This chapter aims to unveil how a Brain-Computer Interface (BCI) system, in conjunction with Augmented Reality (AR) glasses and online platforms such as Zoom, can change students’ language learning experiences and enhance overall learning. To assess the power of AR for language learning, we ran a series of experiments. We found that generating associations with the learned words is critical for acquiring an unknown language that shares no features with the participant’s native language. Employing associative techniques such as these might also be beneficial in other learning contexts. Results of an Electroencephalogram (EEG) analysis suggest that brain oscillations within the Delta waves bandwidth were prominent during the generation of associations, and especially prominent in the brain area known as the corpus callosum. Based on these results we have developed a concept of a BCI system that analyzes learners’ Power Spectrum Density in real time and extracts the Delta waves patterns associated with the corpus callosum as learners generate associations with the given words. Depending on the pattern of the Delta bandwidth, the system automatically provides support for generating relevant associations. Ongoing EEG monitoring demonstrates learners’ capacity to control the Delta waves.

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A Science-Based Environment for Lexical Language Learning

  • Vered Levi Zaydel

摘要

This chapter aims to unveil how a Brain-Computer Interface (BCI) system, in conjunction with Augmented Reality (AR) glasses and online platforms such as Zoom, can change students’ language learning experiences and enhance overall learning. To assess the power of AR for language learning, we ran a series of experiments. We found that generating associations with the learned words is critical for acquiring an unknown language that shares no features with the participant’s native language. Employing associative techniques such as these might also be beneficial in other learning contexts. Results of an Electroencephalogram (EEG) analysis suggest that brain oscillations within the Delta waves bandwidth were prominent during the generation of associations, and especially prominent in the brain area known as the corpus callosum. Based on these results we have developed a concept of a BCI system that analyzes learners’ Power Spectrum Density in real time and extracts the Delta waves patterns associated with the corpus callosum as learners generate associations with the given words. Depending on the pattern of the Delta bandwidth, the system automatically provides support for generating relevant associations. Ongoing EEG monitoring demonstrates learners’ capacity to control the Delta waves.