Two of the most important benefits of using computer-based learning environments are that (1) they allow for interactive learning experiences and (2) it becomes possible to assess learning at a fine level of granularity based on learner actions, choices, and performance. Using these assessments, modern systems can deliver tailored pedagogical interventions, such as through feedback or adjustment of problem difficulty, in order to enhance learning. To magnify their power to promote learning, researchers have also sought to capture additional information, such as physiological data, to make even finer-grained and nuanced pedagogical decisions. A wide range of technologies have been explored, such as depth-sensing cameras (e.g., Kinect), electrodermal activity (EDA) sensors, electroencephalography (EEG), posture/seat detectors, eye- and head-tracking cameras, and mouse-pressure sensors, among many others. This chapter provides an overview and examples of how these techniques have been used by educational technology researchers. We focus on how these additional inputs can improve technology-based pedagogical decision-making to support cognitive (i.e., knowledge and information processing), affective (i.e., emotions, including motivational factors), and metacognitive (i.e., attention and self-regulatory behaviors) aspects of learning. Though not a comprehensive review, we take a selective look at classic and recent developments in this area. The chapter concludes with a brief discussion of emerging topics and key open questions related to the use of physiological tracking in the context of education and learning with technology.
|Original language||English (US)|
|Title of host publication||Mind, Brain and Technology|
|Subtitle of host publication||Learning in the Age of Emerging Technologies|
|Editors||Thomas D Parsons, Lin Lin, Deborah Cockerham|
|ISBN (Print)||978-3-030-02630-1, 978-3-030-02631-8|
|State||Published - Dec 20 2018|
|Name||Educational Communications and Technology: Issues and Innovations|