No more random acts of teaching: high levels of achievement are the result of systematic, targeted and purposeful instruction. Without data, instruction becomes a series of well-intentioned but essentially random acts of teaching

Leadership, Nov-Dec, 2001 by Dennis Fox

Students who require the "re-do" level of support just need additional practice to meet the standard. For example, a student who knows multiplication facts but can't recall them quickly; a student who knows how to write neatly in cursive but can't write fluidly; and a student who recognizes sight words but can't read them rapidly.

Students who require the "review" level of support generally understand what's expected, but typically have a minor area(s) of weakness. Students only require a brief explanation and additional guided practice. For example, a student who is able to write a strong paragraph but has trouble with quotation marks; or a student who understands a particular math process but has trouble with one specific step in the process.

Students who require the "re-teach" level of support don't understand the basic concepts and/or skills targeted by the teacher. They typically require the teacher to start from the beginning of the lesson or unit. For example, a student who doesn't understand the relationship between letters and sounds -- or a student who doesn't know the difference between fact and opinion -- would require re-teaching.

Students who require special interventions may have very different needs from one another, and those differences are often overlooked. Using data to systematically group students leads to purposeful instruction and rapid student progress.

Identifying obstacles

Throughout the institute, the principal has many opportunities to identify obstacles likely to be encountered when he/she returns to school and begins to make data a part of the decision-making process. The principal is also given the opportunity to develop strategies for overcoming those obstacles.

Among the obstacles most often cited are: insufficient time for working with data; inadequate tools and strategies; absence of staff expertise; fear of change; skepticism toward new ideas; "been there, done that" attitude; complacency; fears and misconceptions about data; concern over implied accountability; lack of technology; building ownership; and the "this too shall pass" position.

We can't discuss all of the obstacles and strategies here, so let's look at the issue that is most often cited: lack of time. Given it is unlikely schools will receive additional time for working with data, it is up to the principal to weave data into existing structures and practices. A sample of the ideas generated during the institute are listed below.

1. Focus on data analysis goals in teacher evaluation plans and conferences.

2. Make data a priority for professional development.

3. Discuss data at faculty meetings.

4. Require a specified portion of department/grade level/team meetings be devoted to data.

5. Require that budget requests include supportive data.

6. Select textbooks, supplemental materials and equipment based on data.

7. Discuss data in meetings with teacher-leader groups.

8. Identify a group of teachers who are open to working with data and provide them with professional development, ongoing technical assistance and a forum to share their expertise and success.