By Denyse Doerries, Ph.D., and Fritz Geissler, M.Ed.
Teachers' skills and their confidence in their skills are pivotal to improved student achievement (Marzano, Pickering, & Pollock, 2001). Many of the "new" schoolwide initiatives target the adoption of evidence-based instructional practices; however, the rate at which they are implemented by teachers is quite low (Kratochwill, Volpiansky, Clements, & Ball, 2007). A critical factor in ensuring implementation is obtaining teacher "buy-in." This is best accomplished when teachers see the need for a change and have the skills necessary to implement the change or perceive that they have the support to acquire needed skills (Batsche, 2008; Fixsen, Naoom, Blasé, & Wallace, 2007).
Presentation of school data in a user-friendly format can be pivotal in providing general and special educators the rationale and motivation to acquire new teaching skills (Batsche, 2008). Grade-level data teams can adapt school-level strategies to promote literacy, numeracy, and social competence to a specific grade level and classroom as well as create opportunities for learning and implementing evidence-based strategies (Ervin, Schaughency, Goodman, McGlinchey, & Matthews, 2007). Grade-level data help to focus discussions, answer basic questions, and drive instruction.
Determining Which Types of Data to Use
Determining what data to use is a crucial first step in using data to improve student achievement (Center for Performance Assessment, 2006). Different kinds of data answer different types of questions for schools and teachers. Data from state tests can assist in identifying trends among content areas and student subgroups. Referral data can help schools examine times and places resulting in most referrals. Benchmark tests and classroom-based assessments give teachers a better understanding of what their students know and where students need help.
Use of classroom-based assessment data can most impact instruction on a daily basis. Designing classroom-based assessments prior to teaching a unit allows educators to determine what they want their students to know and how they will know that the students know it (DuFour, 2004). Classroom assessments may consist of pretests, end-of-unit tests, or brief formative assessments given throughout a unit.
Analysis and Interpretation of Data
Perhaps the most important issue to address is how teachers will respond to the results of assessments. Data teams, consisting of teachers from the same grade level, content area, or co-teaching pairs, can work together to make sense of the data as well as design instruction to meet the needs of their students. (To hear a positive discussion that includes connecting assessment and instruction from an effective co-teaching pair, listen to the new co-teaching podcast available at http://education.wm.edu/centers/ttac/resources/podcasts/index.php)
By examining the results for each student, teachers can begin to ask and answer the following questions (Center for Performance Assessment, 2006):
1. Which students are making progress and which need further help?
2. What is working where students are being successful?
3. What does instruction look like in these areas?
4. How can all teachers build on this success?
5. Are there other instructional strategies that could help meet the needs of the students?
Designing Effective Instructional Practices
The way that data and other types of assessment information are used determines the effectiveness of data analysis. While answering the questions is part of the process of meeting the needs of ALL students, it also provides an opportunity for teachers to learn from each other's strengths (DuFour, 2004). General and special education teachers can share their areas of expertise to assist each other in learning new strategies to benefit students. The way that one teacher teaches fractions may work very well, while another teacher's approach to decimals is successful. By being exposed to others' ideas, teachers are able to choose what works best for a given student. Examining the results for individual students also helps teachers decide who needs additional instruction, practice, or enriching experiences. Groupings may be arranged within a single classroom, particularly a co-taught classroom, or they may be formed across two or three classrooms.
Data analysis provides a forum for co-teachers and grade-level teachers to share their skills and focus on students' needs. Data should become the key for designing and implementing effective evidenced-based instructional practices that best ensure student success.
Batsche, G. (2008). Building support. Available: www.rtinetwork.org
Center for Performance Assessment. (2006). Questions for data team leaders to use when facilitating data team meetings. Retrieved September 8, 2008, from http://www.sde.ct.gov/sde/lib/sde/pdf/curriculum/cali/4cidtquestionsfordtleader.pdf
DuFour, R. (2004). What is a "professional learning community"? Educational Leadership, 61(8), 6-11.
Ervin, R. A., Schaughency, E., Goodman, S. D., McGlinchey, M. T., & Matthews, A., (2007). Moving from a model demonstration project to a statewide initiative in Michigan: Lessons learned from merging research-practice agendas to address reading and behavior. In S. R. Jimerson, M. K. Burns, & A. M. VanDerHeyden (Eds.), Handbook of response to intervention (pp. 354-377). New York: Springer Science+Business Media, LLC.
Fixsen, D. L., Naoom, S. F., Blasé, K. A., & Wallace, F. (2007). Implementation: The missing link between research and practice. American Professional Society on the Abuse of Children (APSAC) Advisor, 19(1 & 2), 3-11.
Kratochwill, T. R., Volpiansky, P., Clements, M., & Ball, C. (2007). Professional development in implementing and sustaining multitier prevention models: Implications for Response to Intervention. School Psychology Review, 36(4), 618-631.
Marazano, R. J., Pickering, D.J., & Pollock, J.E. (2001). Classroom instruction that works: Research-based strategies for increasing student achievement. Alexandria, VA: Association for Supervision and Curriculum Development.