The Research about the Role and influence of Teacher emotional support in Online Learning Environmen

来源 :计算机教育 | 被引量 : 0次 | 上传用户:liu55166
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
At the beginning of 2020, the “COVID-19”came out. Affected by the outbreaks, the universities have to carry out online teaching. Online learning provides students with full freedom and personalized learning space, but at the same time, it also brings problems such as weak feelings between teachers and students and lack of learning experience. To solve these problems, this paper adopts the methods of questionnaire survey, experimental control and behavioral modeling. This paper studies how teachers\' emotional support behavior affects students\' learning process and learning emotion in online learning environment, and proposes that teachers\' emotional support behavior is appealed and desired by students. Positive teachers\' emotional support behavior can promote students\' learning process and improve students\' learning emotion.
其他文献
With the emergence of massive online courses, how to evaluate the quality of courses with different qualities to improve the discrimination between courses and recommend personalized online course learning resources for learners needs to be evaluated from
As major contemporary scientific, technological, economic, and social issues are highly comprehensive and interdisciplinary, society has entered a period of systematization and integration. The traditional education model of “discipline-centered” makes th
Taking the programming course as an example, a comprehensive solution for individualized and precise teaching has been proposed. Firstly, graded teaching strategy is performed. The students are divided into three groups according to their base of learning
股指价格时间序列受到长期和短期不同因素的影响,且具有非平稳、非线性等特点,传统计量模型的预测精度较低.为提高预测精度,一些研究将人工神经网络模型用于金融时间序列预测,取得了比传统计量模型更好的效果.提出了一种融合了HP滤波(Hodrick-Prescott Filter)和LSTM神经网络模型的股指价格预测模型,模型使用HP滤波将股指价格时间序列分解为长期趋势和短期波动,利用LSTM神经网络模型分别学习长期趋势和短期波动序列的特征,并分别进行长期趋势和短期波动预测,将预测结果融合得出股指价格预测结果.实验
The theme of CEISEE 2021 is“Software Engineering Education in the Post-Epidemic Internet Era: New Changes, New Technology, New Economy, and New Features”, especially the blooming of artificial intelligence, big data, cloud computing, block chain, IoT etc.
期刊
The practical teaching management system is an important factor to ensure the quality of teaching. The training of systematic thinking needs a systematic teaching system, and a systematic process is a gradual process and a standardized process. This paper
The concept of “New Engineering” has put forward new challenges to the talents cultivation of universities. Due to some problems of the traditional Software Engineering curriculum, e.g. separated design at undergraduate-level and graduate-level courses, p
In view of the mechanism and quality problems in the software ability training of computer majors in colleges and universities, as well as the engineering ability and innovation ability training results can not effectively meet the needs of society, this
The spread and innovative application of MOOC in China has rapidly triggered a profound revolution in the curriculum construction and teaching reform of universities, promoting significant results in teaching and talent cultivation. Based on the practice
In recent years, the IT industry in China has developed rapidly and made remarkable achievements. However, there is still a big gap between China and foreign countries in the core fields of information technology, such as system hardware and software plat