Embodied mixed reality with passive haptics in STEM education: randomized control study with chemistry titration - Johnson-Glenberg, Mina C.; Yu, Christine S. P.; Liu, Frank; Amador, Charles; Bao, Yueming; Yu, Shufan; LiKamWa, Robert (Frontiers in Virtual Reality, 2023)
Researchers, educators, and multimedia designers need to better understand how mixing physical tangible objects with virtual experiences affects learning and science identity. In this novel study, a 3D-printed tangible that is an accurate facsimile of the sort of expensive glassware that chemists use in real laboratories is tethered to a laptop with a digitized lesson. Interactive educational content is increasingly being placed online, it is important to understand the educational boundary conditions associated with passive haptics and 3D-printed manipulables. Cost-effective printed objects would be particularly welcome in rural and low Socio-Economic (SES) classrooms. A Mixed Reality (MR) experience was created that used a physical 3D-printed haptic burette to control a computer-based chemistry titration experiment. This randomized control trial study with 136 college students had two conditions: 1) low-embodied control (using keyboard arrows), and 2) high-embodied experimental (physically turning a valve/stopcock on the 3D-printed burette). Although both groups displayed similar significant gains on the declarative knowledge test, deeper analyses revealed nuanced Aptitude by Treatment Interactions (ATIs). These interactions favored the high-embodied experimental group that used the MR device for both titration-specific posttest knowledge questions and for science efficacy and science identity. Those students with higher prior science knowledge displayed higher titration knowledge scores after using the experimental 3D-printed haptic device. A multi-modal linguistic and gesture analysis revealed that during recall the experimental participants used the stopcock-turning gesture significantly more often, and their recalls created a significantly different Epistemic Network Analysis (ENA). ENA is a type of 2D projection of the recall data, stronger connections were seen in the high embodied group mainly centering on the key hand-turning gesture. Instructors and designers should consider the multi-modal and multi-dimensional nature of the user interface, and how the addition of another sensory-based learning signal (haptics) might differentially affect lower prior knowledge students. One hypothesis is that haptically manipulating novel devices during learning may create more cognitive load. For low prior knowledge students, it may be advantageous for them to begin learning content on a more ubiquitous interface (e.g., keyboard) before moving them to more novel, multi-modal MR devices/interfaces.