Assessment, Data, and Evaluation
Domain 4 - Assessment, Data, and Evaluation focuses on using technology to gather, analyze, and act on evidence of learning. Expect items on assessment types, data interpretation, and the limits of digital tools.
Assessment fundamentals
- Formative assessment informs instruction during learning; summative assessment certifies learning at the end; diagnostic assessment identifies starting points.
- Validity: the assessment measures what it claims; reliability: consistency across occasions or raters.
- Rubrics make performance tasks transparent; analytic rubrics score criteria separately, holistic rubrics give one overall judgment.
- Technology-enhanced items such as drag-and-drop and simulations expand what can be assessed but may introduce construct-irrelevant barriers.
- Data privacy applies to assessment platforms: know what student data is collected and whether it is approved.
Worked example
A class takes a 10-item exit ticket on equivalent fractions. Six students miss items 3 and 7, both requiring simplifying before comparing. The specialist should not reteach the whole unit; the pattern suggests a targeted mini-lesson on simplifying, followed by a new check with parallel items. The score is a starting point, not a diagnosis by itself.
Traps
- Treating a single quiz average as valid evidence of mastery.
- Using an app that collects names and emails without district approval.
- Confusing reliability with validity.
- Ignoring accessibility features during digital assessment.