Scaling Evidence-based Instructional Design Expertise through Large Language Models

TL;DR

This paper explores how GPT-4 and similar large language models can be used to scale evidence-based instructional design, providing practical methods, case studies, and future visions for AI-assisted education.

Contribution

It introduces best practices and a framework for applying LLMs in instructional design, bridging theory and practice with real-world case studies.

Findings

GPT-4 effectively creates complex assessments and active learning components.

Human oversight is essential for quality assurance in AI-generated educational content.

Proposed future system for personalized, evidence-based instructional strategies.

Abstract

This paper presents a comprehensive exploration of leveraging Large Language Models (LLMs), specifically GPT-4, in the field of instructional design. With a focus on scaling evidence-based instructional design expertise, our research aims to bridge the gap between theoretical educational studies and practical implementation. We discuss the benefits and limitations of AI-driven content generation, emphasizing the necessity of human oversight in ensuring the quality of educational materials. This work is elucidated through two detailed case studies where we applied GPT-4 in creating complex higher-order assessments and active learning components for different courses. From our experiences, we provide best practices for effectively using LLMs in instructional design tasks, such as utilizing templates, fine-tuning, handling unexpected output, implementing LLM chains, citing references, evaluating output, creating rubrics, grading, and generating distractors. We also share our vision of a future recommendation system, where a customized GPT-4 extracts instructional design principles from educational studies and creates personalized, evidence-supported strategies for users' unique educational contexts. Our research contributes to understanding and optimally harnessing the potential of AI-driven language models in enhancing educational outcomes.