Expertise-based Adaptive AR Instructions with Motion Data

Abstract

Augmented Reality has been used to support users in a range of scenarios, often showing advantages over traditional approaches such as paper-based instructions. However, existing systems rarely consider the user's expertise when presenting instructional content. We investigate how expertise can be predicted from data available in a consumer-grade head-mounted display and use these predictions to implement an adaptive augmented reality assembly tutorial that tailors instructional support to the user. Expertise classification is performed on a public dataset using different machine learning algorithms. Results show motion-based expertise classification is feasible, demonstrating the potential for adaptive instructional systems.

Citation Copy

@proceedings{kaimel2026ExpertiseDetection,
	author={Kaimel, Tania and Kalkofen, Denis and Skreinig, Lucchas Ribeiro and Stanescu, Ana},
	title={Expertise-based Adaptive AR Instructions with Motion Data}, 
	booktitle={IEEE Int. Symp. on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)}, 
	doi={10.1109/ISMAR-Adjunct73196.2026.00196}
}