Start Date

11-12-2016 12:00 AM

Description

By understanding the psychophysiological factors behind successful e-learning, we aim to identify new techniques that improve participant retention and engagement. Past work has explored the relationship between Electroencephalography (EEG) and learning constructs, such as Cognitive Load and Cognitive Absorption. We believe that the unique application of an e-learning environment warrants an extension of existing theories. Our goal is to develop and validate a model explaining the role of Cognitive Load on Knowledge Gained. This research provides the foundation to then apply this model to create a neuroadaptive learning system. We describe an experiment that uses noninvasive tools to validate this model and explore the viability of off-the-shelf EEG for data collection in e-learning experiments. Potential theoretical contributions are discussed and results from a technical pilot are provided.

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Dec 11th, 12:00 AM

Psychophysiological Measures of Cognitive Absorption and Cognitive Load in E-Learning Applications

By understanding the psychophysiological factors behind successful e-learning, we aim to identify new techniques that improve participant retention and engagement. Past work has explored the relationship between Electroencephalography (EEG) and learning constructs, such as Cognitive Load and Cognitive Absorption. We believe that the unique application of an e-learning environment warrants an extension of existing theories. Our goal is to develop and validate a model explaining the role of Cognitive Load on Knowledge Gained. This research provides the foundation to then apply this model to create a neuroadaptive learning system. We describe an experiment that uses noninvasive tools to validate this model and explore the viability of off-the-shelf EEG for data collection in e-learning experiments. Potential theoretical contributions are discussed and results from a technical pilot are provided.