Honors College Thesis
 

A Study of Learning Effectiveness between Augmented and Traditional Methods in Crafting Origami

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  • Traditionally, people learn to perform object assembly tasks by following the steps in a paper-based instruction manual. Using augmented reality (AR) technology, the instructions could instead be computer generated and appear directly within the user’s workspace as they perform the task. Literature suggests AR’s feasibility in improving performance and learning effectiveness. However, some motor-skill tasks suggest that too much guidance could potentially have adverse effects on learning over a period of time. We initially aimed to use AR spatial animations, but after numerous design iterations, decided to focus on using AR to make the instructions and task more spatially coincident. We conducted an assembly task (crafting origami) experiment to explore the effects of using AR to place instructions directly within in the user’s workspace, and investigated performance over time via three training sessions. We also examined its effects on short-term learning via a test session (administered after a 10 min delay without rehearsal). The augmented condition was compared with results from an unassisted control condition, using standard paper instructions. The experiment was a 4 (session) x 2 (augmented versus paper) repeated-measures design with the latter condition counter-balanced to reduce order and carryover effects. To administer our design, two different origami assembly tasks (boat and swan) of similar complexity were selected. We found in our results that improvements in both completion times and accuracy for both conditions were gained across sessions. While completion times and accuracy appeared slightly better in the spatially coincident condition, these differences were not statistically significant. We suspect that this may be due to the noise introduced from the differing difficulties of crafting the boat and swan origami, even though we attempted to match them. We recommend the use of other assembly tasks and types of augmentations in future studies. We also propose research on the long-term learning effects of AR as a tool for assembly tasks over the course of hours, days, and weeks.
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