The Effect of Online and Offline Sports Safety Education combined with MOOC Platforms in Physical Education Teaching in Colleges and Universities

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI:10.12694/scpe.v24i3.2285

Yuan Gao

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引用次数: 0

Abstract

In light of Internet+, how to make network technology better serve the educational cause needs more exploration. The online and offline hybrid education model that integrates MOOC is a new attempt. The sports safety of college students is the premise for the smooth development of sports activities. Therefore, a mixed teaching mode of sports safety combined with MOOC is designed to evaluate the teaching effect. However, under this teaching mode, the commonly used teaching effect evaluation methods cannot adhere to formative evaluation standards. Consequently, to better evaluate the MOOC teaching mode, a model for evaluating instructional effects based on RF mixed teaching mode is constructed. Aiming at the defects of RF in data processing, a genetic algorithm and particle swarm algorithm are used to optimize random forest. The outcomes demonstrate that the enhanced PSO-RF evaluation model has a 98.68% accuracy rate, which is 5.44% and 3.49% higher than the RF and GA-RF model respectively. Therefore, the enhanced PSO-RF-based teaching effect assessment model can better assess the mixed teaching mode in sports safety, meeting the evaluation requirements for students’ learning effects.

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线上线下结合MOOC平台的体育安全教育在高校体育教学中的效果

在互联网+的背景下，如何让网络技术更好地服务于教育事业需要更多的探索。融合MOOC的线上线下混合教育模式是一种新的尝试。大学生体育安全是体育活动顺利开展的前提。为此，设计了一种与MOOC相结合的体育安全混合教学模式，对教学效果进行评价。然而，在这种教学模式下，常用的教学效果评价方法无法坚持形成性评价标准。因此，为了更好地评价MOOC教学模式，构建了基于RF混合教学模式的教学效果评价模型。针对随机森林算法在数据处理上的缺陷，采用遗传算法和粒子群算法对随机森林进行优化。结果表明，改进后的PSO-RF评价模型准确率为98.68%，分别比RF和GA-RF模型高5.44%和3.49%。因此，基于pso - rf的增强型教学效果评价模型能够更好地评价体育安全混合教学模式，满足对学生学习效果的评价要求。

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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来源期刊

Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.00

自引率

0.00%

发文量

期刊介绍： The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.