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Title: Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student’s Understanding of a Topic
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Author(s): G. Pankaj Jain, Varadraj P. Gurupur, Jennifer L. Schroeder, and Eileen D. Faulkenberry
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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.

File: PDF 文档 jain2014.pdf
Relevant Principles (APA): 原理19 要实现对学生的技能、知识和能力的良好评价,就 应遵循特定的对评价过程的要求,该过程应根植于 心理科学、在质量和公平方面具有明确定义的标准
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