Developing a culture of data analysis requires more than just presenting the data and assuming it will automatically transform teachers’ thinking. Rather, teachers need sensitive coaching and facilitation to study the data and make connections between data and instructional decision making.
School leaders you need to:
- Ensure there is a shared belief in the value of data;
- Develop data literacy capacity and skills;
- Plan times to collaboratively interrogate the data;
A common statistical way of standardising data on one scale so a comparison can take place is using a z-score. The z-score is like a common measure for all types of data. Each z-score corresponds to a point in a normal distribution.
To find a z-score for a specific result in a group of results:
First, calculate the Mean for the group. Then calculate the Standard Deviation. Finally, calculate the z-score using the formula: (student result - Mean) / Standard Deviation.
Stanine scores are used in education to compare student performance over a normal distribution.
Stanine scores convert raw test scores to a one-digit whole number to simplify test interpretation.
Typically, stanine scores between 4 and 6 are considered average, scores of 3 or less are below average while scores of 7 or greater are above average.