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Yang, Yang; Leung, H.; Yue, Lihua; Deng, LiQun – IEEE Transactions on Learning Technologies, 2012
In this paper, an automatic lesson generation system is presented which is suitable in a learning-by-mimicking scenario where the learning objects can be represented as multiattribute time series data. The dance is used as an example in this paper to illustrate the idea. Given a dance motion sequence as the input, the proposed lesson generation…
Descriptors: Foreign Countries, Dance Education, Lesson Plans, Pattern Recognition
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Ferster, Bill; Hammond, Thomas C.; Alexander, R. Curby; Lyman, Hunt – Journal of Interactive Learning Research, 2012
The hurried pace of the modern classroom does not permit formative feedback on writing assignments at the frequency or quality recommended by the research literature. One solution for increasing individual feedback to students is to incorporate some form of computer-generated assessment. This study explores the use of automated assessment of…
Descriptors: Feedback (Response), Scripts, Formative Evaluation, Essays
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Liu, Ming; Calvo, R. A.; Aditomo, A.; Pizzato, L. A. – IEEE Transactions on Learning Technologies, 2012
In this paper, we present a novel approach for semiautomatic question generation to support academic writing. Our system first extracts key phrases from students' literature review papers. Each key phrase is matched with a Wikipedia article and classified into one of five abstract concept categories: Research Field, Technology, System, Term, and…
Descriptors: Foreign Countries, Computer Assisted Instruction, Web 2.0 Technologies, Automation
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Wieling, M. B.; Hofman, W. H. A. – Computers & Education, 2010
To what extent a blended learning configuration of face-to-face lectures, online on-demand video recordings of the face-to-face lectures and the offering of online quizzes with appropriate feedback has an additional positive impact on the performance of these students compared to the traditional face-to-face course approach? In a between-subjects…
Descriptors: Feedback (Response), Grade Point Average, Predictor Variables, Lecture Method