, to compare them to in order to obtain evidence that robotics increases engagement and therefore student outcomes.

My inquiry also did not provide evidence for collaborative groups improving student outcomes as I focused too heavily on engagement at the expense of collaboration.

In future inquiries, I will narrow both my focus and data collection. This will make collecting data in a teaching environment more manageable. Narrowing the focus of my inquiry question, being very clear about what I am looking for, and checking that the methodology I employ to collect the data will actually give me useful results. 

References

Babione, Carolyn. Practitioner Teacher Inquiry and Research, John Wiley & Sons, Incorporated, 2014. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/unitec/detail.action?docID=1887742.

Gibbs, G. (2007). Analyzing qualitative data . London, England: Sage.

Kaser, L. & J. Halbert. (2017). The Spiral Playbook: Leading with an inquiring mindset in school systems and schools. C21 Canada. Retrieved from http://c21canada.org/wp-content/uploads/2016/10/Spiral-Playbook.pdf

Reading and analysing data / Evidence for learning / Home - Assessment. (n.d.). Retrieved March 23, 2019, from http://assessment.tki.org.nz/Using-evidence-for-learning/Reading-and-analysing-data