Data mining for providing a personalized learning path in creativity:

Intelligent Database Systems Lab

Presenter : CHANG, SHIH-JIE

Authors : Chun Fu Lin, Yu-chu Yeh, Yu Hsin Hung, Ray I Chang

2013.CE.

Data mining for providing a personalized learning path in creativity:An application of decision trees

Intelligent Database Systems Lab

Outlines

MotivationObjectivesMethodologyExperimentsConclusionsComments

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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.

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Objectives

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

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The framework of PCLS

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Methodology

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Methodology- Agent structures

Feature selection Decision tree algorithm

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Methodology - Creativity Game Agent

(1)The living room(2)The kitchen (3) The bathroom

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Methodology – Collecting data

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Experiments – Gain ratio result

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Experiments-Analyzing the decision tree model

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Experiments

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Experiments

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Conclusions– The system helps learners to choose their optimal

learning path and helps teachers to understand the cognitive process of learners, to allow them to adapt their teaching behavior efficiently.

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Comments• Advantages

– To enhance the learning effectiveness and learning efficiency.

• Applications– Teaching and learning strategies.