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Week of March 9th, 2026
A Quick Primer on Learning Design
A Quick Primer on Learning Design
New to the terminology? This guide unpacks the key concepts before you dive in — outcomes, taxonomies, and what AI really means for assessment.
Weak vs. Strong Outcomes
Weak vs. Strong Outcomes
The verb carries the weight. Compare these two versions of the same outcome:
❌ Weak Outcome
❌ Weak Outcome
"Students will understand recursion and how it works in programming."
Vague. No clear evidence. Open to interpretation by both student and instructor.
✅ Strong Outcome
✅ Strong Outcome
"Students will trace the execution of a recursive function by hand, identifying the base case, recursive call, and return values at each stack frame."
Specific. Measurable. Points to an exact cognitive level.
Why Verbs Matter So Much
Why Verbs Matter So Much
Choosing a verb with intention — not habit — is one of the most powerful design decisions you make. Taxonomies like Bloom's give you a shared vocabulary for doing exactly that.
Verbal Signal Cognitive Level - Each verb maps to a level of thinking. The right verb tells students exactly what depth is expected.
Verbs Shape Assessment Design - Once you pick a verb, the form of your assessment almost writes itself. Vague verbs leave too much open.
Verbs Create Shared Expectations - Clear verbs communicate the same expectation to every student; no guessing, no ambiguity.
Bloom's Revised Taxonomy: A Visual Overview
Bloom's Revised Taxonomy: A Visual Overview
Bloom's classifies cognitive tasks into six levels; from basic recall to complex creation. Levels build on each other, but a well-designed course moves students up and down with purpose.
Bloom's Taxonomy with Computer verbiage
Bloom's Taxonomy with Computer verbiage
Most traditional computing assessments cluster around levels one through three — leaving critical dimensions of student development underdeveloped.
Bloom's in Computing: Verb Reference
Bloom's in Computing: Verb Reference
Use this table to quickly match your desired cognitive level to the right action verbs for computing courses.
AI and Assessment Integrity: What's Actually at Stake
AI and Assessment Integrity: What's Actually at Stake
Generative AI can produce code, written explanations, and analytical responses good enough to substitute for many traditional assignments. Most computing faculty are already navigating this in real time.
The Deeper Question Isn't About Cheating
The Deeper Question Isn't About Cheating
| If a student can delegate a task entirely to AI and submit the result — did any learning actually happen?
If the answer is no, the assignment may not be measuring what you think it is measuring. That's the real design problem.
Think of AI as a capable assistant who never sleeps. Any task you can describe clearly in a prompt — and verify by reading the output — is essentially delegatable.
The Real Design Question for Your Course
The Real Design Question for Your Course
Which tasks genuinely require the student to have done the thinking, had the experience, or developed the judgment themselves?
Thinking: Tasks that require students to reason through a problem; not just produce an answer.
Experience: Assignments built around doing: debugging, iterating, and making decisions under constraints.
Judgement: Higher-order tasks where students must evaluate, defend, or critique; not just execute.
Fink's Taxonomy helps you see exactly where these tasks live... and how to design for them intentionally.
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