Investigating the Influence of Spatial Ability in Augmented Reality-assisted Robot Programming

Abstract

Augmented Reality (AR) offers promising opportunities to enhance learning, but its mechanisms and effects are not yet fully understood. As learning becomes increasingly personalized, considering individual learner characteristics becomes more important. This study investigates the moderating effect of spatial ability on learning experience with AR in the context of robot programming. A between-subjects experiment ($N=71$) compared conventional robot programming to an AR-assisted approach using a head-mounted display. Participants' spatial ability was assessed using the Mental Rotation Test. The learning experience was measured through the System Usability Scale (SUS) and cognitive load. The results indicate that AR support does not significantly improve the learning experience compared to the conventional approach. However, AR appears to have a compensatory effect on the influence of spatial ability. In the control group, spatial ability was significantly positively associated with SUS scores and negatively associated with extraneous cognitive load, indicating that higher spatial ability predicts a better learning experience. In the AR condition, these relationships were not observable, suggesting that AR mitigated the disadvantage typically experienced by learners with lower spatial abilities. These findings suggest that AR can serve a compensatory function by reducing the influence of learner characteristics. Future research should further explore this compensatory role of AR to guide the design of personalized learning environments that address diverse learner needs and reduce barriers for learners with varying cognitive profiles.