Opportunities and Challenges of College Mental Health Education from the Perspective of Big Data

This paper explores the opportunities and challenges of college mental health education from the perspective of big data.Firstly,through literature review,the importance of mental health education and the current issues are elucidated.Then,from the perspective of big data,the potential opportunities of big data in college mental health education are analyzed,including data-driven personalized education,real-time monitoring and warning systems,and interdisciplinary research and collaboration.At the same time,the challenges faced by college mental health education under the perspective of big data are also pointed out,such as data privacy and security issues,insufficient data analysis and interpretation capabilities,and inadequate technical facilities and talent support.Lastly,the research content of this paper is summarized,and directions and suggestions for future research are proposed.

The Influence of Social Media on College Choice among Undergraduates Majoring in Big Data Management and Application in China:Taking Guilin University of Electronic Technology as an Example

This study aims to investigate the influence of social media on college choice among undergraduates majoring in Big Data Management and Application in China.The study attempts to reveal how information on social media platforms such as Weibo,WeChat,and Zhihu influences the cognition and choice process of prospective students.By employing an online quantitative survey questionnaire,data were collected from the 2022 and 2023 classes of new students majoring in Big Data Management and Application at Guilin University of Electronic Technology.The aim was to evaluate the role of social media in their college choice process and understand the features and information that most attract prospective students.Social media has become a key factor influencing the college choice decision-making of undergraduates majoring in Big Data Management and Application in China.Students tend to obtain school information through social media platforms and use this information as an important reference in their decision-making process.Higher education institutions should strengthen their social media information dissemination,providing accurate,timely,and attractive information.It is also necessary to ensure effective management of social media platforms,maintain a positive reputation for the school on social media,and increase the interest and trust of prospective students.Simultaneously,educational decision-makers should consider incorporating social media analysis into their recruitment strategies to better attract new student enrollment.This study provides a new perspective for understanding higher education choice behavior in the digital age,particularly by revealing the importance of social media in the educational decision-making process.This has important practical and theoretical implications for higher education institutions,policymakers,and social media platform operators.

Research on the Path of Higher Education Teaching Reform from the Perspective of Big Data

The advent of the digital age has pointed out the direction for the development of higher education.In this paper,the undergraduate course“Science of Interrogation”is taken as the research subject,the challenges of big data teaching reform in universities are analyzed systematically,and concrete measures,such as adhering to the concept of teaching reform under the condition of big data,establishing professional teaching teams,improving the curriculum construction level,emphasizing on being student-centered,and optimizing the reform of the curriculum evaluation system,are proposed to address these challenges.

Big data challenge for monitoring quality in higher education institutions using business intelligence dashboards

As big data becomes an apparent challenge to handle when building a business intelligence(BI)system,there is a motivation to handle this challenging issue in higher education institutions(HEIs).Monitoring quality in HEIs encompasses handling huge amounts of data coming from different sources.This paper reviews big data and analyses the cases from the literature regarding quality assurance(QA)in HEIs.It also outlines a framework that can address the big data challenge in HEIs to handle QA monitoring using BI dashboards and a prototype dashboard is presented in this paper.The dashboard was developed using a utilisation tool to monitor QA in HEIs to provide visual representations of big data.The prototype dashboard enables stakeholders to monitor compliance with QA standards while addressing the big data challenge associated with the substantial volume of data managed by HEIs’QA systems.This paper also outlines how the developed system integrates big data from social media into the monitoring dashboard.

From Big Data to Intelligent Tutoring: Exploring the Application of Big Data Technology in the Ideological and Political Education for College Counselors

This paper explores the application of big data technology in ideological and political education for college counselors.Big data-driven personalized counseling for students,social network analysis,and public opinion monitoring can optimize the efficiency of counselor work.However,there are still challenges concerning data privacy protection,technical support,and training.By scientifically evaluating and addressing these challenges,big data technology is expected to enhance the effectiveness of college counselors and improve the quality of ideological and political education.In the future,with technological advancements,big data technology will become an essential tool for higher education management.

Design and implementation of low-cost geomagnetic field monitoring equipment for high-density deployment

The observation of geomagnetic field variations is an important approach to studying earthquake precursors.Since 1987,the China Earthquake Administration has explored this seismomagnetic relationship.In particular,they studied local magnetic field anomalies over the Chinese mainland for earthquake prediction.Owing to the years of research on the seismomagnetic relationship,earthquake prediction experts have concluded that the compressive magnetic effect,tectonic magnetic effect,electric magnetic fluid effect,and other factors contribute to preearthquake magnetic anomalies.However,this involves a small magnitude of magnetic field changes.It is difficult to relate them to the abnormal changes of the extremely large magnetic field in regions with extreme earthquakes owing to the high cost of professional geomagnetic equipment,thereby limiting large-scale deployment.Moreover,it is difficult to obtain strong magnetic field changes before an earthquake.The Tianjin Earthquake Agency has developed low-cost geomagnetic field observation equipment through the Beijing–Tianjin–Hebei geomagnetic equipment test project.The new system was used to test the availability of equipment and determine the findings based on big data..

Research on the Development of Daur Ethnic Education under the Influence of Big Data

In this paper, we conduct research on the development of Daur ethnic education under the influence of big data. Life in the river valley of Daur ethnic which is a nationality has a long history, splendid culture and the national spirit of national self-confidence, the foundation of national culture has a strong self-confidence. Combining the concept of big data and data analysis technique to the Daur ethnic education will largely enhance the result of the current education pattern. The survey of the research indicated that we should pay attention to the precious data captured.

Research on the Innovation of Personalized Education in Colleges and Universities under the Context of Big Data

The advent of the big data era has opened up unprecedented quantifiable dimensions for all walks of life,while also presented many opportunities and challenges.The widespread application of big data in the field of education will inevitably promote the innovation and transformation of the higher education in colleges and universities which introduce new opportunities and challenges to personalized education in colleges and universities.How to promote the indepth integration of big data and higher education to meet the needs of students’personalized development is one of the hot topics in the theoretical field today.In view of this,this article starts with explaining the connotation of personalized education in colleges and universities,analyzes the opportunities and challenges faced by personalized education in colleges and universities under the context of big data,and proposes the ideas of innovating personalized education in colleges and universities under the context of big data.

An Exploration into the Application Value of Critical Thinking in Higher Education from the Perspective of Big Data

Starting from the characteristics of big data,the cognition and thinking of contemporary college students have shown new features.Therefore,it is necessary to use the technical means of big data to formulate thinking under big data,combined with critical thinking.By doing so,students can finally nurture a correct attitude and better morality and even complete the fundamental task of higher education.

Application status and development of big data in medical education in China

With the development of information technology, big data has been widely used in medical education in China. Through the analysis of the definition, characteristics and development process of big data, summarized the transformation of domestic big data medical education mode compared with the traditional medical education mode in the teaching mode reform, research method innovation, teaching courses optimization, teaching key extension and the teaching quality monitoring. Based on this, this paper expounds the impact and challenge of big data on medical education, and makes an outlook on its development prospect, indicating that the future development of big data will be open, popular and trending. At the same time, some suggestions on further optimization direction of China's big data medical education are put forward.

Research on Innovation of Ideological and Political Education Method in Colleges and Universities in Big Data Era

The era of big data has brought about tremendous changes in people's daily life, work and thinking patterns. The ideological and political education of colleges and universities has also faced opportunities and challenges. To this end, college ideological and political education workers must strengthen data awareness, innovate data dissemination methods, and transform research paradigms to meet the requirements of the development of the times. This requires universities to continue to innovate, advance with the times, and strive to use innovative methods to promote ideological and political work. Guided by Marxist theory and combined with relevant knowledge of pedagogy and educational psychology, this paper comprehensively and profoundly explores the impact of big data on people's life style, thinking mode and education. On this basis, the current situation and new ways of Ideological and political education in Colleges and universities in the era of big data are discussed in depth, with a view to providing effective reference for the industry.

Integration of Big Data with International Graduate Ideological and Political Education

Nowadays,colleges and universities have a large amount of information about political thought and education in addition to complex student data.Like big data,it has the characteristics of large capacity,high speed,and diversity.The ideological and political education in colleges and universities urgently needs scientific decision-making and the ability to predict possible problems ahead of time.It also perfectly matches the technical advantages of big data technology that can efficiently process data,analyze and extract information,as well as propose solutions.The traditional higher education model can no longer meet the needs of current international higher education.Under the new background,universities must explore a new model of postgraduate international education,which is practical,multi-channel,and comprehensive,on a deeper level.According to data on graduate students’interest,psychology,and behavior,higher education teachers can purposefully innovate the methods and approaches to higher education.The integration of international graduate education with big data has been examined in this research,and a series of cultural exchanges has been carried out for foreign students at Central South University.This kind of introduction seems to have effectively boosted the attractiveness of ideological and political education,improved the research level of international graduate students,and deepened the role of campus cultural activities in educating people on a deeper level.

ChatGPT:The New Trend of Smart Education

In response to the limitations of the traditional education and teaching model,this article proposes a smart education model based on ChatGPT.The model actively breaks the constraint of time and space and the design patterns of traditional education,providing smart education services including personalized learning,smart tutoring and evaluation,educational content creation support,and education big data analysis.Through constructing an open and inclusive learning space and creating flexible and diverse educational models,ChatGPT can help to meet students’individuality and overall development,as well as assist teachers in keeping up with the students’learning performance and developmental requirements in real-time.This provides an important basis for optimizing teaching content,offering personalized and accurate cultivation,and planning the development path of students.

Research on the Construction of Application-Oriented Undergraduate Data Science and Big Data Technology Courses

In order to conduct research and analysis on the construction of application-oriented undergraduate data science and big data technology courses,the professional development characteristics of universities and enterprises should be taken into consideration,the development trend of the big data industry should be scrutinized,and professional application-oriented talents should be cultivated in line with job requirements.This paper expounds the demand for capacity-building professional development in application-oriented undergraduate data science and big data technology courses,conducts research and analysis on the current situation of professional development,and puts forward strategies in hope to provide reference for capacity-building professional development.

A Brief Study of the Development and Application of ＂Internet＋＂ in Middle School English Teaching

Internet education has appeared with the development of the lnternet. Since ＂lnternet＋＂ has come up with in the 2015 government work report, it has become a hot word. ＂Intemet＋＂ has been applied to traditional education, which has reformed the traditional English teaching in middle school. Nowadays, there are many applications in teaching, such as distance education, smart classroom, and so on. Moreover, with the popularizing of big data, it provides all kinds of information for teachers and students in time, helping teachers in middle school to master the process of study among students. Also, parents can know their children＇s performance in school through the big data. In education, the development of the Internet has gone through a few parts from the lowest applications to the complex applications. The applications in education are gradually accepted by every educator. There is no limit of time and space so that people can study anywhere, any time.

Big data in education:Themes and trends

With the rapid growth of big data research,the existing research has investigated the research themes and trends of big data in different disciplines,but less has paid attentions on the field of education.Using bibliographic data from the Web of Science(Wos),we conduct bibliometric analysis and science mapping to explore the research themes and trends of big data in education.The results show that though education is not the major producer of big data research,it does have a positive development trend.In addition,we find that big data in education mainly serves as a tool to facilitate educational outcomes.Implications,limitations,and futuredirections arediscussed.

教育大模型的发展现状、创新架构及应用展望

从通用大模型到教育大模型,是人工智能大模型技术深化发展的重要趋势。基于对教育大模型发展现状、典型案例、潜在挑战的分析,文章认为教育大模型是适用于教育场景、具有超大规模参数、融合通用知识和专业知识训练形成的人工智能模型,是大模型技术、知识库技术及各类智能教育技术的集成,能够推动人类学习和机器学习的双向建构,进而提出了应用驱动、共建共享的创新架构和“以学习者为中心”的未来应用场景,旨在建立人工智能大模型与各类数字化教育应用的开放接口,持续训练和完善能够更好地解决教育专业问题的教育场景模型,形成让广大师生常态化使用的智能教育开放模型集群和知识库,在提炼和萃取深度教育知识的同时,破解人工智能教育应用中的风险和挑战。

数据驱动教育数字化转型的信任机制——教育大数据全生命周期隐私增强模型的构建与典型应用场景分析

教育大数据正在成为驱动国家教育数字化转型战略行动的核心资源,带来了巨大的教育价值,但教育大数据的采集和分析产生了隐私侵害风险、信任危机等严峻问题,阻碍了数据的共享、开发和利用。如何增强教育大数据在开放共享、共建共用中的隐私保护和信任关系,成为制约数据驱动教育数字化转型的关键难题。对此,文章首先采用文献分析法,剖析了教育大数据隐私保护的研究现状与关键问题。随后,文章从应用场景角度设计了教育大数据全生命周期隐私增强框架,并基于此框架从技术实现角度构建了满足不同实体、不同阶段隐私需求的教育大数据全生命周期隐私增强模型及其应用流程。最后,文章介绍了该模型的典型应用场景,涉及学分与资质认证、教育协同与治理、可信评教、个性化学习服务等多个方面。文章的研究能够厘清教育大数据开放共享时的隐私保护关键问题和技术思路,可为实现教育数据要素化全生命周期的隐私保护、建立健全数据驱动教育数字化转型的信任机制提供参考。

大数据赋能基础教育学业质量评价的机理、困境与破解路径

大数据重塑了教育评价生态,推动了基础教育学业质量评价的转型与变革。大数据通过革新评价理念、优化评价方式、扩展评价内容、改进评价结果,全面赋能基础教育学业质量评价。然而,囿于大数据的“双刃剑”属性,基础教育学业质量评价面临着数据滥用、教师数据素养缺失、学生主体性消解等现实困境。为破解困境,大数据赋能基础教育学业质量评价应从加强顶层设计、提升教师数据素养、厘清数据技术价值观念等方面着力,推动基础教育高质量发展。

大数据在高等教育研究中的应用前景分析

大数据为高等教育研究的视野扩展和领域深化赋予了更多可能。研究着重梳理大数据在高等教育研究中的重点领域,分析大数据在高等教育研究中的应用重心和应用方式。研究发现,高等教育的行为主体、实践行动和机构管理是大数据的重点研究领域,聚焦点为研究与教学潜力的开发、教育教学的改革与创新、效能提升。大数据能够帮助高等教育研究实现视域突破、方法融合及应用深化,但在伦理与隐私、数据分析、数据源和存储、主体鸿沟等方面其仍须应对新的挑战。