在线教育与传统教育:用Shapley加法解释分析学生在计算机科学方面的表现

IF 2.1 Q1 EDUCATION & EDUCATIONAL RESEARCH

Informatics in Education Pub Date : 2023-01-02 DOI:10.15388/infedu.2023.23

M. Charytanowicz

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引用次数: 0

摘要

如今，信息通信技术的快速发展带来了更加灵活的形式，突破了传统教学方法的界限。本文分析了新冠肺炎大流行迫使在线教学与传统教育方式的比较。在这方面，我们评估了2019-2022年卢布林工业大学计算机科学工程学位学生在面对面、在线和混合模式下的学习表现。使用机器学习模型和Shapley加性解释方法检查了总共1827个最终考试成绩。结果显示，使用在线和混合模式的学生在期末考试中的成绩平均有所提高，但差异不超过满分的10%。此外，学生的工作对最终考试成绩的影响比学习系统和他们的个人特征要大得多。

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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Online Education vs Traditional Education: Analysis of Student Performance in Computer Science using Shapley Additive Explanations

Nowadays, the rapid development of ICT has brought more flexible forms that push the boundaries of classic teaching methodology. This paper is an analysis of online teaching and learning forced by the COVID-19 pandemic, as compared with traditional education approaches. In this regard, we assessed the performance of students studying in the face-to-face, online and hybrid mode for an engineering degree in Computer Science at the Lublin University of Technology during the years 2019-2022. A total of 1827 final test scores were examined using machine learning models and the Shapley additive explanations method. The results show an average increase in performance on final tests scores for students using online and hybrid modes, but the difference did not exceed 10% of the point maximum. Moreover, the students' work had a much higher impact on the final test scores than did the study system and their profile features.

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来源期刊

Informatics in Education EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

6.10

自引率

3.70%

发文量

审稿时长

20 weeks

期刊介绍： INFORMATICS IN EDUCATION publishes original articles about theoretical, experimental and methodological studies in the fields of informatics (computer science) education and educational applications of information technology, ranging from primary to tertiary education. Multidisciplinary research studies that enhance our understanding of how theoretical and technological innovations translate into educational practice are most welcome. We are particularly interested in work at boundaries, both the boundaries of informatics and of education. The topics covered by INFORMATICS IN EDUCATION will range across diverse aspects of informatics (computer science) education research including: empirical studies, including composing different approaches to teach various subjects, studying availability of various concepts at a given age, measuring knowledge transfer and skills developed, addressing gender issues, etc. statistical research on big data related to informatics (computer science) activities including e.g. research on assessment, online teaching, competitions, etc. educational engineering focusing mainly on developing high quality original teaching sequences of different informatics (computer science) topics that offer new, successful ways for knowledge transfer and development of computational thinking machine learning of student''s behavior including the use of information technology to observe students in the learning process and discovering clusters of their working design and evaluation of educational tools that apply information technology in novel ways.