Evaluating DataDriven Decision Making................................................

Evaluating DataDriven Decision Making (DDM) requires careful investigations into both the longitudinal data system’s design and efforts to build decision makers’ capacities to use the data system.  Because so many states, districts and schools are just beginning to design and implement DDM initiatives, both formative and summative evaluations are essential for optimizing widespread evidence-based practice.

Considerations for Evaluating DDM

Every evaluation requires a design—a well-articulated conceptual plan for determining when and from whom information will be gathered for a particular purpose.  The best evaluation designs actively engage all relevant stakeholders - including clients, educators, administrators, political leaders and state and federal agencies - from beginning to end.

As formative evaluators, we gather feedback from data-system users and professional development participants, which informs subsequent iterations of both the longitudinal data system and associated professional development offerings. 

As summative evaluators, we examine the nature of data use over time and associated impact on classroom instruction and student achievement that can result from providing decision-makers with seamless, technology-based access to (a) coherent educational data, (b) enriching opportunities to better understand and utilize these data for targeting particular needs, and (c) instructional materials that align with state standards.

Hezel Associates’ evaluation approach (link to hezel.com/services2) combines good science with each client’s unique stakeholder-centered needs.  We understand that evaluating educational initiatives requires careful attention to real world challenges, which often command customized solutions that maintain flexibility during both the planning and implementation stages.  In this way, we make the most strategic use of evaluation resources to ensure that each client receives value-added outcomes.

Characteristics of Effective DDM Evaluation Design