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Direct linkXin Tang; Zhiqiang Yuan; Shaojun Qu – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (AI) represents a significant technological leap, with platforms like OpenAI's ChatGPT and Baidu's Ernie Bot at the forefront of innovation. This technology has seen widespread adoption across various sectors of society and is anticipated to revolutionise the educational landscape, especially in the…
Descriptors: Influences, College Students, Student Behavior, Intention
Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
Marco Rüth; Maria Jansen; Kai Kaspar – Journal of Computer Assisted Learning, 2024
Background: Online exams have become a more common form of assessment at universities due to the COVID-19 pandemic. However, cheating behaviour in online exams is widespread and threatens exam validity as well as student learning and well-being. Objective: To better understand the role of university students' needs, conceptions and reasons…
Descriptors: Foreign Countries, College Students, Computer Assisted Testing, Cheating
