基于数据挖掘的工科研究生英文论文写作课程SPOC教学模式设计

Improving English thesis writing education in Chinese technical universities: A quest for designing a sustainable teaching mode based on data mining

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DOI 10.12208/j.ssr.20250110
刊名
Modern Social Science Research
年,卷(期) 2025, 5(3)
作者
作者单位

西安理工大学 陕西西安

摘要
构建“英语语言”与“专业技术”两个知识体系之间相互支撑的闭环教学模式,是“新工科”时代下工科研究生英文论文写作课程提升教学质量与丰富教学层次的重要手段之一。本文以基于KPCA的科技文本汉译英翻译质量分类与评价方法为主要工具,设计了使得数据挖掘的理性思维能够服务于英文写作这一感性过程的知识反馈回路,从而在原“专业+志趣+语言”的开环SPOC教学模式基础上,营造新的闭环SPOC教学模式。同时,探讨了在新的教学模式中,任课教师所面临的主要挑战。
Abstract
Constructing a closed-loop teaching model that supports each other between the two knowledge systems of “English language” and "professional technology" is one of the important means to improve the teaching quality and enhance the teaching level of English thesis writing courses for engineering graduate students in the era of “new engineering”. This article uses KPCA based technology text Chinese to English translation quality classification and evaluation method as the main tool, and designs a knowledge feedback loop that enables rational thinking of data mining to serve the emotional process of English writing. Based on the original "professional, interest and language" open-loop SPOC teaching model, a new closed-loop SPOC teaching model is created. At the same time, the main challenges faced by teachers in the new teaching model were discussed.
关键词
英文论文写作;工科研究生;SPOC教学模式;数据挖掘
KeyWord
English thesis writing; Engineering graduate students; SPOC teaching model; Data mining
基金项目
页码 107-110
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樊迪*. 基于数据挖掘的工科研究生英文论文写作课程SPOC教学模式设计 [J]. 现代社会科学研究. 2025; 5; (3). 107 - 110.

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