Abstract
The limitations of current AR assembly training systems’ guided information have prompted exploration into enhancing efficiency and user experience. By integrating information decay strategies with individual learning status, this paper focuses on customizing decay to improve AR training. Against the backdrop of AR manual assembly training, we designed a user-centered adaptive gradual decay training program (“Adapt Grad Dec”) and developed a corresponding AR system using Unity 3D. To evaluate the effectiveness of “Adapt Grad Dec” in AR manual assembly training, a user study was conducted that compared it against both pre-programmed decay conditions and a non-decay condition, drawing on insights from previous research. The pre-programmed decay conditions included three variations: (1) only gradual decay of training information (“Only Grad Dec”), (2) fast decay of training information with manual adjustment options (“Fst Dec and Manl Adj”), and (3) gradual decay with manual adjustment options (“Grad Dec and Manl Adj”). In contrast, the un-decay condition involved no reduction of training information throughout the process (“UnDec”). Results demonstrated that participants performed better in various aspects under the “Adapt Grad Dec” condition compared to “Only Grad Dec.” Based on findings, we propose that combining individual learning conditions with gradual decay strategies is a potentially effective approach to enhancing AR training outcomes. Additionally, the study also discusses limitations and future research directions.
Published Version
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