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Yanqing Wang; Shaoying Gong; Ning Jia; Ying Liu – Journal of Computer Assisted Learning, 2025
Background: Online learning is becoming increasingly popular among learners. To enhance the effectiveness of online learning, researchers have embedded an affective pedagogical agent (PA) on the computer screen to help regulate learners' emotions and support their learning. However, previous research has paid little attention to the effects of…
Descriptors: Metacognition, Prompting, Electronic Learning, Computer Uses in Education
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Jiyou Jia; Tianrui Wang; Yuyue Zhang; Guangdi Wang – Asia Pacific Journal of Education, 2024
In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…
Descriptors: Problem Solving, Artificial Intelligence, Learning Processes, Prompting
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Zheng, Xudong; Ma, Yunfei; Yue, Tingyan; Yang, Xianmin – Educational Technology Research and Development, 2023
The purpose of this study was to investigate the effects of different types of cues and self-explanation prompts in instructional videos on intrinsic motivation, learning engagement, learning outcomes, and cognitive load, which were indicators to measure deep learning performance. Seventy-two college students were randomly assigned to one of the…
Descriptors: Cues, Reflection, Prompting, Video Technology
Wu, Sally P. W.; Corr, Jainaba; Rau, Martina A. – Grantee Submission, 2019
Instructors in STEM classrooms often frame students' interactions with technologies to help them learn content. For instance, in many STEM domains, instructors commonly help students translate physical 3D models into 2D drawings by prompting them to focus on (a) orienting physical 3D models and (b) generating 2D drawings. We investigate whether…
Descriptors: Educational Technology, STEM Education, Teaching Methods, Learning Strategies
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Gurlitt, J.; Renkl, A. – Journal of Computer Assisted Learning, 2008
We investigated whether and how prior knowledge activation improves learning outcomes for high school (less experienced learners) and university students (experienced learners) in a hypertext environment. Map coherence was defined as the extent to which relationships between the concepts in the map were made explicit. Therefore, we classified the…
Descriptors: High School Students, College Students, Concept Mapping, Learning Strategies