Cluster approach to criteria evaluation of the quality of a student’s educational outcome

N. I. Pak, M. M. Klunnikova
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引用次数: 0

Abstract

Problem and goal . The issues of criteria-based evaluation of the student's educational results remain relevant for the modern theory and practice of education. As a rule, measures to monitor educational results and resources in educational institutions are carried out by expert, manual, non-automated methods. In accordance with the directions of digital transformation of education, it is necessary to create a technological assessment system that meets the requirements of modern society, subject to automation and intellectualization. The purpose of the work is to substantiate a new model of criteria-based assessment of the quality of the educational result, based on the mathematical methods of the theory of clustering and pattern recognition and allowing to automate the procedures for assessing the quality of educational objects, resources, educational and personal achievements of students. Methodology. The quality of an educational result or resource is determined by criteria indicators, which can be represented as features of the evaluated object using the information vector. By clustering the set of acceptable objects into three classes - with low, medium and high quality - it is possible to evaluate an object by its belonging to one of these classes. Clustering is carried out on the basis of a mining algorithm, the metric of city blocks is taken as a measure of the similarity of objects. Results. A program has been developed that consists of a source data module, a clustering module, and a recognition and training module. The model results of the program correlate with traditional rating assessments, in which the quality of the object is determined by a point scale. The obtained test results confirm the validity of the recognition algorithm and the correctness of the software product. Conclusion. Thus, the proposed model based on clustering and the recognition method showed the possibility of automated assessment of the quality of educational results of trainees and educational resources.
学生教育成果质量标准评估的聚类方法
问题和目标。以标准为基础的学生教育成果评价问题与现代教育理论和实践息息相关。通常,监测教育机构的教育成果和资源的措施是通过专家、人工、非自动化的方法进行的。根据教育数字化转型的方向,有必要创建一个符合现代社会要求、服从自动化和智能化的技术评估系统。本研究的目的是在聚类和模式识别理论的数学方法的基础上,建立一个基于标准的教育结果质量评估的新模型,并允许自动化评估教育对象、资源、学生的教育和个人成就的质量的程序。方法。教育结果或资源的质量是由标准指标决定的,这些指标可以用信息向量表示为被评估对象的特征。通过将一组可接受的对象聚类为三个类别——低、中、高质量——可以通过对象是否属于这些类别之一来评估对象。在挖掘算法的基础上进行聚类,以城市街区的度量作为对象相似度的度量。结果。开发了一个由源数据模块、聚类模块和识别与训练模块组成的程序。该程序的模型结果与传统的评级评估相关联,其中对象的质量由点尺度确定。得到的测试结果验证了识别算法的有效性和软件产品的正确性。结论。因此,本文提出的基于聚类和识别方法的模型为学员的教育成果和教育资源的质量自动评估提供了可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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