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Pan, Wen Fu – Educational Technology & Society, 2017
The objective of this study was to test whether the Kinect motion-sensing interactive system (KMIS) enhanced students' English vocabulary learning, while also comparing the system's effectiveness against a traditional computer-mouse interface. Both interfaces utilized an interactive game with a questioning strategy. One-hundred and twenty…
Descriptors: Elementary School Students, English Instruction, Vocabulary Development, Control Groups
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Guevara-Cedeno, J. Y.; Palma-Behnke, R.; Uribe, R. – IEEE Transactions on Education, 2012
In the field of electricity markets, the development of training tools for engineers has been extremely useful. A novel experimental economics approach based on a computational Web platform of an electricity market is proposed here for the practical teaching of electrical engineering students. The approach is designed to diminish the gap that…
Descriptors: Foreign Countries, Theory Practice Relationship, Cooperative Learning, Teaching Methods
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Yang, Jie Chi; Chien, Kun Huang; Liu, Tzu Chien – Turkish Online Journal of Educational Technology - TOJET, 2012
Energy education has been conducted to equip learners with relevant energy conservation knowledge for many years. However, learners seldom put the knowledge into practice and even have few ideas about how to reduce energy consumption. To this end, there is a need to address this issue to improve the efficiency of energy education. One of the…
Descriptors: Foreign Countries, Learning Motivation, Learning Strategies, Energy Conservation
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Zhao, Guopeng; Ailiya; Shen, Zhiqi – Educational Technology & Society, 2012
Teachable agent is a type of pedagogical agent which instantiates Learning-by-Teaching theory through simulating a "naive" learner in order to motivate students to teach it. This paper discusses the limitation of existing teachable agents and incorporates intrinsic motivation to the agent model to enable teachable agents with initiative…
Descriptors: Foreign Countries, Instructional Design, Artificial Intelligence, Electronic Learning