Title

Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach For Analyzing A Student'S Understanding Of A Topic

Keywords

Concept maps; Evaluation; Probability distributions; XML parsers

Abstract

In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of the concepts identified in the concept map developed by the student. The evaluation of a student's understanding of the topic is assessed by analyzing the curve of the graph generated by this tool. This technique makes extensive use of XML parsing to perform the required evaluation. The tool was successfully tested with students from two undergraduate courses and the results of testing are described in this paper.

Publication Date

7-1-2014

Publication Title

IEEE Transactions on Learning Technologies

Volume

7

Issue

3

Number of Pages

267-279

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TLT.2014.2330297

Socpus ID

84907525431 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84907525431

This document is currently not available here.

Share

COinS