How to Create Sticky, Embodied Content: Designing and Assessing With Immersive Visual Technologies

• In Event: Of Bodies and Minds: Immersive Physical Sensor Technologies and STEM Learning

Abstract

We have been designing educational content for immersive virtual platforms for over seven years. With the advent of the more cost-effective Microsoft KINECT camera we have been able to reach a broader audience with motion capture technologies and would like to share what we have learned about creating embodied educational content. We propose that three necessary components be present in a range to a garner a degree of embodiment: a) amount of motoric engagement, b) gestural congruency– that is, how well-mapped the evoked gesture is to the content to be learned, and c) perception of immersion (Johnson-Glenberg, Birchfield, Tolentino, & Koziupa, in press). Bearing these degrees in mind, our lab called the Embodied Games for Learning Lab’s has developed a set of heuristics when creating educational games (see Table 1 in document version).

We will present results from two experiments investigating the relationships among embodiment, technology platform, and learning design. The first study was on concepts of Centripetal Force. Our experimental platform was SMALLab - Situated Multimedia Arts Learning Lab. This is a 15 X 15 foot space with an interactive floor projection. The system tracks a hand-held wand using 12 infrared motion capture cameras. Several randomized controlled studies have demonstrated significant gains when SMALLab-learned content is compared to learning in a regular classroom (Tolentino, Birchfield, Megowan-Romanowicz, Johnson-Glenberg, Kelliher, & Martinez, 2009; Johnson-Glenberg, Birchfield, Tolentino, & Koziupa (in press). The recent study included six conditions by crossing two levels of embodiment (low versus high) with three platforms: 1) SMALLab, 2) an Interactive Whiteboard environment, and 3) a desktop environment—all requiring different kinds of relevant motion from learners. At immediate posttest all groups learned significant amounts and all learned the same amount. However, results on the one-week follow-up revealed that the embodied learning condition continued to show gains in generative physics knowledge, while the low embodied group decreased in knowledge. This significant effect of learning by time suggests that there may be a type of consolidation of knowledge that occurs after learning in an embodied, multimodal manner. A second design example will come from the Electric Fields experiment (another DRK12 NSF sponsored study). We are finalizing the creation of four conditions to instruct in Coulombs Law: 1) pure symbol manipulation, 2) low embodied- watch simulation, 3) high embodied- manipulate simulations, and 4) full game version with manipulation – essentially how does wrapping a game (The Lightning Apprentice) around the content affect learning.

It is crucial that new media instructional designers and learning scientists share their design principles with others, as well as sharing lessons learned the hard way. Several of our studies have not been published because the learning gains between platforms were identical. This had not been predicted. It is only recently that we have begun to add delayed follow-up tests and now we see consistent and intriguing results favoring the embodied learning condition. These results may support the concept of memory consolidation occurring after instruction in a multi-modal and embodied manner.

Author

• Mina Catherine Johnson-Glenberg, Arizona State University