scholarly journals An Empirical Study on Innovation of College Blended Teaching under Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qianqian Xie ◽  
Sang-Bing Tsai
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Learning Experience ◽  
Information Age ◽  
Big Data Analysis ◽  
Teaching Model ◽  
Application Technology ◽  
Teaching Mode ◽  
Teaching Content ◽  
Blended Teaching

With the advent of the information age, the way people obtain information has changed profoundly. The wave of informationization in higher education has also come with it, and the teaching mode, teaching content, and teaching form are constantly innovated. How to organically integrate information technology into education teaching in order to care for learners’ learning experience and promote the cultivation of new talents is an issue that current educational technology researchers need to pay great attention to. This paper first builds a complete blended teaching model of public English for higher education, but its application effect needs to be further examined. This paper is an investigation in the background of the current era to build a blended teaching model. Based on the continuous development of the era, the ideology and application technology of this field will keep upgrading, so the teaching model also needs to be changed and updated according to the characteristics of the development of the era. The investigation of mixed teaching modes is not permanent. The investigation of the mixed teaching mode is not permanent. At present, only a few courses apply the blended teaching mode. On the basis of the continuous updating of teaching concepts and the latest technologies, it is foreseen that the focus of subsequent investigations will be on the individualized development of the blended teaching mode.

scholarly journals A News Big Data Analysis of Issues in Higher Education in Korea amid the COVID-19 Pandemic

2021 ◽  
Vol 13 (13) ◽  
pp. 7347
Author(s):  
Jangwan Ko ◽  
Seungsu Paek ◽  
Seoyoon Park ◽  
Jiwoo Park
Keyword(s):  
Higher Education ◽  
Big Data ◽  
Data Analysis ◽  
College Education ◽  
Big Data Analysis ◽  
Second Phase ◽  
Public Attention ◽  
Job Market ◽  
Media Reports ◽  
The Government

This paper examines the main issues regarding higher education in Korea—where college education experienced minimal interruptions—during the COVID-19 pandemic through a big data analysis of news articles. By analyzing policy responses from the government and colleges and examining prominent discourses on higher education, it provides a context for discussing the implications of COVID-19 on education policy and what the post-pandemic era would bring. To this end, we utilized BIgKinds, a big data research solution for news articles offered by the Korea Press Foundation, to select a total of 2636 media reports and conducted Topic Modelling based on LDA algorithms using NetMiner. The analyses are split into three distinct periods of COVID-19 spread in the country. Some notable topics from the first phase are remote class, tuition refund, returning Chinese international students, and normalization of college education. Preparations for the College Scholastic Ability Test (CSAT), contact and contactless classes, preparations for early admissions, and supporting job market candidates are extracted for the second phase. For the third phase, the extracted topics include CSAT and college-specific exams, quarantine on campus, social relations on campus, and support for job market candidates. The results confirmed widespread public attention to the relevant issues but also showed empirically that the measures taken by the government and college administrations to combat COVID-19 had limited visibility among media reports. It is important to note that timely and appropriate responses from the government and colleges have enabled continuation of higher education in some capacity during the pandemic. In addition to the media’s role in reporting issues of public interest, there is also a need for continued research and discussion on higher education amid COVID-19 to help effect actual results from various policy efforts.

Research on the Data Driven Practice Teaching Mode: Take the Didi Data Set as Example

2021 ◽  
Vol 105 ◽  
pp. 348-355
Author(s):  
Hou Xiang Liu ◽  
Sheng Han Zhou ◽  
Bang Chen ◽  
Chao Fan Wei ◽  
Wen Bing Chang ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Teaching Method ◽  
Rapid Development ◽  
Big Data Analysis ◽  
Theoretical Knowledge ◽  
Data Set ◽  
Teaching Mode ◽  
Practice Teaching ◽  
Practical Teaching

The paper proposed a practice teaching mode by making analysis on Didi data set. There are more and more universities have provided the big data analysis courses with the rapid development and wide application of big data analysis technology. The theoretical knowledge of big data analysis is professional and hard to understand. That may reduce students' interest in learning and learning motivation. And the practice teaching plays an important role between theory learning and application. This paper first introduces the theoretical teaching part of the course, and the theoretical methods involved in the course. Then the practice teaching content of Didi data analysis case was briefly described. And the study selects the related evaluation index to evaluate the teaching effect through questionnaire survey and verify the effectiveness of teaching method. The results show that 78% of students think that practical teaching can greatly improve students' interest in learning, 89% of students think that practical teaching can help them learn theoretical knowledge, 89% of students have basically mastered the method of big data analysis technology introduced in the course, 90% of students think that the teaching method proposed in this paper can greatly improve students' practical ability. The teaching mode is effective, which can improve the learning effect and practical ability of students in data analysis, so as to improve the teaching effect.

scholarly journals Research on the Innovative Strategy of Blended Teaching in Network Marketing in the Era of Big Data

2021 ◽  
Vol 5 (11) ◽  
pp. 83-88
Author(s):  
Lei Liang ◽  
Zhiyong Fan
Keyword(s):  
Big Data ◽  
Independent Learning ◽  
Teaching Model ◽  
Network Marketing ◽  
Innovative Strategy ◽  
Model Combining ◽  
Hybrid Teaching ◽  
Core Literacy ◽  
Big Data Technology ◽  
Blended Teaching

Network Marketing is a practical professional compulsory course. With the advent of big data technology, a hybrid teaching model combining online and offline has emerged. Based on the analysis of the advantages of using a hybrid teaching model in Internet Marketing, this article comprehensively considers a variety of factors and put forward the innovative strategy of blended teaching in Network Marketing in the era of big data. This may provide new paths and methods for enhancing teaching effects, cultivating students’ independent learning, and improving core literacy.

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