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Intelligent Database Systems Lab
Presenter: NENG-KAI, HONG
Authors: G. PANKAJ JAIN, VARADRAJ P. GURUPUR, JENNIFER L.
SCHROEDER, AND EILEEN D. FAULKENBERRY
2014, IEEE
Artificial Intelligence-Based Student LearningEvaluation: A Concept Map-Based Approach forAnalyzing a Student’s Understanding of a Topic
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Intelligent Database Systems Lab
Outlines
MotivationObjectivesMethodologyExperimentsConclusionsComments
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Intelligent Database Systems Lab
Motivation
• Traditional method of concept map can only be
used to measure what the student knows about
a subject.
• Concepts developed by students should be more
measurable and comparable.
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Intelligent Database Systems Lab
Objectives
• Development of a comparative analysis using
probability distribution to compare concept
maps developed by students.
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Methodology
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Intelligent Database Systems Lab
Experiment
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Intelligent Database Systems Lab
Experiment
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Intelligent Database Systems Lab
Conclusions• Use of AISLE considerably reduces the time involved
in assessing a student’s understanding of a topic in study for the instructor.
• The method used to assess concept maps does not work very well when the concept maps submittedby the students are not hierarchical in nature
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Intelligent Database Systems Lab
Comments• Applications– Concept maps, evalution, probability distributions
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