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Rungsilp, Chutimon; Piromsopa, Krerk; Viriyopase, Atthaphon; U-Yen, Kongpop – International Association for Development of the Information Society, 2021
The study of mind-wandering is popular since it is linked to the emotional problems and working/learning performance. In terms of education, it impacts comprehension during learning which affects academic success. Therefore, we sought to develop a machine learning model for an embedded portable device that can categorize mind-wandering state to…
Descriptors: Brain Hemisphere Functions, Diagnostic Tests, Artificial Intelligence, Cognitive Processes
Moreno, Valter; Cavazotte, Flavia; Alves, Isabela – British Journal of Educational Technology, 2017
Students' success in e-learning programs depends on how they adopt and embed technology into their learning activities. Drawing on the Technology Acceptance Model, we propose a framework to explain students' intention to use e-learning platforms effectively, that is, their intention to fully exploit system's functionalities in leaning processes,…
Descriptors: College Students, Electronic Learning, Intention, Student Attitudes
Karanam, Saraschandra; van Oostendorp, Herre; Indurkhya, Bipin – Behaviour & Information Technology, 2012
CoLiDeS + Pic is a cognitive model of web-navigation that incorporates semantic information from pictures into CoLiDeS. In our earlier research, we have demonstrated that by incorporating semantic information from pictures, CoLiDeS + Pic can predict the hyperlinks on the shortest path more frequently, and also with greater information scent,…
Descriptors: Semantics, Hypermedia, Semiotics, Visual Stimuli