The 4Ds through an educator's eyes
This course assumes the 4D framework (Chapter 3) and turns it toward your own practice: designing courses, writing materials, and building assessments in a world where students have AI too. It empowers faculty, instructional designers, and educational leaders to apply AI Fluency to both teaching and institutional strategy.
Key concept · Two questions AI forces on every course
AI pushes two design questions to the front. Delegation: which parts of your course workload can AI genuinely help with (drafting materials, generating variants, differentiating for levels) versus which must stay human (judgment, mentorship, grading that shapes a learner)? And outcomes: if AI can do a task the assignment used to measure, is the assignment still measuring learning — or measuring the tool? The rest of the course works through both.
Applying AI Fluency to course design and learning outcomes
AI is a fast collaborator for the design work around a course, used with Description and Discernment.
Key concept · Design with AI, verify like an expert
Use AI to draft and refine outcomes, map them to activities, propose lesson structures, generate examples and analogies at different levels, and differentiate for varied learners — then bring your disciplinary Discernment to check accuracy, rigor, and fit. The strategic layer is revisiting learning outcomes themselves: emphasize the higher-order skills AI doesn't replace (framing problems, evaluating evidence, judgment) and make "using AI well" an explicit, teachable outcome rather than a loophole.
Applying AI Fluency to learning materials and assignments
The same collaboration produces day-to-day teaching materials — readings, worked examples, rubrics, question banks, feedback scaffolds — and, most importantly, assignments designed for an AI world.
Key concept · Assignments that assume AI exists
Rather than police AI out of existence, design assessments that stay meaningful with it: ask for process and reasoning (drafts, decision logs, reflections), require personal or local context AI can't supply, build in oral or in-class components, and assess the Discernment of AI output itself (have students critique a generated answer). Diligence runs throughout — model transparent AI use, set clear expectations, and protect equity so every student can meet them.
Chapter 6 quiz
Twelve questions on course design, outcomes, and assignments. Answer first, then expand Show answer.
Part A · Multiple choice
Who is this course primarily for?
- A Faculty, instructional designers, and educational leaders
- B Backend developers
- C Students only
- D Nonprofit fundraisers
Show answer
A. Applying AI Fluency to teaching practice and institutional strategy.
Which is a sound Delegation split for an educator?
- A AI drafts material variants; the human keeps mentorship and formative judgment
- B AI grades everything unreviewed
- C AI replaces the instructor
- D Never use AI for anything
Show answer
A.
If AI can complete the task an assignment measured, the course recommends:
- A Reconsidering what the assignment measures and redesigning it
- B Ignoring the change
- C Banning all technology
- D Lowering standards
Show answer
A. Measure learning, not the tool.
Which is an assignment design that stays meaningful with AI available?
- A Require process artifacts (drafts, decision logs) and personal/local context
- B A generic take-home essay on a common topic
- C A fact-recall quiz that's one search away
- D Nothing changes
Show answer
A. Also oral components and assessing discernment of AI output.
What should learning outcomes emphasize in an AI world?
- A Higher-order skills AI doesn't replace, plus "using AI well" as an outcome
- B Only memorization
- C Speed of typing
- D Avoiding all judgment tasks
Show answer
A.
Part B · True or false
Educators should apply disciplinary Discernment to AI-drafted materials before use.
Show answer
True. Check accuracy, rigor, and fit.
Making "using AI well" an explicit outcome turns a loophole into a teachable skill.
Show answer
True.
Modeling transparent AI use is irrelevant for instructors.
Show answer
False. Diligence — educators set the example and expectations.
Equity is a concern when redesigning assignments around AI.
Show answer
True. Ensure every student can meet the expectations.
Part C · Short answer
Name the two application areas this course covers.
Show answer
Course design & learning outcomes, and learning materials & assignments.
Give two features of an assignment designed for an AI world.
Show answer
Any two: requires process/reasoning artifacts, personal/local context, oral/in-class components, assesses discernment of AI output.
Which two 4D competencies dominate designing with AI?
Show answer
Description (drafting/guiding) and Discernment (expert evaluation) — with Delegation and Diligence framing the choices.