Prognostic model for assessing the success of subject learning in conditions of digitalization of education

M. Noskov, Yu. V. Vaynshteyn, Marina V. Somova, I. M. Fedotova
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引用次数: 1

Abstract

Problem statement. One of the approaches to solving the problem of predicting the academic performance of students is displayed. Unlike existing studies in this area, which are mainly aimed at predicting the effectiveness of graduation, that is, based on the results of intermediate certifications that allow us to assess the chances of students to successfully graduate from a university, the results of this study are aimed at predicting the success of education in the early stages of the educational process. Methodology. A feature and novelty of the proposed prognostic model is the forecasting of student performance based on the Markov model, the data sources of which are universal predictors of an e-learning course that determine the success of subject education based on the personal characteristics of the student. Results. The authors present a description of a predictive model for assessing the success of subject education in the context of digitalization of education, reveal their experience of its approbation for students of the Siberian Federal University in the field of study “Informatics and Computer Engineering” and the results of a qualitative assessment of the model. Conclusion. The prospects for building a digital service for predicting the academic performance of students in the electronic information and educational environment of the university based on the results of the study are stated.
教育数字化条件下评估学科学习成功与否的预测模型
问题陈述。展示了解决学生学习成绩预测问题的方法之一。这一领域的现有研究主要旨在预测毕业的有效性,也就是说,基于中级证书的结果,我们可以评估学生成功从大学毕业的机会,与此不同,这项研究的结果旨在预测教育过程早期阶段的教育成功。方法论所提出的预测模型的一个特点和新颖性是基于马尔可夫模型对学生表现的预测,马尔可夫模型的数据源是电子学习课程的通用预测因子,根据学生的个人特征决定学科教育的成功与否。后果作者介绍了在教育数字化背景下评估学科教育成功的预测模型,揭示了他们在“信息学和计算机工程”研究领域对西伯利亚联邦大学学生认可的经验,以及对该模型的定性评估结果。结论根据研究结果,展望了在大学的电子信息和教育环境中建立预测学生学习成绩的数字服务的前景。
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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