Many course proposals go through repeated rounds of review, not because the idea is weak but because the design logic is unclear. Faculty often submit outlines with worthwhile content, carefully chosen readings and sensible assessments, only to receive requests for revision. Reviewers ask for clearer alignment, stronger assessment rationale, more active learning, better sequencing or clearer evidence that students will achieve the intended outcomes.
In many cases, the issue is simple: The proposal explains what will be taught, but not how learning has been designed.
This is where the work of Philippa Hardman is especially useful. Her approach to course design emphasizes evidence-informed learning architecture rather than content coverage alone. It encourages instructors to think like designers of learning experiences, not just subject-matter experts organizing material. For faculty members hoping to avoid endless cycles of review and resubmission, this shift can make all the difference.
Begin with outcomes, not weekly topics
A common mistake is to start by building a 12-week schedule. Week 1 introduces concepts, Week 2 adds theory, Week 3 moves to applications and so on. Although familiar, this approach often produces a sequence of topics rather than a coherent learning journey. A stronger starting point is to ask: What should students be able to do by the end of the course?
Use outcomes that describe capability:
- Analyze competing perspectives
- Solve authenic problems
- Interpret evidence
- Communicate recommendations
- Design solutions
- Critique AI-generated outputs
- Apply professional judgement
Once those outcomes are clear, the rest of the course becomes easier to justify. Reviewers can see purpose and direction. Without them, proposals often look like collections of interesting material.
Design backwards from performance
If the final assessment asks students to evaluate a case, build a plan, conduct analysis or defend a decision, students need repeated opportunities to practise those same moves during the course.
Too many proposals still follow an outdated model:
- Readings for several weeks
- Lectures or slide decks
- Occasional discussion posts
- Then a final project requiring sophisticated performance
This model creates a design gap. Students are assessed on capabilities they were never systematically taught to develop. Hardman’s lens suggests beginning with the end in mind. Ask:
- What evidence would convince me a student is competent?
- What smaller tasks prepare them for that moment?
- Where do they receive feedback before final grading?
This is often what reviewers mean when they ask for stronger alignment.
Build active learning intentionally
A course does not become active merely because students talk occasionally in class or complete an assignment. Active learning means students are intellectually engaged in doing the work of the discipline. Depending on the field, this could include:
- Analyzing real scenarios
- Interpreting data
- Solving client problems
- Role-playing decisions
- Conducting labs
- Designing prototypes
- Critiquing arguments
- Comparing AI and human outputs
- Making professional recommendations
Strong proposals describe these activities explicitly. They show where students practise judgement, not just absorb information.
Sequence learning carefully
Experts often forget how much novices do not yet know. Reviewers notice when a course asks beginners to complete advanced tasks too early or introduces too much complexity too fast. Good design moves students through stages:
- Understand core concepts
- Observe worked examples
- Practise with support
- Apply independently
- Integrate knowledge in realistic contexts
This sequencing matters. It reduces overload, builds confidence and improves success rates. A well-designed course does not simply become harder each week — it becomes more capable.
Use feedback as part of the design
Feedback should not appear only after grades are released. If students receive meaningful guidance only at the end, the learning opportunity has largely passed. Strong proposals build feedback loops into the course through:
- Draft submissions
- Short practice tasks
- Peer review
- Instructor checkpoints
- Annotated exemplars
- Low-stakes quizzes
- Reflective self-assessment
When reviewers ask for better student support, they are often looking for evidence of these mechanisms.
Rethink assessment in the age of AI
Today, many traditional assessments can be completed with assistance from tools students already use. That does not mean abandoning written work, but it does mean designing assessments that verify real learning. Consider adding:
- Oral defence of written work
- Live problem solving
- In-class critique tasks
- Iterative projects with drafts
- Applied case decisions
- Reflective process notes
- Comparison of AI-generated and student-generated outputs
A use question is this: Could someone completed this task successfully without truly understanding the material? If yes, redesign is needed.
A practical pre-submission test
Before submitting your course, ask yourself:
- Are the outcomes measurable and capability-focused?
- Does every assessment connect clearly to one or more outcomes?
- Do students practise the required skills before being graded on them?
- Is learning active, not mainly passive?
- Is feedback built into the journey?
- Could AI complete large parts of the assessment without understanding?
- Can a reviewer understand the design logic in one reading?
If the answer to most of these is yes, you are likly close to approval quality.
Final thoughts
Course approval should not require endless revision cycles. In many cases, proposals stall because they present content without design, activity without purpose or assessment without alignment. Hardman’s lens helps faculty avoid those traps by focusing on the architecture of learning itself.
When reviewers can see how students will build competence step by step, how outcomes connect to assessment and how the course reflects contemporary learning design, the conversation changes. Instead of asking for resubmission, they are more likely to ask when the course can begin.
