Remote embodiment for augmented collaborative help (REACH): Supporting distributed maker communities

Based in constructivist and socio-cultural learning theories, Makerspaces support learners in communities of practice as they construct knowledge through shared work and construction of personally meaningful artifacts. However, uneven access to support from mentors and peers can make participation in maker activities challenging. Aiming to expand the benefits of co-located making to provide maker support at a distance, the three studies presented in this dissertation investigate extended and augmented (XR & AR) remote making interactions using a camera-projector device, REACH (Remote Embodiment for Augmented Collaborative Help) that merges local and remote workspaces for joint work. By projecting artifacts for shared viewing and gesturing, REACH enables mentors and student peers to engage in real-time discussions, adjustments, and exploration of artifacts, supporting cognitive and communication processes without a shared physical space. This gesture-driven collaboration model facilitates just-in-time support, allowing mentors and peers to provide guidance, scaffolding, and feedback in ways that mimic the dynamics of in-person maker interactions. Through this approach, REACH outlines the ways in which XR & AR applications can bridge the gap between in-person and remote mentorship and peer collaboration, ensuring that learners in distributed makerspaces have access to the support they need to engage in meaningful, technology-enhanced making experiences.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Curriculum and Instruction

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Smith, Casey James

Contributors dc:contributor

• Tissenbaum, Mike
• Lindgren, Robb
• Mercier, Emma
• Hathaway Goldstein, Molly

• Maker Education
• Computing Education, Collaboration
• Physically Distributed Learning
• Divergent Collaborative Learning Mechanisms

Statement dc:rights

• Copyright 2025 Casey Smith

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129408

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129408