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Evaluating student learning using concept maps and Markov chains
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DOI：10.1016/j.eswa.2014.12.016.png)
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Abstract
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In this paper we describe a tool that can be effectively used to evaluate student learning outcomes using concept maps and Markov chain analysis. The main purpose of this tool is to advance the use of artificial intelligence techniques by using concept maps and Markov chains in evaluating a student's understanding of a particular topic of study using concept maps. The method used in the tool makes use of XML parsing to perform the required evaluation. For the purpose of experimenting this tool we have taken into consideration concept maps developed by students enrolled in two different courses in Computer Science. The result of this experimentation is also discussed. (C) 2014 Elsevier Ltd. All rights reserved.
Keywords:
Concept maps
Student evaluation
Artificial intelligence
Finite Markov chains
Transition matrix
XML parsing
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