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Leveraging Machine Learning Approach to Identify the Predictors of Informal Digital Learning of English Behaviours among EFL Learners
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Yu Cui; Lingjie Tang; Fang Fang – Journal of Computer Assisted Learning, 2025
Background Study: With the rapid transition to remote learning necessitated by the closure of traditional educational infrastructures globally, the arena of informal digital learning of English (IDLE) has received much attention, particularly among English as a Foreign Language (EFL) learners in China. Objective: This study explores how…
Descriptors: Electronic Learning, Artificial Intelligence, Predictor Variables, Informal Education
Toward Building a Fair Peer Recommender to Support Help-Seeking in Online Learning
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Li, Chenglu; Xing, Wanli; Leite, Walter L. – Distance Education, 2022
Help-seeking is a valuable practice in online discussion forums. However, the asynchronicity and information overload of online discussion forums have made it challenging for help seekers and providers to connect effectively. This study formulated a new method to provide fair and accurate insights toward building a peer recommender to support…
Descriptors: Peer Relationship, Help Seeking, Electronic Learning, Distance Education
Toward Building a Fair Peer Recommender to Support Help-Seeking in Online Learning
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Li, Chenglu; Xing, Wanli; Leite, Walter L. – Grantee Submission, 2022
Help-seeking is a valuable practice in online discussion forums. However, the asynchronicity and information overload of online discussion forums have made it challenging for help seekers and providers to connect effectively. This study formulated a new method to provide fair and accurate insights toward building a peer recommender to support…
Descriptors: Peer Relationship, Help Seeking, Electronic Learning, Distance Education
The Impact of VR and AR Technologies on the Academic Achievements of Medical Students: The Age Aspect
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Vladimir Beketov; Marina Lebedeva; Marina Taranova – Interactive Learning Environments, 2024
The use of the innovative technologies, in particular virtual and augmented reality technologies, can have a significant impact on the training of future doctors. The sample set of the experiment consisted of 211 students from I.M. Sechenov First Moscow State Medical University. The students were divided into 4 age groups: full-time students of…
Descriptors: Artificial Intelligence, Computer Simulation, Academic Achievement, Influence of Technology