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Gerardo Ibarra-Vazquez; Maria Soledad Ramirez-Montoya; Mariana Buenestado-Fernandez – IEEE Transactions on Learning Technologies, 2024
This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and…
Descriptors: Gender Differences, Open Education, Cross Cultural Studies, Student Attitudes
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Ruiperez-Valiente, Jose A.; Gaydos, Matthew; Rosenheck, Louisa; Kim, Yoon Jeon; Klopfer, Eric – IEEE Transactions on Learning Technologies, 2020
Learning games have great potential to become an integral part of new classrooms of the future. One of the key reported benefits is the capacity to keep students deeply engaged during their learning process. Therefore, it is necessary to develop models that can measure quantitatively how learners are engaging with learning games to inform game…
Descriptors: Behavior Patterns, Learner Engagement, Learning Analytics, Computer Games
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Calvo-Morata, Antonio; Rotaru, Dan Cristian; Alonso-Fernandez, Cristina; Freire-Moran, Manuel; Martinez-Ortiz, Ivan; Fernandez-Manjon, Baltasar – IEEE Transactions on Learning Technologies, 2020
Bullying is a serious social problem at schools, very prevalent independently of culture and country, and particularly acute for teenagers. With the irruption of always-on communications technology, the problem, now termed cyberbullying, is no longer restricted to school premises and hours. There are many different approaches to address…
Descriptors: Educational Games, Bullying, Computer Mediated Communication, Learning Analytics