Last week I facilitated an Instructional Round at a neighbouring school and tried to embrace some of the principles of Data Wise into the evidentiary analysis of the observations. The initiative was well received so I thought I would share it.
There were 3 groups of principals who observed students in 5 classes over an hour. Our prime focus was on student understanding of and connection to the lessons stated learning intention. We made 75 observations which were grouped and regrouped according to some headings (and this was the initiative) and then tallied the number of observations in each group calculating each groups percentage of the total number of observations.
We were then able to make some generalisations for example:
- over …% of students when asked were able to state the learning intention of the lesson.
- over …% of students when asked were able to make a connection between the lesson and their personal improvement goal.
- over …% of students when asked were able to state why it was important to learn that lesson (skills or understanding).
This school had been providing some professional learning on learning intentions over the past few months for teachers. We saw the intentions written in some form in every class. The students were questioned during lessons and were completing a variety of tasks from debating, to planting, to playing a mathematics game.
This information was going to be shared with the observed teachers later in the day. One comment made was that it would have been nice to have a snapshot of this type of data before they started their professional learning program to measure progress. Anecdotally the school felt that there was a significant change and would then decide on its next phase of work.
My reflections were that although the analysis was not an exact science it did prove useful and I’m taking this back to my implement in my school. As as teacher I would have liked some examples of the sort of comments students made (random example) to get an idea of depth of understanding.