Practical measures are designed to provide rapid feedback that enables practitioners to assess and improve their practices. They are in contrast to research measures -- which tend to be laborious to administer and thus unable to rapidly inform implementation -- and accountability measures -- which tend to be unable to pinpoint where to take action. We developed a system of practical measures that provide information about key aspects of middle-grades mathematics teaching and professional learning.

An assumption of this work is that these tools will not, by themselves, lead to instructional improvement. Our research indicates the importance of integrating the practical measures in ongoing, high-quality professional learning. We are investigating the potential of different routines and representations for supporting various role groups to interpret and act on the basis of the resulting data.

Data visualizations provide supports to making sense of practical measures and enhancing improvement routines. We are co-designing a data visualization platform to document how the design of visual analytics can play an important role in improvement efforts. With our design studies, we’re trying to understand the range of sensemaking that can occur with data representations (charts, graphs etc.), and the conditions under which data is taken up productively.