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Situational Cognition of College English Education Based on Image Block Gain Optimization in Pseudo-haze State

机译:基于伪雾状态下图像块增益优化的大学英语教学情境认知

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Situational cognition can help students to construct their knowledge to a great extent. In order to solve the problem of lack of situational cognition in College English teaching, this paper studies the validity of students' situational cognition in College English teaching based on the method of image block gain optimization. First, this paper analyses the general situation of situational cognition capacity in College English teaching in China at present, and puts forward the function of device image in constructing situational cognitive competence in teaching. Then, it divides device image into blocks under pseudo-haze conditions, and proposes the optimization method of block gain. Finally, on the basis of block gain, it makes an empirical test of situational cognitive competence in College English teaching. The empirical results show that image block gain optimization can effectively improve the construction of situational cognition capacity in College English teaching. With the help of this study, some new and useful ideas can be traced for the development of computer science and college English teaching, and also stimulate the further improvement of College English education in China.
机译:情境认知可以在很大程度上帮助学生建立知识。为了解决大学英语教学中情境认知不足的问题,本文基于图像块增益优化的方法,研究了学生情境认知在大学英语教学中的有效性。首先,本文分析了目前我国大学英语教学中情境认知能力的概况,提出了设备形象在教学中建构情境认知能力的作用。然后,在伪霾条件下将设备图像划分为块,并提出了块增益的优化方法。最后,在块增益的基础上,对大学英语教学中的情境认知能力进行了实证检验。实验结果表明,图像块增益优化可以有效地改善大学英语教学中情境认知能力的建设。借助这项研究,可以为计算机科学和大学英语教学的发展寻找一些新的有用的思路,并刺激中国大学英语教育的进一步改善。

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