The University of Wisconsin and the Albert Shanker Institute are jointly developing the Educator Day Reconstruction Method, which provides a new and flexible way of measuring teachers' work and the broader context where it unfolds. The Educator DRM can be adapted to meet a district's information needs and can be used to complement existing data sources. We view this customization process as something to be accomplished collaboratively, with districts and stakeholders. Our end goal is to develop a tool that shed light on teaching and learning conditions and eventually be used to enrich decision-making and improvement efforts at the school and district levels.
A team led by Nobel Prize winner Daniel Kahneman developed the original DRM - and here. The method captures evidence of people’s activities, affective experiences, and characteristics of the situations in which they occur in two steps. First, respondents write an outline of the different activities they did the previous day. Writing about one's day has the effect of "reviving" memories about the specifics of each activity. In a second step, respondents answer a brief questionnaire in which they record details about each activity. The most distinctive feature of the DRM is that it measures how people feel during specific activities of daily life. Measuring what people do and experience in this way yields much richer, and more accurate data. The instrument has been successfully implemented in countries such as China, Ghana, India, Mexico, Russia, South Africa, and Spain.
Why a New Tool for Measuring Teachers' Work?
Conventional instruments such as annual "climate surveys" can provide useful information but often leave many questions unanswered. The DRM has some advantages over existing common approaches:
- The DRM approach has the potential to capture evidence of teachers' work that is more detailed and accurate than one-time surveys.
- A unique feature of the DRM is that it measures how teachers feel about different facets of their work as they perform it. This information can provide useful insight into how the contexts of teachers’ work affect their engagement and satisfaction, as well as the quality of teacher/student relationships, an important determinant of student learning.
- When aggregated to the school level, DRM data can provide timely and important diagnostic information about school climate, which also influences teacher and student outcomes.