Which practice best describes data-driven decision making for student outcomes?

• A. Rely solely on anecdotal reports from teachers when planning services.
• B. Use data only at the end of the year to evaluate program success.
• C. Collect and analyze data across academics, attendance, behavior, and college/career readiness; set SMART goals; implement evidence-based interventions; monitor progress with dashboards.
• D. Focus exclusively on behavior data and ignore academics and attendance.

Answer: (C)

Data-driven decision making for student outcomes means using multiple, timely data sources to guide planning, action, and follow-up, rather than relying on opinions or waiting until the end to judge success. The strongest approach collects and analyzes data across academics, attendance, behavior, and college/career readiness, then translates what the data show into concrete, measurable goals and actions.

Setting SMART goals gives clear targets that are Specific, Measurable, Achievable, Relevant, and Time-bound, so progress can be tracked and adjustments made as needed. Implementing evidence-based interventions ensures the strategies used have demonstrated effectiveness, rather than relying on intuition. Monitoring progress with dashboards provides ongoing visibility into trends and outcomes, enabling early identification of where to intensify or modify supports.

This holistic, data-informed process is preferable because it builds a complete picture of student success, supports continuous improvement, and allows for timely, data-guided decisions. Relying on anecdotes can introduce bias; waiting until year-end to evaluate misses opportunities to adjust; or focusing on one domain while ignoring others fails to address the full range of student outcomes.