Data-Based Decision Making
Course Description: Data-based decision-making involves small teams meeting regularly and using an explicit, data-driven structure to disaggregated data, analyze student performance, set incremental student learning goals, engage in dialogue around explicit and deliberate classroom instruction, and create a plan to monitor instruction and student learning.
Learner Objectives:
By the end of this course, learners will….
- know the purpose of data-based decision making;
- review and analyze schoolwide office discipline referral data to improve student outcomes schoolwide
- review and analyze common formative assessment data in tandem with Classroom Managed/Minor behavior data to improve academic and behavioral outcomes for student at within grade level or content area collaborative teams.
- monitor, review, analyze and problem solve around equity data
Lesson Modules
| Lessons | Description |
|---|---|
| Overview Data-Based Decision Making | This session provides an overview of DBDM process, prerequisites that must be in place for a team to conduct DBDM, and the essential functions and purpose of each step of the DBDM. While this overview is presented through the lens of behavior, the concepts discussed can be applied to academic improvement, as well. |
| Schoolwide Data-Based Decision Making | In this session, Building Leadership Teams will apply the DBDM process described in the overview to review and analyze patterns of schoolwide Office Discipline Referral Data and associated contextual information in order to solve schoolwide behavior challenges. |
| DBDM for Collaborative Teams | In this session, grade level or content alike Collaborative Teams review and analyze common formative assessment data in tandem with classroom managed/minor behaviors in order to improve academic and behavioral outcomes for students. |
| Monitoring Equity | In this session, Building Leadership Teams learn to monitor equity data to ensure that all students have similar, positive experiences and outcomes from school |
| Implementation Supports | Description |
|---|---|
| DBDM Practice Profile | The DBDM Practice Profile describes essential functions that teams perform while conducting data-based decision making. The practice Profile can be used to implement DBDM, and to evaluate this implementation. |
References
Gilbert, T.F. (1978). Human competence: Engineering worthy performance. New York : McGraw-Hill.
Gresham, F. M., Sugai, G., & Horner, R. H. (2001). Interpreting outcomes of social skills training for students with high-incidence disabilities. Exceptional Children, 67(3), 331-344.
Horner, R. (March 8, 2016). Personal Communication.
Horner, R.H. (2011). Moving PBS forward with quality, equity and efficiency. Keynote: Eighth International Conference of the Association for Positive Behavior Support. Denver: CO.
PBIS Apps (2016). Swift at SWIS. University of Oregon
Reaves, D.A. (2006). The learning leader: How to focus school improvement for better results. Association for Supervision and Curriculum Development:Alexandria, Virginia.
Sugai, G., Sprague, J.R., Horner, R.H., & Walker, H.M. (2000). Preventing school violence. The use of office discipline referrals to assess and monitor schoolwide discipline interventions. Journal of Emotional and Behavioral Disorders, 9(2), 94–101.
Tilly, W. D. (2008). The evolution of school psychology to science-based practice: Problem-solving and the three-tiered model. In A. Thomas & J. P. Grimes (Eds.), Best practices in school psychology V (pp.