Evaluating Student Learning Using Concept Maps And Markov Chains

Keywords

Artificial intelligence; Concept maps; Finite; Markov chains; Student evaluation; Transition matrix; XML parsing

Abstract

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.

Publication Date

5-1-2015

Publication Title

Expert Systems with Applications

Volume

42

Issue

7

Number of Pages

3306-3314

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.eswa.2014.12.016

Socpus ID

84920973912 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84920973912

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