Abstract

Smart Glasses such as Google Glass are mobile computers combining classical Head-Mounted Displays (HMD) with several sensors. Therefore, contact-free, sensor-based experiments can be linked with relating, near-eye presented multiple representations. We will present a first approach on how Smart Glasses can be used as an experimental tool for head-centered, context-aware, wearable-technology-enhanced, and inquiry-based learning in physics education. Therefore, we developed an app that is based on the Google Glass platform and designed to perform educational physical experiments on the topic of acoustics. Its initial application is intended for high-school students whose task is to study the relationship between the frequency of the sound generated by hitting a glass of water and the amount of water in the glass. The core idea is to have Google Glass automatically measure both the water fill level with the camera and the sound frequency with the microphone, and incrementally generate a fill level/frequency graph in the HMD. We designed an educational setting and studied its effect on cognitive and affective variables with an intervention-control-group design. While the intervention group analyzed the fill level/frequency relationship with the Google Glass platform, control group 1 worked on the phenomenon using the same platform implemented on a tablet PC. Control group 2 analyzed the phenomenon using a tablet PC with a typical mobile-based education platform. We used a two-way ANCOVA to study learning outcome, wondering, curiosity, cognitive load, and experimentation time as dependent variables of 46 high-school eighth-graders together with group membership and gender influence as independent variables. While the positive effects of using Google Glass as a mobile lab on wondering and curiosity as well as a positive trend for experimentation time were detected, no differences were analyzed for learning achievement. Although students have a higher cognitive load when working with Google Glass compared to other devices, the cognitive load level is very low in general.

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