Assessment and Data-Based Decision Making
What to know
Assessment questions test technical concepts and data use. Know reliability (consistency) and validity (accuracy for the intended interpretation), norm-referenced versus criterion-referenced, standard scores and percentile ranks, standard error of measurement, formative versus summative assessment, universal screening, progress monitoring, and diagnostic assessment. Know MTSS/RTI logic: screen, intervene, monitor, adjust. Know data-based decision rules: use multiple data points, compare to baseline and goal, consider trend and variability, and avoid decisions from a single score.
Traps
- Saying a test is valid because it is reliable. Reliability is necessary but not sufficient.
- Confusing percentile rank with percent correct. A 25th percentile score does not mean 25% correct.
- Using one probe to change an intervention.
- Ignoring base rates or referral bias.
- Assuming a standard score difference alone proves a disability.
Worked example / rule of thumb
A student earns a standard score of 85 (16th percentile) on a reading test. Say: the student scored at or below 16% of the norm group. Do not say the student got 16% right. If progress monitoring shows a flat trend across six weeks while the goal line rises, the team should intensify or change the intervention. Rule: reliability first, validity second, and never decide from one data point.