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Direct linkTsai, Jinn-Tsong; Chou, Ping-Yi; Fang, Jia-Cen – IEEE Transactions on Education, 2012
An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and…
Descriptors: Puzzles, Artificial Intelligence, Mathematics, Computer Science Education
Hwang, Gwo-Jen; Tsai, Chin-Chung; Yang, Stephen J. H. – Educational Technology & Society, 2008
Recent progress in wireless and sensor technologies has lead to a new development of learning environments, called context-aware ubiquitous learning environment, which is able to sense the situation of learners and provide adaptive supports. Many researchers have been investigating the development of such new learning environments; nevertheless,…
Descriptors: Learning Activities, Computer Uses in Education, Criteria, Educational Environment
Lu, Chun-Hung; Wu, Chia-Wei; Wu, Shih-Hung; Chiou, Guey-Fa; Hsu, Wen-Lian – Educational Technology & Society, 2005
This paper presents a new model for simulating procedural knowledge in the problem solving process with our ontological system, InfoMap. The method divides procedural knowledge into two parts: process control and action performer. By adopting InfoMap, we hope to help teachers construct curricula (declarative knowledge) and teaching strategies by…
Descriptors: Problem Solving, Teaching Methods, Models, Educational Games
