Connecting Feedback to Choice: Understanding Educator Preferences in GenAI vs. Human-Created Lesson Plans in K-12 Education -- A Comparative Analysis
Project Overview
The document examines the integration of generative AI (GenAI) in K-12 education, with a specific focus on its application in lesson planning. A comparative analysis of AI-generated lesson plans—produced by customized GPT-4 and fine-tuned LLaMA-2-13b models—versus those created by human educators reveals a nuanced landscape. While human-designed plans are still favored, particularly in elementary education, AI-generated plans are gaining traction in high school settings. The research indicates that using GenAI as a collaborative tool can improve the efficiency of lesson planning without compromising educational quality. Overall, the findings underscore the potential of generative AI to support teachers in creating effective lesson plans, suggesting a future where AI serves as a valuable partner in the educational process.
Key Applications
Comparative analysis of lesson plans generated by AI models and human curriculum designers.
Context: K-12 education, particularly for mathematics lesson planning.
Implementation: An exploratory study with mathematics educators evaluating lesson plans from AI models and human designers.
Outcomes: Identified that AI-generated lesson plans can rival human-created plans in certain contexts, especially at the high school level.
Challenges: AI-generated plans often lack domain-specific knowledge, leading to potential inaccuracies and pedagogical misalignments.
Implementation Barriers
Technological Barrier
Generative AI tools often lack domain-specific knowledge, leading to inaccuracies in content and pedagogy.
Proposed Solutions: Fine-tuning AI models with domain-specific datasets and incorporating educator feedback into model training.
Perceptual Barrier
Educators exhibit a preference for human-authored plans due to perceived higher quality and engagement levels.
Proposed Solutions: Highlighting effective use cases of AI-generated content and demonstrating improvements in AI-generated plans.
Project Team
Shawon Sarkar
Researcher
Min Sun
Researcher
Alex Liu
Researcher
Zewei Tian
Researcher
Lief Esbenshade
Researcher
Jian He
Researcher
Zachary Zhang
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Shawon Sarkar, Min Sun, Alex Liu, Zewei Tian, Lief Esbenshade, Jian He, Zachary Zhang
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18
Analysis Provider: Openai