Chuang-Kai Chiou

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In context-aware ubiquitous learning environment, finding out an optimal learning path for each student in real time to maximize the learning performance is important. In addition, many studies also indicated and confirmed that personalization is effective in improving the learning efficacy of students. Although the issue of personalized navigation support(More)
Situating students to learn from the real world has been recognized as an important and challenging issue. However, in a real-world learning environment, there are usually many physical constraints that affect the learning performance of students, such as the total learning time, the limitation of the number of students who can visit a learning target, and(More)
Several algorithms have been proposed for association rule mining, such as Apriori and FP Growth. In these algorithms, a minimum support should be decided for mining large itemsets. However, it is usually the case that several minimum supports should be used for repeated mining to find the satisfied collection of association rules. To cope with this(More)
The learning efficiency in a traditional classroom is easily influenced by three factors: the learning environment, the instruction mode and the conditions of students. For improving the learning efficiency, an intelligent classroom management system with context-awareness based on the wireless sensor network technology is proposed and implemented in this(More)
In the literatures, hash-based association rule mining algorithms are more efficient than Apriori-based algorithms, since they employ hash functions to generate candidate itemsets efficiently. However, when the dataset is updated, the whole hash table needs to be reconstructed. In this paper, we propose an incremental mining algorithm based on minimal(More)
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