AI for the Educators: Module 1: Practical Skills in Crafting Effective Prompts
Posted by anne.grey
Presenter: Lakshmi Srinivasan
Summary
As artificial intelligence becomes increasingly integrated into higher education, faculty members need practical skills to navigate and utilize these tools effectively. This interactive workshop introduces educators to prompt engineering—the art of crafting clear, structured instructions to get reliable and relevant outputs from generative AI. Approaching AI as a personal assistant rather than a replacement for instructional expertise, the session emphasizes how educators can save time, improve teaching productivity, and better prepare students for an AI-driven world.
The presentation covers foundational and advanced prompting strategies. Essential practices include specifying distinct personas, defining exact output formats, and engaging in iterative refinement. Participants explore advanced concepts such as Chain-of-Thought reasoning (asking AI to solve problems step-by-step), Prompt Chaining (deconstructing complex workflows), zero-shot versus few-shot prompting, and self-criticism techniques. Additionally, the session highlights key parameters like Temperature and Top-P, demonstrating how adjusting these settings controls whether an AI response is predictable and focused or highly creative.
Participants also gain hands-on experience with campus-supported tools, including Google Gemini (comparing the Flash and Pro models for coding and mathematics) and custom Google Gems to automate repetitive teaching tasks. Finally, the workshop demonstrates NotebookLM, showing how faculty can curate slide decks, documents, and web links into a single notebook to instantly generate study guides, FAQs, and multimedia overviews for students.
View AI for the Educators: Module 1 Presentation Slides
View Prompt Engineering Practice Spreadsheet
View Google Gems Examples Document
Presentation Outcomes
- Master Foundational Prompting: Craft effective prompts using defined roles, target audience specifications, explicit formatting, and step-by-step evaluation methods.
- Apply Advanced Prompt Frameworks: Utilize chain-of-thought reasoning, prompt decomposition, zero-shot/few-shot examples, and self-critique techniques to handle complex academic tasks.
- Control AI Output Parameters: Adjust temperature and Top-P values to balance analytical precision with creative generation in AI responses.
- Build Custom AI Workflows: Navigate Google Gemini Flash and Pro models and design reusable Google Gems to streamline lesson planning and feedback.
- Synthesize Content with NotebookLM: Combine course documents, websites, and media files into centralized notebooks to produce interactive study guides, quizzes, and summaries.
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