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Data mining for providing a personalized learning path in creativity:

Data mining for providing a personalized learning path in creativity: An application of decision trees. Presenter : CHANG, SHIH-JIE Authors : Chun Fu Lin , Yu- chu Yeh , Yu Hsin Hung, Ray I Chang 2013.CE. Outlines. Motivation Objectives Methodology Experiments Conclusions

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Data mining for providing a personalized learning path in creativity:

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  1. Data mining for providing a personalized learning path in creativity: An application of decision trees Presenter : CHANG, SHIH-JIE Authors : Chun Fu Lin, Yu-chuYeh, Yu Hsin Hung, Ray I Chang 2013.CE.

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments

  3. Motivation  Traditional Web-based learning systems neglect the customization of learning materials to the learners’ needs. Routine learning materials and paths might not meet the learners’ needs.

  4. Objectives • Developing a personalized creativity learning system (PCLS) to provide adaptive learning paths for learners with varied backgrounds and personal traits.

  5. The framework of PCLS  

  6. Methodology

  7. Methodology- Agent structures     Feature selection Decision tree algorithm

  8. Methodology - Creativity Game Agent (1)The living room(2)The kitchen (3) The bathroom

  9. Methodology – Collecting data

  10. Experiments – Gain ratio result

  11. Experiments-Analyzing the decision tree model

  12. Experiments

  13. Experiments

  14. Conclusions • The system helps learners to choose their optimal learning pathand helps teachers to understand the cognitive process of learners, to allow them to adapt their teaching behavior efficiently.

  15. Comments • Advantages • To enhance the learning effectiveness and learning efficiency. • Applications • Teaching and learning strategies.

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