Beyond Tools, Toward Teammates: Human-AI Teaming for Inclusive Learning Analytics

Introduction

This half-day in-person workshop explores Human–AI teaming as a frontier for inclusive learning analytics. As AI systems evolve from passive tools to active teammates in collaborative learning environments, understanding their impact on equity, inclusion, and team dynamics has become essential. Grounded in the Machines as Teammates (MaT) framework, this session brings together researchers, educators, designers, and technologists to examine how learning analytics can guide the design and evaluation of AI teammates that foster belonging, mitigate bias, and enhance collaboration—particularly in STEM and team-based educational contexts. Rather than emphasizing paper submissions, the workshop focuses on interactive, activity-driven participation, including design sprints, group brainstorming, and conceptual mapping activities centered on Human-AI collaboration and inclusion.

Activities and Program

The workshop blends expert insights with collaborative design activities and demonstrations.
Sample sessions include:

• Welcome and Introduction – Framing Human-AI teaming and its relevance to inclusion in education

• Invited Talks – Brief presentations from leaders in AI, learning analytics, and DEI

• Panel Discussion – Exploring challenges and opportunities in Human-AI collaboration

• Human-AI Teaming Vignette Challenge – Analyze short scenarios of human-AI interaction and identify inclusion opportunities

• Design Your AI Teammate – Small-group sprint to prototype inclusive AI teammate concepts

• Interactive Demonstrations – Showcasing tools and platforms that foster equitable collaboration

• Roundtable Reflection – Synthesizing principles, frameworks, and open questions for future work

Outcomes and Community Impact

The workshop aims to:

• Co-create a shared agenda for research and design on Human-AI teaming in education.

• Develop community resources—summaries, frameworks, and recommendations—shared via open-access platforms.

• Foster sustained collaboration among participants through post-event initiatives and cross-disciplinary partnerships.

Together, these outcomes will help define how learning analytics can guide the responsible integration of AI teammates in education—advancing both the science of teamwork and the practice of inclusive, data-informed learning.