An agenda for neuroeducation: relating psychophysiological and behavioral data across time scales of learning

Abstract

Research on learning has previously focused on changes in knowledge and

Please Wait, Processing: A Selective Literature Review of the Neurological Understanding of Emotional Processing in ASD and Its Potential Contribution to Neuroeducation

“…As research methodologies and technology in neuroimaging continue to advance, it becomes even more imperative that such research projects be conducted in more practical and applied settings rather than laboratory environments. Because neuroimaging can detect changes in as short a time as a few milliseconds, well before raw behavioral observations can be facilitated, factors that affect the behavior, and potential modulations in that behavior, may be better identified, further enhancing the quickness and efficiency that core issues of individuals may be addressed [ 3 , 32 ].…”

The use of psychophysiological data to better understand real-time learning: the fragile balance between the validity of data and the authenticity of data collection contexts

“…Their work and methodologies could meet a transdisciplinary research need since many researchers, in education sciences and cognitive psychology among others, have been calling for some years now to the development and application of such real-time methods of data collection (e.g. Boekaerts, 2017;Campbell, 2011;Campbell & Pagé, 2012;Gerjets, 2017;Mercier & Charland, 2013;Timms, DeVelle, & Lay 2016), to enrich and develop theoretical models by combining them, notably, to behavioral data. These real-time data collection methods allow the study of processes related to metacognition (e.g.…”

L’utilisation de données psychophysiologiques pour mieux comprendre l’apprentissage en temps réel : le fragile équilibre entre la validité des données et l’authenticité des contextes de collecte de données

“…Leurs travaux et méthodologies pourraient répondre à un besoin en recherche transdisciplinaire puisque plusieurs chercheurs, en sciences de l'éducation et en psychologie cognitive entre autres, en appellent depuis quelques années déjà au développement et à l'application de telles méthodes de collecte de données en temps réel (p. ex. Boekaerts, 2017;Campbell, 2011, Campbell et Pagé, 2012Gerjets, 2017;Mercier et Charland, 2013;Timms, DeVelle et Lay, 2016), pour enrichir et développer leurs modèles théoriques, en les combinant notamment à des données comportementales. Ces ditesméthodes permettent l'étude de processus liés, notamment, à la métacognition (p. ex.…”