Artificial Intelligence-Based Student Learning
Evaluation: A Concept Map-Based Approach for
Analyzing a Student’s Understanding of a Topic
Presenter: NENG-KAI, HONG
Authors: G. PANKAJ JAIN, VARADRAJ P. GURUPUR, JENNIFER L.
SCHROEDER, AND EILEEN D. FAULKENBERRY
2014, IEEE
Intelligent Database Systems Lab
Outlines
 Motivation
 Objectives
 Methodology
 Experiments
 Conclusions
 Comments
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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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Objectives
• Development of a comparative analysis using
probability distribution to compare concept
maps developed by students.
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Methodology
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Methodology
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Methodology
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Methodology
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Methodology
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Methodology
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Methodology
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Methodology
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Experiment
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Experiment
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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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Comments
• Applications
– Concept maps, evalution, probability distributions
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