Читать книгу The Data Coach's Guide to Improving Learning for All Students - Katherine E. Stiles - Страница 40

During our work with schools, we observed Data Teams that were quite proficient at using data to identify problems, but, initially, they did not do the best job of verifying the causes. Often they would leap to assigning cause without checking out their theories. For example, as you can read in the Clark County, Nevada, case study in Chapter 8, one of the Data Teams accurately identified that their students had difficulty solving nonroutine mathematics problems. They concluded that the cause was that students were not persisting and that they were unable to read the problems. It wasn’t until they actually observed 40 students engaged in problem solving that they saw their theory didn’t hold water. Students were persisting. And even when the problem was read aloud to the students, they still weren’t able to solve it. Through their observations and by consulting research, the team came to the conclusion that the cause of the problem was that students lacked problem-solving strategies, not persistence. This led to a very different course of action. The Using Data Process builds in checks and balances to guide teams to verify the causes of problems with data and research. Another place the process can break down is in generating solutions. Data Teams would seize upon a strategy such as implementing a professional development workshop. But they wouldn’t think through exactly what that workshop would accomplish that would get them closer to their student-learning goal. This led us to incorporate logic-model thinking to increase the accuracy of Data Teams’ action planning.