“Schools are data rich and information poor” is a quote I frequently hear. The focus on increased testing, high-stakes testing, accountability, and professional learning communities has yielded mountains of data from standardized tests, formative assessments, locally-developed assessments, and student work. We’re doing the right thing – looking at the data. But often when you look closely teachers, schools, and districts are really not digging deep and reflecting on possible trends, causes, and effective solutions.
However, this is not a result of lack of motivation, concern, or willingness to persevere. It’s simply a lack of skill. Most teacher training and prep does not include how to analyze data and dig deep to truly understand what the data (numbers, observatons, facts) means and its implication for instructional practices and student achievement. Despite the that most of us are not data analysis experts, there are some steps teachers, schools, and districts can take to build skill sets for data analysis:
- Process data through a team or PLC (professional learning community) that understands the process and protocols of collective inquiry.
- Data needs to be presented in a a simple format – not simplistic.
- Data needs to be in the hands of teachers and schools in a timely manner.
- Provide teachers with PD related to looking at data.
- Consider using a facilitator to guide a dialogue surrounding data sets – this is important so the focus remains on the data not an indivudals opinion, biases, agenda etc.
- Start with a question about the data.
- Follow a protocol for facilitation and data conversations (see below for a numbers of protocols).
- Look at multiple sources of data (triangulate the data).
- Look for trends and patterns among the data sources.
- Drill down to look at individual student needs – identify and act on the implications of the patterns for students.
- Reflect on the reasons for student performance – what in our teaching might be preventing student achievement and the changes that need to occur? Identify and act on the implications for our instuction.
- Create a plan with interventions and actions steps, ways to monitor progress, timelines to collect and reflect on the data.
Using Data For Meaningful Change Blog (Highly Recommened – Follow in Twitter):
Data My New Dirty Word
ATLAS Looking At Data http://www.nsrfharmony.org/protocol/doc/atlas_looking_data.pdf
Methods For Looking At Student work http://www.lasw.org/methods.html
Looking At Data Sets http://schoolreforminitiative.org/protocol/doc/looking_data_sets.pdf
Data Driven Dialogues http://www.nsrfharmony.org/protocol/doc/data_driven_dialogue.pdf