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Augmented Handcraft - Enhancing Manual Skill Acquisition through Adaptive Learning and Augmented Reality
This research aims to enhance manual skill acquisition for human craft in the Architecture, Engineering, and Construction (AEC) industry. Acquiring manual skills can be challenging due to limited sensing capabilities, difficulties in extracting useful information from the environment, and a lack of sufficient instructions. To address these issues, this research introduces an adaptive learning system that combines a sensing integration and an integral learning strategy on an Augmented Reality (AR) display.
The proposed adaptive learning system seeks to overcome the limitations of human sensing abilities by integrating additional sensors during skill practice. This data is then processed and displayed through an AR interface, providing users with concurrent feedback at the beginner state. As the users gain the essentials of the task, the feedback will be switched to fading and terminal feedback for medium users to internalize the instructions. This adaptive learning system offers a targeted solution to improve manual skill acquisition in the AEC industry, which enables users to receive accurate and timely information, enhancing their understanding of the task at hand and facilitating the development of effective strategies.
ITECH M.Sc. Thesis Project 2023: Augmented Handcraft - Enhancing Manual Skill Acquisition through Adaptive Learning and Augmented Reality
Min Deng
Thesis Advisers: Felix Amtsberg, Xiliu Yang
Thesis Supervisor: Prof. Achim Menges
Second Supervisor: Prof. Jan Knippers