Intelligent Database Systems Lab Presenter: NENG-KAI, HONG Authors: G. PANKAJ JAIN, VARADRAJ P. GURUPUR, JENNIFER L. SCHROEDER, AND EILEEN D. FAULKENBERRY.

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Presentation transcript:

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 Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student’s Understanding of a Topic

Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments 1

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. 2

Intelligent Database Systems Lab Objectives Development of a comparative analysis using probability distribution to compare concept maps developed by students. 3

Intelligent Database Systems Lab Methodology 4

Intelligent Database Systems Lab Methodology 5

Intelligent Database Systems Lab Methodology 6

Intelligent Database Systems Lab Methodology 7

Intelligent Database Systems Lab Methodology 8

Intelligent Database Systems Lab Methodology 9

Intelligent Database Systems Lab Methodology 10

Intelligent Database Systems Lab Methodology 11

Intelligent Database Systems Lab Experiment 12

Intelligent Database Systems Lab Experiment 13

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 14

Intelligent Database Systems Lab Comments Applications – Concept maps, evalution, probability distributions 15