A Conceptual Framework for Supporting Expertise Development with Augmented Reality and Wearable Sensors

B.H. Limbu*, Mikhail Fominykh, R. Klemke, M.M. Specht

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Experts are imperative for supporting expertise development in apprentices but learning from them is difficult. In many cases, there are shortages of experts to train apprentices. To address this issue, we use wearable sensors and augmented reality to record expert performance for supporting the training of apprentices. In this context, we present the conceptual framework which outlines different instructional design methodologies for training various attributes of a task. These instructional design methodologies are characterized by their dependencies on expert performance and experts as model for training. In addition, they exploit the affordances of modern wearable sensors and augmented reality. The framework also outlines a training workflow based on the 4C/ID model, a pedagogic model for complex learning, which ensures that all aspects of conventional training are considered. The paper concludes with application guidelines and examples along with reflection of the authors.
Original languageEnglish
Title of host publicationPerspectives on Wearable Enhanced Learning (WELL)
Subtitle of host publicationCurrent Trends, Research, and Practice
EditorsIlona Buchem, Ralf Klamma, Fridolin Wild
Place of PublicationCham
PublisherSpringer
Chapter10
Pages213-228
Number of pages16
ISBN (Electronic)9783319643014
ISBN (Print)9783319643007
DOIs
Publication statusPublished - 2 Nov 2019

Cite this

Limbu, B. H., Fominykh, M., Klemke, R., & Specht, M. M. (2019). A Conceptual Framework for Supporting Expertise Development with Augmented Reality and Wearable Sensors. In I. Buchem, R. Klamma, & F. Wild (Eds.), Perspectives on Wearable Enhanced Learning (WELL): Current Trends, Research, and Practice (pp. 213-228). Springer. https://doi.org/10.1007/978-3-319-64301-4_10