Prompting for teaching is not about clever wording. It is about making purpose, audience, constraints, examples, and quality criteria visible to the AI tool.
A useful faculty prompt should improve preparation while keeping pedagogical decisions with the teacher.
Who can use this material
- Faculty preparing classes.
- FDP participants practicing AI workflows.
- Teaching-learning centers creating shared resources.
Teaching problem it addresses
Many faculty prompts are too broad, which leads to generic lecture notes, weak examples, and superficial assessment items.
Teaching prompt structure
Effective prompts include role, topic, learner level, constraints, output format, and quality check.
- Role: specify the teaching task.
- Context: course, level, topic, and learner profile.
- Constraint: time, syllabus, difficulty, and format.
- Output: table, rubric, examples, questions, or activity.
- Review: ask for limitations and possible misconceptions.
How to adapt it
- Start from a learning outcome.
- Ask for multiple teaching approaches, not a final answer only.
- Request examples from familiar contexts.
- Review output for accuracy and bias.
- Adapt into your own teaching material.
Classroom and department examples
- Generate three examples to explain opportunity cost to MBA students using Indian business contexts.
- Draft a rubric for a literature review assignment with criteria for synthesis and citation quality.
- Create five misconception checks for a session on AI hallucination.
Prompt patterns included
- Lesson planning prompt.
- Rubric prompt.
- Feedback prompt.
- Caselet prompt.
- Discussion question prompt.
- Assessment redesign prompt.
Before using it with students
- Do not treat AI output as evidence unless the underlying source has been checked.
- Do not upload confidential student, institutional, or unpublished research data into unapproved tools.
- Keep human judgment visible in reading, teaching, assessment, publication, and policy decisions.
- Disclose meaningful AI assistance when the work, course, journal, or institution requires it.
Adaptation questions
How should faculty adapt Faculty Prompt Bank for Teaching and Assessment?
Use it as a working academic document, then align it with the course level, assessment type, student background, and institutional rules. The first adaptation step is: Start from a learning outcome.
What should be documented when this material is used?
Keep enough evidence for review and improvement. The most useful fields to preserve are: Lesson planning prompt, Rubric prompt, Feedback prompt, and Caselet prompt.
Where must human academic judgment remain visible?
The tool or template should support judgment, not replace it. A useful boundary is: Role: specify the teaching task.
Guides to use with this material
- Generative AI in Education Hub
- Agentic AI Hub
- AI for Research Hub
- Downloads and Templates
- Session Inquiry
Use in FDPs and classroom workshops
For a faculty session, research training activity, institutional workshop, or downloadable handout, share the audience profile, intended use, and the level of detail required.
How to adapt this material
- Use the material as a lecture note, pre-reading, workshop handout, classroom discussion prompt, or FDP activity.
- Adjust examples for the audience: students need clarity and boundaries, faculty need teaching applications, and researchers need verification and citation discipline.
- Pair the material with a short reflection task so learners explain where AI helped, what they verified, and what remained their own academic judgment.
Quality check
Before using the material in class or training, review examples for accuracy, privacy, academic integrity, disclosure expectations, and fit with institutional policy.