skills/mentorship-teaching/teaching-syllabus
Version Compatibility
Reference frameworks: Backward Design (Wiggins & McTighe 2005), Bloom's Taxonomy Revised (Anderson & Krathwohl 2001), UDL 3.0 (CAST 2024), NSF PAPPG 24-1.
The frameworks are stable. Adapt templates to your institution's syllabus format, accreditation requirements, and local academic policies. The Bloom's levels and UDL guidelines are durable; institutional templates change.
Teaching Syllabus Construction
A syllabus is more than a course calendar—it is a learning contract, a navigation tool, and a public statement of your teaching philosophy. This skill provides a comprehensive syllabus construction framework that translates backward design course plans into a complete, accessible, and inclusive syllabus that aligns with Universal Design for Learning (UDL) principles.
For course design principles and module planning, see mentorship-teaching/ors-teaching-course-design. For individual mentee development, see mentorship-teaching/ors-mentorship-goal-setting.
When to Use This Skill
| Scenario | Application |
|---|---|
| New course preparation | Full syllabus construction |
| Revising existing course | Update outcomes, schedule, policies |
| Updating accessibility language | UDL-aligned accommodation statements |
| Aligning with accreditation | Outcomes mapping and assessment alignment |
| Standardizing multi-section courses | Common syllabus template |
| Converting F2F to hybrid/online | Schedule and assessment revision |
Syllabus as a Learning Contract
A syllabus performs three functions simultaneously:
- Contractual: Defines expectations, policies, and grade calculations
- Navigational: Provides schedule, resources, and pathways through content
- Pedagogical: Communicates teaching philosophy and approach
Principle: A syllabus that students actually read (not just file) treats them as partners in learning.
Required Syllabus Components
| Component | Purpose | UDL alignment |
|---|---|---|
| Course information | Logistics, meeting times | Multiple means of representation |
| Instructor information | Contact, office hours, response time | Multiple means of engagement |
| Course description | What is this course about? | Multiple means of representation |
| Learning outcomes | What students will be able to do | Backward design link |
| Materials | Texts, software, supplies | Multiple means of representation |
| Schedule | Weekly topics, readings, assignments | Multiple means of representation |
| Assessment | What is graded, how, when | Performance-based evidence |
| Grading policy | Calculation, late work, academic integrity | Clarity and predictability |
| Inclusion statement | Welcome, respect, accessibility | Multiple means of engagement |
| Accommodations statement | UDL, disability services | Action/expression options |
| Course policies | Attendance, communication, AI use | Engagement support |
Writing Learning Outcomes
Learning outcomes must be specific, measurable, and aligned with assessments. Use Bloom's verbs to anchor the cognitive level.
Bloom-Verb Selection by Level
| Level | Strong verbs to use | Weak verbs to avoid |
|---|---|---|
| Remember | define, list, recall, identify | know, learn |
| Understand | explain, summarize, interpret, describe | understand (alone) |
| Apply | implement, execute, use, perform, solve | apply (alone) |
| Analyze | compare, contrast, diagnose, differentiate, attribute | analyze (alone) |
| Evaluate | critique, justify, assess, defend, prioritize | evaluate (alone) |
| Create | design, synthesize, develop, construct, formulate | create (alone) |
Outcome Templates
Apply-level outcome:" "By the end of this course, students will be able to implement [technique] in [software] to [purpose]."
Analyze-level outcome: "By the end of this course, students will be able to compare and contrast [method 1] and [method 2] for [problem] and diagnose when each is appropriate."
Create-level outcome: "By the end of this course, students will be able to design a [artifact type] that [addresses need] and justify design choices with [evidence type]."
Example outcomes for a research methods course:
- Apply: "Implement appropriate statistical tests for common experimental designs using R or Python"
- Analyze: "Diagnose sources of bias and confounding in published research"
- Evaluate: "Critique the methodological rigor of peer-reviewed papers"
- Create: "Design a complete replication study, including preregistration, analysis plan, and data management"
Outcomes-Assessment Matrix
Document alignment between outcomes and assessments:
| Outcome | Bloom level | Where assessed | % of grade |
|---|---|---|---|
| Outcome 1 | Apply | Weekly problem sets, midterm | 30% |
| Outcome 2 | Analyze | Paper critiques | 20% |
| Outcome 3 | Evaluate | Peer review exercises | 20% |
| Outcome 4 | Create | Final project | 30% |
Principle: Every outcome should be assessed. If an outcome is not assessed, it is decorative.
Weekly Schedule Construction
The schedule should clearly indicate:
- Topic
- Pre-class preparation (readings, videos)
- In-class activities
- Post-class deliverables
- Bloom level progression
Template:
Week [N]: [Topic]
Bloom focus: [Apply/Analyze/Evaluate/Create]
Pre-class:
- [Read chapter X, watch video Y]
In-class:
- [Activity 1, Activity 2]
Due by [date]:
- [Assignment name]
Read ahead for next week:
- [Reading]
Sample progression for a 15-week research methods course:
| Week | Topic | Bloom level | Major deliverable |
|---|---|---|---|
| 1 | Course intro, reproducibility foundations | Understand | Reading response |
| 2-3 | Literature search and synthesis | Apply | Annotated bibliography |
| 4-5 | Study design fundamentals | Analyze | Design critique |
| 6-7 | Statistical reasoning | Apply | Problem set |
| 8 | Midterm exam | Apply/Analyze | Take-home exam |
| 9-10 | Analysis workflow | Apply | Code review |
| 11-12 | Scientific writing | Create | Draft section |
| 13-14 | Peer review process | Evaluate | Peer review report |
| 15 | Final presentations | Create | Capstone presentation |
Assessment Rubrics
Rubrics make grading transparent and consistent. They also support student learning by clarifying expectations.
Single-point rubric (recommended for clear, fast feedback):
| Criterion | Areas of strength | Areas for growth |
|---|---|---|
| Analysis rigor | [Specific strengths] | [Specific growth areas] |
| Communication | [...] | [...] |
| Reproducibility | [...] | [...] |
Multi-level rubric (use when level differentiation matters):
| Criterion | Excellent (4) | Proficient (3) | Developing (2) | Beginning (1) |
|---|---|---|---|---|
| Analysis | Sophisticated; unexpected insights | Correct; appropriate depth | Correct but shallow | Errors or missing |
| Communication | Engaging, clear, appropriate | Clear and appropriate | Some unclear sections | Often unclear |
| Reproducibility | Fully reproducible, documented | Mostly reproducible | Partially reproducible | Not reproducible |
Inclusive Teaching and UDL
Syllabus language shapes the climate of a course. Inclusive language signals that all students belong.
Welcome and Inclusion Statement Template
This course is designed to be accessible to all students, regardless of
background, identity, or prior experience. I am committed to creating
an environment where every student can learn.
If there is anything I can do to support your learning, please contact
me. I welcome feedback on how to improve the course for all students.
Accommodations Statement
Universal Design for Learning
This course follows UDL principles: multiple means of engagement,
representation, and action/expression. Course materials are designed
to be accessible through varied formats and flexible assessments.
Disability Accommodations
If you require accommodations, please contact [Disability Services]
to establish an accommodation plan. Once you have your plan, please
share it with me early in the semester (or as soon as it changes) so
I can support your learning. I will keep your plan confidential.
If you encounter barriers that are not addressed by existing
accommodations, please let me know so we can find solutions.
AI Use Policy
Be explicit about AI tool use. Ambiguity leads to integrity concerns.
Sample policy (tiered by assignment type):
| Assignment type | AI use permitted? | What must be disclosed |
|---|---|---|
| Reading responses | Brainstorming only | Any AI suggestions used |
| Code assignments | Debugging assistance | Specific functions/blocks |
| Draft writing | Editing suggestions | Detailed prompt used |
| Final projects | Limited (with approval) | Pre-approval required |
| Exams | None | n/a |
Course Policies
Common policies to address explicitly:
| Policy | Topics to cover |
|---|---|
| Late work | Acceptable lateness, penalty, exceptions |
| Communication | Email response time, when to use email vs. office hours |
| Attendance | Required vs. optional, recording availability |
| Academic integrity | Collaboration norms, citation, AI |
| Grading disputes | Timeline, process, evidence required |
| Technology | Laptop use, recording, generative AI |
Universal Design for Learning Implementation
Map UDL considerations to syllabus elements:
| UDL network | Syllabus element | Concrete choice |
|---|---|---|
| Engagement | Welcome statement | "I am committed to your success" |
| Engagement | Choice in assessments | "Choose 2 of 3 paper critiques" |
| Engagement | Connection to careers | "Real-world data applications weekly" |
| Representation | Multiple materials | "Textbook, videos, code examples" |
| Representation | Vocabulary support | "Glossary of key terms provided" |
| Representation | Cognitive load | "Weekly modules chunked by concept" |
| Action/Expression | Flexible submission | "Written, oral, or video options" |
| Action/Expression | Variable pacing | "Sliding deadline with notice" |
| Action/Expression | Executive function | "Project planning template" |
Syllabus Self-Audit Checklist
Before finalizing the syllabus, check:
- Outcomes are written with Bloom verbs at appropriate levels
- Each outcome is mapped to at least one assessment
- Schedule includes Bloom progression across the term
- Materials and resources are accessible (formats, costs)
- Assessment policy is fully specified
- Late work policy is clear
- AI use policy is explicit
- Welcome and inclusion statements are present
- Accommodations statement references UDL and disability services
- Communication norms (response time, channels) are stated
- Grade calculation is transparent
- Office hours and contact info are clear
- Course policies do not contain hidden expectations
Common Syllabus Pitfalls
| Pitfall | Why it fails | Prevention |
|---|---|---|
| Outcomes are vague | Cannot be measured or assessed | Use Bloom verbs and specific tasks |
| No outcome-assessment link | Assessment drift | Build alignment matrix |
| Schedule is topic-only | No cognitive progression | Tag each week with Bloom level |
| Accessibility as afterthought | Students with needs left out | UDL from the start |
| Policies are punitive | Adversarial climate | Frame policies as supporting learning |
| AI policy is unclear | Integrity issues rise | Explicit tiered policy |
| Hidden expectations | Disputes and resentment | Self-audit checklist |
References
- Wiggins & McTighe, Understanding by Design (2nd ed.)
- Anderson & Krathwohl, A Taxonomy for Learning, Teaching, and Assessing
- CAST UDL Guidelines 3.0: https://udlguidelines.cast.org/
- NSF PAPPG 24-1: https://www.nsf.gov/bfa/dias/policy/pappg/
- NIH BEST: https://www.nih.gov/best-programs
- CIMER Entering Mentoring: https://cimer.wisc.edu/
Related Skills
- mentorship-teaching/ors-teaching-course-design - Backward design principles
- mentorship-teaching/ors-mentorship-goal-setting - Individual mentee IDPs
- mentorship-teaching/ors-mentorship-onboarding - Mentor-mentee relationship setup
