Computer Science Instruction and Assessment
Domain 6 tests pedagogical content knowledge: planning CS instruction, eliciting misconceptions, designing assessments, and using results to adapt teaching. It is not a general classroom-management domain; answers should connect to how computing is learned.
Core rules
- Begin with measurable objectives and align activities and assessments to them. A valid assessment measures the stated objective; a reliable one produces consistent results.
- Formative assessment is low-stakes evidence used during learning; summative assessment judges achievement at the end. Feedback should be specific and actionable.
- Misconceptions are predictable: students may think a
whileloop always runs once, that variables are algebraically fixed, or that binary search works on unsorted data. Diagnose before reteaching. - Scaffolds such as worked examples, Parsons problems, pair programming, and gradual release support novices without removing the core thinking.
- Rubrics should describe observable criteria. Accessibility and culturally responsive examples broaden participation; group work needs individual accountability.
Worked example
Objective: students trace a loop with an accumulator. A multiple-choice item asks for the output of total=0; for i in 1..3: total+=i. Distractor 3 comes from stopping at 2; distractor 9 from multiplying. If many choose 3, the pattern suggests an off-by-one misconception, so reteach with a trace table showing i, total, and iteration count. A writing-from-scratch task would not isolate the same objective.
Traps
Calling every quiz formative; using a rubric that rewards neatness over correctness; assessing syntax when the objective is debugging; and treating group success as individual mastery. Also avoid assuming access to devices or prior coding experience.