Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine

Q1 Social Sciences

International Journal of Emerging Technologies in Learning Pub Date : 2023-06-21 DOI:10.3991/ijet.v18i12.39697

Jianmeng Ou, Dongdong Lin, Zhitao Zheng

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引用次数: 0

Abstract

Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.

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基于支持向量机的高校在线实验教学质量综合评价

受全球新冠肺炎疫情影响，我国多所高校不得不开展网上实验教学。在线实验教学可以充分实现实验教学数据的保留，实验教学的最大化共享，通过良好的网络存储设备，提高教师通过移动方式完成实验教学的能力。科学系统地评价网上实验教学质量，可以促进网上教学活动的不断改进，充分发挥教师的教学积极性，提高大学生的综合培养质量，使网上实验教学成为实验教学改革的新趋势。本研究在现有文献的基础上，分析了影响在线实验教学质量的因素，提出了在线实验教学的评价指标，并运用支持向量机训练评价系统建立了高校在线实验教学品质的评价模型。实验结果表明，提出的在线实验教学质量评价指标较为完善，具有良好的适用性和推广性。基于支持向量机的方法提高了高校在线实验教学质量的评价效果。输出评估结果与实际评估结果高度一致。网上实验教学质量评价结果非常客观全面。结论对在线实验教学行为分析、改进在线实验教学质量评价指标、减少在线教学质量评价误差、提高在线教学质量评估效果具有重要参考价值。

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来源期刊

International Journal of Emerging Technologies in Learning EDUCATION & EDUCATIONAL RESEARCH-

自引率

0.00%

发文量

352

审稿时长

12 weeks

期刊介绍： This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of technology enhanced learning. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Software / Distributed Systems -Knowledge Management -Semantic Web -MashUp Technologies -Platforms and Content Authoring -New Learning Models and Applications -Pedagogical and Psychological Issues -Trust / Security -Internet Applications -Networked Tools -Mobile / wireless -Electronics -Visualisation -Bio- / Neuroinformatics -Language /Speech -Collaboration Tools / Collaborative Networks