Co-Designing Digital Humans for Online Learning: A Framework for Human-AI Pedagogical Integration

Abstract

Artificial intelligence (AI) and large language models (LLMs) are reshaping education, with virtual avatars emerging as digital teachers capable of enhancing engagement, sustaining attention, and addressing instructor shortages. Aligned with the Sustainable Development Goals (SDGs) for equitable quality education, these technologies hold promise yet lack clear guidelines for effective design and implementation in online learning. To fill this gap, we introduce a framework specifying when, what, and how digital teachers should be integrated. Our study combines (1) a design space analysis of 87 works across AI, educational technology, design, and HCI, (2) a survey of 132 learners' practices and preferences, and (3) three co-design workshops with 18 experts from pedagogy, design, and AI. It provides actionable guidance for educators, designers, and HCI researchers, advancing opportunities to build more engaging, equitable, and effective online learning environments powered by digital teachers.

References in corpus (9)

• Human-in-the-loop Artificial Intelligence
• Teach AI How to Code: Using Large Language Models as Teachable Agents for Programming Education
• XAIR: A Framework of Explainable AI in Augmented Reality
• A Piece of Theatre: Investigating How Teachers Design LLM Chatbots to Assist Adolescent Cyberbullying Education
• LessonPlanner: Assisting Novice Teachers to Prepare Pedagogy-Driven Lesson Plans with Large Language Models
• Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception
• Malleable Overview-Detail Interfaces
• NeuroChat: A Neuroadaptive AI Chatbot for Customizing Learning Experiences
• From Passive Watching to Active Learning: Empowering Proactive Participation in Digital Classrooms with AI Video Assistant