Getting Started: Practical Ways to Use AI in Your Teaching

AI can be a powerful teaching assistant when used thoughtfully. This toolkit offers starting points for exploring how AI might enrich your teaching - adapt these ideas to fit your course, your students, and your context.

AI can help you redesign assignments so students must think critically, synthesize ideas, and apply knowledge - not just copy answers from AI. Use this space to experiment with your own assignments and see how they could be reframed.
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Examples (Mathematics)
Prompt Tip: Ask AI to “rewrite this assignment so it requires higher-order thinking skills” and include specific learning outcomes. Focus on evaluation, synthesis, or comparison - not simple recall.
AI can help you generate lecture notes that highlight common student misconceptions, simplify complex ideas, and create richer discussion prompts. Use this space to explore how AI might assist in clarifying tough concepts, while keeping your own expertise and voice at the center.
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Examples (Mathematics)
Prompt Tip: Ask AI to “generate lecture notes that include at least one common misconception and a conceptual question to challenge it.” Encourage AI to provide examples, analogies, or prompts that promote discussion - not memorization.
AI can help you design realistic, discipline-aligned case studies that encourage students to apply theory to practice. Use this space to explore how AI might help generate prompts, role-play situations, or ethical dilemmas that deepen analysis and reflection - not just provide “right” answers.
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Examples (Mathematics)
Prompt Tip: Ask AI to “generate a short case scenario with realistic context, competing perspectives, and an ethical or analytical twist.” Encourage outputs that require students to explain reasoning, evaluate assumptions, or connect theory to practice.
Scaffolding helps students learn by guiding them step-by-step through complex reasoning, rather than giving answers directly. AI can help instructors design structured prompts, hints, or reflection steps that build understanding gradually - supporting diverse learners at their own pace.
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Examples (Mathematics)
Prompt Tip: Scaffolding with AI helps students reason through complexity rather than skip to an answer. The goal isn’t to simplify the task - it’s to make thinking visible and structured.
In-class activities bring concepts to life and allow students to practice applying what they’ve learned. AI can help you design dynamic, interactive exercises - from data simulations to ethical debates - that invite participation and deeper understanding. The goal is to make learning active, collaborative, and reflective.
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Examples (Mathematics)
Prompt Tip: AI can make in-class activities vivid and experiential - from generating data to moderating debates. Use it to simulate complexity, introduce unpredictability, or visualize invisible processes.
Use AI to accelerate formative feedback while keeping your professional judgment central. These patterns show how AI can surface rubric dimensions, diagnose misconceptions, and draft targeted comments you refine before release.
Policy Reminder: Use of AI for Feedback and Grading
Northeastern University policy governs the use of AI tools in courses. Please review Policy 125 and follow your college or department guidance.
Keep a human in the loop - do not rely solely on AI to grade or determine outcomes.
Protect student privacy (FERPA) - avoid uploading identifiable student work to external tools.
Be transparent with students about how AI-assisted feedback is used in your course.
Verify and edit AI output, you remain responsible for accuracy, equity, and tone.
Document your AI use in course materials, for example the syllabus, when appropriate.
This summary is informational only. Refer to the official policy for requirements and updates.
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Examples (Mathematics)
Prompt Tip: AI-assisted feedback helps identify learning patterns quickly - giving students timely insights while freeing faculty time for deeper guidance. Always refine and humanize AI output before sharing.