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Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
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Md. Shahinur Rahman; Md. Mahiuddin Sabbir; Jing Zhang; Iqbal Hossain Moral; Gazi Md. Shakhawat Hossain – Australasian Journal of Educational Technology, 2023
Little knowledge is available on students' attitudes and behavioural intentions towards using ChatGPT, a breakthrough innovation in recent times. This study bridges this gap by adding two relevant less-explored constructs (i.e., perceived enjoyment and perceived informativeness) to the technology acceptance model and illustrating the moderating…
Descriptors: Student Behavior, Intention, Student Attitudes, Artificial Intelligence
Jaggar, Angela, Ed.; Smith-Burke, M. Trika, Ed. – 1985
Intended for teachers and others having responsibility for shaping language policy in the schools, this collection of invited, original articles is based on the belief that a teacher's task is not to "teach" children language but, rather, to create an environment that will allow language learning to occur naturally. The book is divided into four…
Descriptors: Beginning Reading, Child Development, Child Language, Classroom Environment