Читать книгу The Data Coach's Guide to Improving Learning for All Students - Katherine E. Stiles - Страница 16

Data have no meaning. Meaning is imposed through interpretation. Frames of reference, the way we see the world, influence the meaning we derive from data. Effective data users become aware of and critically examine their frames of reference and assumptions (Wellman & Lipton, 2004, pp. ix–xi). Conversely, data themselves can also be a catalyst to questioning assumptions and changing practices based on new ways of thinking.

This assumption is closely related to the first and is why we place so much emphasis on surfacing assumptions, particularly assumptions about children and their capabilities and beliefs about teaching and learning. If one holds the view that whether students learn is the student’s responsibility and not that of the teacher, one might then look at a student’s poor performance on assessments and conclude that it is entirely the student’s fault. There is nothing to be done to improve teaching. If one believes that African American students are not as capable as White students, then data that reveal an achievement gap between these groups does nothing but confirm that belief. The reaction is complacency or resignation. Beliefs about teaching also profoundly influence data interpretation. For example, one teacher believes that students learn best when they are actively constructing their own meaning. Another believes that skill building and practice and teacher talk are how students learn. When examining student work that reveals a student’s confusion, these two teachers will react very differently.

On the other hand, when one is open to critically examining assumptions, data can be a catalyst to discarding old frames of reference and embracing new ones. We have seen educators in our project look at disaggregated student-learning data and become outraged by inequities that they had not been aware of before. Simply examining data about schools that were closing achievement gaps has caused others to question their belief that these gaps are inevitable. When teachers observed that teaching in a new way actually reached more students, they changed their assumptions about teaching and learning. Through their collaborative inquiry, many Data Team members threw out unproductive, blame-the-victim explanations of students’ poor performance and shifted the focus to instruction.