Education Network Technology Research Articles

Research on the Interactive Technology of 6G Network Online Classroom for Ideological and Political Education Infiltration

Aiming at the application of 6G network technology in online classroom interaction of ideological and political education, this paper first analyzes the challenges faced by online classroom interaction of ideological and political education; and discusses the advantages of 6G network technology in education and its role in improving online classroom interaction. Through literature research and case analysis, this study studies the application and realization of 6G network technology in online classroom interaction of ideological and political education. Then, this paper puts forward a framework of 6G network classroom interaction technology for ideological and political education. This mode can provide more diverse interactive ways for online ideological and political classroom, thus enhancing students' interest and enhancing teaching effect. Finally, this study puts forward the future research direction of 6G network classroom interaction technology. This paper can provide useful reference for the development of interactive technology in online classroom of ideological and political education.

AI through the eyes of university students: benefits, concerns and possible challenges

The article discusses the issues related to the application of artificial intelligence (AI) within the environment of the senior bachelor's and master's degree students of different universities. To that end the method of questionnaire was implemented based on the online test constructor Testmoz, which comprised 10 questions of both closed and open-ended types. The observations and conclusions presented are based on the results of analyzing students' perceptions and usage patterns of neural network-based applications, in particular in English studies. Assignments on developing students’ competences in mastering a foreign language are exemplified. The study shows how often, to what extent and which tools they rely on, how much AI affects students' learning and performance, and what their concerns are in terms of its increasing integration into education. The peculiar features of chatbots as the most popular “assistants” in learning are considered, with a special emphasis on Chat GPT (Generative Pre-trained Transformer); according to students’ evidence, it is in high demand in carrying out various academic and research tasks. In addition, the study analyzes the challenges that teachers are facing and those that will have to address, such as ensuring fair assessment, addressing issues of trust and credibility, and adapting to the changing educational landscape heavily influenced by AI. The results of the study emphasize the need for a balanced approach to the use of neural network technology in education, taking into careful consideration ethics, data privacy, and the importance of maintaining critical thinking skills.

RETRACTED: Multimedia network teaching platform and its application in mechanical design

The comprehensive application and development of multimedia technology and network technology in education is a research hotspot for a long time now and for a long time. Mechanical design is an important technical basic course for mechanical and related majors in colleges and universities. It is practical and comprehensive. This paper takes mechanical design teaching as the starting point, designs and develops a multimedia network education platform that meets the mechanical design teaching of colleges and universities. The platform fully utilizes the comprehensive advantages of streaming media technology, WebRTC technology and Web mining technology to enable teachers and students to attend classes and communicate remotely online. Through the comparative experiments on the classes of Chengnan College, the results show that with the platform teaching, the students' motivation for learning in the mechanical design discipline is enhanced, the learning investment is increased, and the teachers are satisfied with the classroom atmosphere and teaching effects. This shows that the platform can improve the teaching effect.

Technology forecasting in the National Research and Education Network technology domain using context sensitive Data Fusion

Using inductive reasoning this paper develops a framework for the Structural Equation Modeling based context sensitive Data Fusion of technology indicators in order to produce Technology Forecasting output metrics. Data Fusion is a formal framework that defines tools, as well as the application of these tools, for the unification of data originating from diverse sources. Context sensitive Data Fusion techniques refine the generated knowledge using the characteristics of exogenous context related variables, which in the proposed framework entails non-technology related metrics. Structural Equation Modeling, which is a statistical technique capable of evaluating complex hierarchical dependencies between latent and observed constructs, has been shown to be effective in implementing context sensitive Data Fusion. For illustrative purposes an example model instantiation of the proposed framework is constructed for the case of the National Research and Education Network technology domain using knowledge gained through action research in the South African National Research Network, hypotheses from peer-reviewed literature and insights from the Trans-European Research and Education Network Association's annual compendiums for National Research and Education Network infrastructure and services trends. This example model instantiation hypothesizes that a National Research and Education Network's infrastructure and advanced services capabilities are positively related to one another, as well as to the contextual influence it experiences through government control. Also, positive relationships are hypothesized between a National Research and Education Network's infrastructure and advanced services capabilities and its usage, which is defined as the technology forecasting output metric of interest for this example. Data from the 2011 Trans-European Research and Education Network Association compendium is used in the Partial Least Square regression analysis of the example model instantiation, which confirms all hypothesized relationships, except the postulation that a National Research and Education Network's infrastructure and advanced services capabilities are positively related. This latter finding is explained by observing the prevalence of technology leapfrogging in the National Research and Education Network global community.

Eye State Recognition Algorithm GAHMM of Web-based Learning Fatigue

With the increasingly deeper application of multimedia and network technology in education, the proportion of web-based learning presents a trend of continuous growth in people’s daily study, and the web-based learners tend to have learning fatigue during their learning process of distance education. Under the 4 learning states of normal study, fatigue and doubt, the eye opening degrees of web-based learner have certain difference. Through preprocessing of the color images of web-based learners’ eye state, the 2-dimensional kernel function is selected to build 48 optimal filters and obtain 48 eigenvalues, and then, through HMM, training is conducted to identify the eye state and feature classification. The experiment results show that this algorithm has very high identification ability of the web-based learning fatigue