Instructional Design and Assessment in Science
Instructional Design and Assessment tests coherent planning: selecting standards, anchoring instruction in phenomena, building three-dimensional learning, and gathering valid evidence of student understanding. Assessment questions often ask you to critique alignment or revise a task and rubric.
Core rules and concepts
- Use backward design: performance expectation to evidence statements to learning experiences to assessment.
- Anchor units in phenomena and driving questions; develop science and engineering practices, crosscutting concepts, and disciplinary core ideas together.
- Formative assessment is ongoing evidence used for feedback and adjustment; summative assessment evaluates achievement after learning.
- Rubrics need observable criteria and performance levels; avoid construct-irrelevant reading or mathematics load.
- Plan accessibility and a feedback loop before teaching.
Worked example
An ecosystem unit targets carrying capacity. The phenomenon is an algal bloom. Evidence includes a model, data interpretation, and argumentation. The summative task gives a new lake dataset and asks students to predict and justify; the rubric scores mechanism, use of evidence, and uncertainty. Formative tasks include model revisions and exit tickets. If the rubric rewards 'neat poster,' it misaligns with the standard.
Traps that cost marks
- Designing activities first and attaching standards afterward.
- Assessing only vocabulary recall when the standard requires explanation or modeling.
- Vague rubric language such as 'good understanding.'
- One task measuring several objectives without separable criteria.
Key points
- Begin with the standard and the evidence students must produce.
- Use phenomena to motivate and integrate practices, concepts, and core ideas.
- Formative evidence must change instruction; summative evidence must match the objective.
- Rubrics should name observable features and levels.
- Remove construct-irrelevant barriers without lowering rigor.