America’s love for data is nothing new. The real challenge is asking whether the data makes sense. As more states apply data to the classroom in the form of standardized tests and data-driven improvement and accountability (DDIA) programs, this challenge becomes critical for the future of our children and their ability to meet their fullest potential.
DDIA programs can provide teachers and students broad goals to aim for, establishing a baseline of accountability. At the same time, we should all question what data is gathered, how the data is used and, most importantly, whether the data is helping us improve students’ ability to learn. These questions are especially timely now as Connecticut moves toward using the Smarter Balanced assessments for the first time.
In the newly released report, Data-driven Improvement and Accountability, Boston College education professors Andy Hargreaves and Harry Braun say schools must ask these questions because high-stakes measures tend to put adverse and perverse pressure on administrators, teachers, and students. As a result, DDIA programs set back real and sustainable improvement opportunities. These issues must be addressed now because Hargreaves and Braun argue that strategies in U.S. education are generally inferior to those of other countries.
When it is used thoughtfully, DDIA provides educators with valuable feedback on their students’ progress by pinpointing where the most useful interventions can be made.
However, in the United States, measures of learning are usually limited in number and scope, and the consequences for schools and teachers of apparently poor performance are often punitive:
- Accountability impedes improvement. Under pressure to avoid poor scores and unpleasant consequences, many educators concentrate their efforts on narrow tasks such as test preparation and coaching targeted at those students whose improved results will contribute most to their school’s test-based indicators.
- Accountability is undermined because more and more teachers “game the system” to get their scores up quickly.
To ensure that student improvement becomes the main driver of DDIA – and not simply an afterthought to accountability concerns – Hargreaves and Braun suggest basing professional judgments and interventions on a wide range of evidence and indicators that properly reflect what students should be learning. They also recommend designing systemic reforms to promote collective responsibility for improvement, with top down accountability serving as a strategy of last resort when this falls short – practices common in high-performing countries and systems.
As DDIA programs become part of our educational culture, schools should look closely at the mass of Big Data we gather every school year and ask questions that can really help students achieve and improve.