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In this article, we describe a tool coined as Artificial Intelligence-Based Student Learning Evaluation Tool (AISLE). The main purpose of AISLE is to improve the use of artificial intelligence techniques in evaluating a student’s understanding of a particular topic of study using concept maps. Using this tool, we calculate the probability distribution of the concepts identified in the concept map developed by the student. This tool evaluates a student’s understanding of the topic 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.
Gyanchand Jain, Varadraj Gurupur, Jennifer Schroeder, Eileen Faulkenberry, "Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student’s Understanding of a Topic", IEEE Transactions on Learning Technologies, , no. 1, pp. 1, PrePrints PrePrints, doi:10.1109/TLT.2014.2330297
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