Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. From Apprenticeship to Autonomy: Mixed Reality-Assisted Training in a Cleanroom by a Hybrid Authoring Workflow
 
conference paper

From Apprenticeship to Autonomy: Mixed Reality-Assisted Training in a Cleanroom by a Hybrid Authoring Workflow

Shan, Qinglan  
•
Kapur, Manu
•
Brugger, Juergen  
April 13, 2026
Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems
CHI 2026: CHI Conference on Human Factors in Computing Systems

High-stakes environments like semiconductor cleanrooms traditionally rely on synchronous "master-apprentice" training, which is difficult to scale and resource-intensive. We present a Mixed Reality (MR)-assisted learning system equipped with a web-based authoring tool that allows instructors to create spatialized training modules and practical learning sessions. Through a long-term study (N = 15) spanning two semesters, we implemented MR usage as an assisting tool during the training. The findings reveal that this asynchronous scaffolding not only lowers the threshold to content creation but also provides an alternative way of learning and training in restricted environments. Video analysis also revealed a shift in social interaction: while training inside the cleanroom was previously dominated by instructors, MR promotes individual learning rather than imitating the instructors, although this shift to autonomy resulted in a state of situated isolation. Ultimately, this work validates a scalable, instructor-authored MR system that successfully transitions novices to self-regulated autonomy in high-stakes environments. CCS Concepts • Human-centered computing → Collaborative and social computing systems and tools; Mixed / augmented reality; • Applied computing → Interactive learning environments.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

3772363.3798988.pdf

Type

Main Document

Version

Published version

Access type

openaccess

License Condition

CC BY

Size

5.37 MB

Format

Adobe PDF

Checksum (MD5)

0e8ea3a675c186d5699699acbe39387f

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés