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Jenny Yun-Chen Chan; Avery H. Closser; Vy Ngo; Hannah Smith; Allison S. Liu; Erin Ottmar – Journal of Computer Assisted Learning, 2023
Background: Prior work has shown that middle school students struggle with algebra and that game-based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what…
Descriptors: Teaching Methods, Game Based Learning, Middle School Students, Algebra
Qian Huangfu; Qianmei He; Sisi Luo; Weilin Huang; Yahua Yang – Journal of Computer Assisted Learning, 2025
Background: Video lectures which include the teachers' presence have become increasingly common. As teacher enthusiasm is a nonverbal cue in video lectures, more and more studies are focusing on this topic. However, little research has been carried out on the interactions between teacher enthusiasm and prior knowledge when learning from video…
Descriptors: Chemistry, Science Instruction, Teacher Student Relationship, Teacher Response
Liu, Qingtang; Yu, Shufan; Chen, Wenli; Wang, Qiyun; Xu, Suxiao – Journal of Computer Assisted Learning, 2021
While the use of experiments is important for developing students' scientific knowledge and skills, challenges may arise when teachers and students are conducting experiments in class, such as non-reusable experimental resources, safety issues and difficulties simulating some specific effects. Augmented reality (AR) technology affords an…
Descriptors: Science Experiments, Computer Simulation, Magnets, Junior High School Students
Wauters, K.; Desmet, P.; Van den Noortgate, W. – Journal of Computer Assisted Learning, 2010
The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching…
Descriptors: Knowledge Level, Adaptive Testing, Test Items, Item Response Theory