Using sequential AI prompts to create more sophisticated and effective educational outcomes.
Chain prompting is an advanced technique where multiple AI prompts are used in sequence to achieve more complex and nuanced results. This approach allows faculty to break down complex tasks into manageable steps, refine outputs iteratively, and create more sophisticated educational materials. This guide explores how to effectively use chain prompting in educational contexts.
Definition: Chain prompting involves using the output of one AI prompt as input for subsequent prompts, creating a sequence of refined or developed content.
Key Benefits:
Step 1: Initial Content Generation
"Create an initial outline for [topic] suitable for [level] students."
Step 2: Content Expansion
"Expand each section of this outline with detailed explanations and examples."
Step 3: Enhancement
"Add engaging elements to this content including discussion questions and activities."
Step 4: Refinement
"Review and adjust the language and complexity for [specific audience]."
Step 1: Learning Objective Analysis
"Analyze these learning objectives and suggest appropriate assessment types."
Step 2: Question Generation
"Create assessment questions based on these suggested types."
Step 3: Answer Key Development
"Develop detailed answer keys and rubrics for these questions."
Step 4: Feedback Template Creation
"Create feedback templates for common response patterns."
Effective chain prompting should: