基于智能体的电子学习系统的改进项目反应理论(IRT)模型和k均值聚类

B. Lakshman, J. V. Wijekulasooriya, M. Sandirigama
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引用次数: 0

摘要

中北部省是斯里兰卡最大的省份。但普通水平数学普通证书考试(gce - O/L)成绩不佳是该省的一个严重问题。(表01)许多报告,包括来自国家评估测试服务部的报告显示,超过50%的学生在普通教育证书考试中数学科目的成绩很差(W)。因此,进行了多次调查,找到了这种情况的根源,并提出了克服这种情况的补救措施。从这些调查中可以看出,小学数学概念知识贫乏是造成这种情况的主要因素之一。因此,提出了基于Agent的E学习系统作为补救措施。在任何E学习系统中,进行心理测量和数据聚类都是非常重要的。本文给出了适用于E学习的新项目反应理论模型,以及利用k均值算法从新IRT模型中计算出的聚类概率值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modified Item Response Theory (IRT) model and k means clustering for agent based E learning system
North Central Province is the largest province in Sri Lanka. But gaining poor results for Mathematics in General Certificate in ordinary level (G.C.E. - O/L) is an intense problem in the province. (Table 01) Many reports including reports from the Department of Examination national Evaluation Testing Services show that more than fifty percent of students have obtained poor (W) grade for the mathematics subject in the G.C.E. - O/L Examination. Therefore, it is conducted several surveys to find the root courses for this situation and suggested a remedy to overcome the situation. From these surveys, it is revealed that poor knowledge of primary level mathematics concepts is one of leading factor for this situation. So, it is suggested an Agent based E learning system as a remedy. In any E learning system, taking psychometric measurements and data clustering are very important. In this paper, it is shown the new Item response Theory model that suit for E learning and clustering probability values that calculated from new IRT model using k means algorithm.
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