Faculty Resources

Center for Teaching & Learning

Supporting pedagogical excellence, inclusive teaching, course design, and thoughtful technology integration across all academic disciplines.

Syllabus checklist AI levels guidance Accessible design Course assistant pilot

Pedagogical Excellence

Teaching Support & Consultation

The Center for Teaching & Learning (CTL), located on the 3rd floor of Whitcombe Library, is the university hub for instructional innovation and faculty professional development.

CTL consultants partner with full-time and adjunct faculty across all five schools to design engaging syllabi, refine student learning outcomes, integrate evidence-based active learning strategies, and leverage modern digital tools without sacrificing academic rigor.

Confidential Consultations

One-on-one sessions on syllabus structure, assignment scaffolding, grading rubrics, and mid-semester feedback.

Workshops & Learning Communities

Faculty working groups on AI pedagogy, inclusive course design, classroom assessment techniques, and Socratic questioning.

Dr. Marcus Lee

Director of the Center for Teaching & Learning

Leading instructional innovation, course design consultations, and faculty development across campus.

Office: Whitcombe Library 3rd Floor
Phone: (555) 555-0172
Email: mlee@university.alkimi.ai

Center for Teaching & Learning

Where: Whitcombe Library 3rd Floor
Phone: (555) 555-0172
Email: ctl@university.alkimi.ai
Hours: Monday–Friday 8:30 a.m.–5:00 p.m.
Lead: Dr. Marcus Lee, Director of the Center for Teaching & Learning

Mandatory Course Documentation

The 12 Required Syllabus Elements

Every course syllabus posted in Canvas must include the twelve elements codified in Faculty Handbook §5.2. Syllabi must be accessible to enrolled students by the first day of classes.

Canvas Syllabus Compliance Checklist

Required for all undergraduate and graduate course sections.

Faculty Handbook §5.2: Syllabus Requirements and Mandatory Statements

1 Course code, title, credits, term, meeting times, and location or modality
2 Instructor name, contact information, and office hours (including the virtual hour)
3 Course description matching the catalog, and any prerequisites
4 Measurable student learning outcomes
5 Required materials and their approximate cost
6 Grading components, weights, and the grading scale
7 Schedule of topics, major assignments, and exam dates, including the final exam slot
8 Attendance and late-work policies
9 The course's generative AI level (1, 2, or 3) and what it allows
10 The standard Academic Integrity statement
11 The standard Accessibility Services statement
12 Links to student support services (Advising, Writing Center, Hollis Health & Counseling Center)

Posting Deadline: Syllabi must be posted in Canvas by the first day of classes and include the required elements in Faculty Handbook §5.2. The CTL provides downloadable Canvas syllabus templates with pre-formatted statements for accessibility, academic integrity, and support services.

Generative AI in the Classroom

AI Syllabus Policy Guidance

Under Faculty Senate Resolution FS-2526-14, every instructor must designate one of three generative AI course levels on their syllabus.

Level 1

AI Prohibited for Graded Work

Generative AI tools may not be used on any graded coursework, problem sets, essays, or examinations. The focus is on unassisted individual student mastery.

Typical courses: Introductory composition, introductory language courses, early STEM fundamentals, closed-book problem solving.

Governed by Faculty Handbook §7.1

Level 2

Specified Tasks with Disclosure

Generative AI tools may be used only for instructor-specified assignments or tasks (such as brainstorming, literature search, or code debugging).

Disclosure required: Students must submit a written statement describing the tool used and the nature of its contribution.

Governed by Faculty Handbook §7.1 & Faculty Handbook §7.2

Level 3

Broad Permissibility with Disclosure

Generative AI tools may be integrated broadly throughout coursework as collaborative or analytical partners, accompanied by transparent disclosure.

Ethical practice: Students remain wholly responsible for all factual claims, logic, and code accuracy submitted for credit.

Governed by Faculty Handbook §7.1 & AI Guidelines §3.1

The University Default Rule

Unless the syllabus says otherwise, generative AI tools may be used for brainstorming, studying, and feedback on your own drafts, but not to produce work you submit for a grade.

If a syllabus does not explicitly state a level, students are permitted to use approved AI tools for studying, conceptual explanations, and draft critiques, but may not submit AI-generated text or code as graded work.

AI Guidelines §3.2: University Default Rule When a Syllabus Is Silent

AI Detection Tool Evidentiary Limits

AI detection scores may not be the sole basis for an academic integrity report.

Due to established rates of false positives and algorithmic bias, detection software outputs cannot substantiate an academic integrity violation without corroborating evidence (e.g., fabricated citations or revision histories).

Faculty Handbook §7.3: AI Detection Tools: Capabilities and Legal Limits

Universal Design for Learning

Accessible Course Design

Ensuring instructional materials, learning platforms, and assessments provide equitable access to all learners.

In partnership with the Office of Accessibility Services (OAS), the CTL helps faculty implement Universal Design for Learning (UDL) frameworks that reduce barriers before accommodations are requested.

Accommodation Letters

Students provide verified accommodation letters via the faculty portal. Instructors must implement stated accommodations promptly per Faculty Handbook §8.1.

Accessible Digital Materials

All PDFs, Canvas pages, and presentation slides must adhere to WCAG 2.1 AA standards, featuring semantic headings and alt text per Faculty Handbook §8.3.

Testing Accommodations

Extra time and reduced-distraction environments are coordinated with the OAS Testing Center in Harlan Hall 204.

Video & Audio Media

Pre-recorded lectures and video course materials must include synchronized accurate closed captions.

A calculus lecture in Ashby Hall — Faculty member facilitating an active seminar discussion.

Instructional Assessment

Grading Timelines & Course Feedback

Grade Submission Rules

Midterm Grades (100- & 200-Level Courses):: Required for 100- and 200-level courses, due at the end of week 8. Required in Fall (Oct 16, 2026) and Spring (Mar 12, 2027) to identify students needing advising interventions.
Final Course Grades:: Due 72 hours after the final exam, and no later than the published grade deadline (noon). Deadlines are strictly enforced to permit degree certification and graduation verification.
Incomplete (I) Grades:: Incomplete (I) grades must be resolved by the end of the following regular semester or they convert to F.
Grade Change Authorization:: A grade change after submission requires the chair's approval and must be filed within one regular semester.

Faculty Handbook §5.6: Grading Policies, Scale, and Submission Deadlines

Student Course Evaluations

Student Course Feedback surveys are administered online during the final two weeks of instruction each semester, closing prior to final examinations.

• Formative & Summative: Results inform course adjustments and are included in Annual Faculty Activity Reports (FAR) and promotion dossiers.
• Grade Anonymity: Numerical ratings and written comments are released to instructors only after all final grades are certified.
• Mid-Semester Feedback: The CTL provides early pulse survey tools to assess course climate during weeks 5–6.

Faculty Handbook §5.9: Student Course Evaluations (Course Feedback)

Pedagogical Innovation

Fall 2026 Course Assistant Pilot

Eight undergraduate courses are pioneering custom, instructor-curated Alkimi Course Assistants embedded inside Canvas.

Developed in close collaboration with the AI Advisory Council and the Center for Teaching & Learning, the Fall 2026 Course Assistant Pilot equips students with 24/7 Socratic learning partners grounded strictly on verified course materials.

HIST 204