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Junokas, M. J.; Lindgren, R.; Kang, J.; Morphew, J. W. – Journal of Computer Assisted Learning, 2018
Gestural recognition systems are important tools for leveraging movement-based interactions in multimodal learning environments but personalizing these interactions has proven difficult. We offer an adaptable model that uses multimodal analytics, enabling students to define their physical interactions with computer-assisted learning environments.…
Descriptors: Nonverbal Communication, Multimedia Instruction, Computer Assisted Instruction, Data Analysis
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Taminiau, E. M. C.; Kester, L.; Corbalan, G.; Spector, J. M.; Kirschner, P. A.; Van Merriënboer, J. J. G. – Journal of Computer Assisted Learning, 2015
On-demand education enables individual learners to choose their learning pathways according to their own learning needs. They must use self-directed learning (SDL) skills involving self-assessment and task selection to determine appropriate pathways for learning. Learners who lack these skills must develop them because SDL skills are prerequisite…
Descriptors: Independent Study, Metacognition, Student Needs, Self Evaluation (Individuals)
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Hummel, Hans G. K.; Paas, Fred; Koper, E. J. R. – Journal of Computer Assisted Learning, 2004
We investigate the effects of cueing, in a multimedia programme for the individualized training of the whole task to prepare a plea, on the learning outcomes of 43 sophomore law students. The cueing formats of worked-out examples (WOEs), process worksheets (PWs), and both WOE and PW are compared to a no-cueing control condition. Our hypotheses…
Descriptors: Law Students, Multimedia Instruction, Cues, Comparative Analysis