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Du, Jiahui; Hew, Khe Foon Timothy – Journal of Research on Technology in Education, 2022
Self-regulated learning (SRL) plays a significant role in promoting academic success in online education. In recent years, attention has focused on using new techniques to promote SRL--one of which is the recommender system. However, there has been little discussion of the actual effects of using recommender systems to facilitate SRL skills among…
Descriptors: Independent Study, Electronic Learning, Artificial Intelligence, Information Technology
Peter Pavlis – Online Submission, 2025
This quantitative, quasi-experimental study aimed to propose research-based AI constructivist learning activities by measuring students' self-perceptions of their critical thinking using the Motivational Strategies and Learning Questionnaire (MSLQ). The study utilized the input-experience-output framework to evaluate how these learning pursuits…
Descriptors: Critical Thinking, Artificial Intelligence, Constructivism (Learning), Learning Activities
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Ng, Davy Tsz Kit; Chu, Samuel Kai Wah – Online Learning, 2021
In Hong Kong, after-school activities have long been used to foster friendships and to allow students to pursue their interests in an informal setting. This case study reports on a three-phase action research process in which information technology teachers delivered after-school activities focused on artificial intelligence during the COVID-19…
Descriptors: Student Motivation, Student Satisfaction, Secondary School Students, Artificial Intelligence
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Aryadoust, Vahid – International Journal of Testing, 2015
The present study uses a mixture Rasch model to examine latent differential item functioning in English as a foreign language listening tests. Participants (n = 250) took a listening and lexico-grammatical test and completed the metacognitive awareness listening questionnaire comprising problem solving (PS), planning and evaluation (PE), mental…
Descriptors: Item Response Theory, English (Second Language), Listening Comprehension Tests, Metacognition
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McLaren, Bruce M.; DeLeeuw, Krista E.; Mayer, Richard E. – Computers & Education, 2011
Should an intelligent software tutor be polite, in an effort to motivate and cajole students to learn, or should it use more direct language? If it should be polite, under what conditions? In a series of studies in different contexts (e.g., lab versus classroom) with a variety of students (e.g., low prior knowledge versus high prior knowledge),…
Descriptors: Feedback (Response), Test Items, Intervention, Intelligent Tutoring Systems
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Musso, Mariel F.; Kyndt, Eva; Cascallar, Eduardo C.; Dochy, Filip – Frontline Learning Research, 2013
Many studies have explored the contribution of different factors from diverse theoretical perspectives to the explanation of academic performance. These factors have been identified as having important implications not only for the study of learning processes, but also as tools for improving curriculum designs, tutorial systems, and students'…
Descriptors: Prediction, Academic Achievement, Networks, Learning Processes