DescriptionHumans have become increasingly dependent on digital technologies. As a result, the study of how digital tools shape human behavior and the brain has become an important research area in education and neuroscience. In this talk, I outline the approach of digital language learning (DLL) for bilingual language learning and representation, and provide a theoretical synthesis and analytical framework with respect to DLL’s current and future promises. Theoretically, the DLL approach serves as the basis for understanding differences between child language learning adult second language learning, and for understanding the neurocognitive mechanisms underlying learning context and learner differences. Practically, based on findings from learner behaviors, cognitive abilities, and brain correlates, DLL can inform the design of better tools and platforms for language pedagogies. Because of its highly interdisciplinary nature, DLL serves to integrate cognitive neuroscience and education with the rapid developments in AI and big data analytics, providing a gateway for multilingual communication, intercultural adaptation, and social integration.
|Period||30 Apr 2022|
|Held at||Taiwan Society of Cognitive Neuroscience, Taiwan|
|Degree of Recognition||International|