自适应电子评估教学系统中确定问题难度的模糊推理模型

Oscar M. Salazar, D. Ovalle, F. de la Prieta
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引用次数: 0

摘要

电子评估是一个至关重要的过程,它可以验证学生之前获得的知识状态,以及监控他/她的进步和/或验证他/她在学习过程结束时获得的知识水平。本文的目的是提出一个模糊推理模型,用于确定适应性教学系统中电子评估问题的难度水平,从而允许整合和分析与学生认知概况适当匹配的问题的关键特征,以进行适当的问题选择。为了验证该模型,建立了一个原型,并通过案例研究进行了测试。研究结果证明了所提出的模糊推理模型在自适应电子评估教学系统中的有效性。
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Fuzzy Inference Model for Determining the Question Difficulty Level within Adaptive e-Assessment Instructional Systems
The e-assessment is a crucial process that allows to validate the previous state of knowledge acquired by the student, as well as to monitor his/her progress and/or validate the level of knowledge obtained by him/her at the end of the learning process. The aim of this paper is to propose a fuzzy inference model for determining the difficulty level of e-assessment questions within adaptive instructional systems, thus allowing to integrate and analyze key features of the questions properly matching with the student's cognitive profile for an appropriate question selection. In order to validate the model a prototype was built and tested through a case study. Results obtained demonstrate the effectiveness of the proposed fuzzy inference model for adaptive e-assessment instructional systems.
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