A modern technology-supported vocational educational system significantly affects the quality of vocational training and contributes to the innovation and economic development of the regional area.... Show More

A modern technology-supported vocational educational system significantly affects the quality of vocational training and contributes to the innovation and economic development of the regional area. The visualization literature analysis was adopted with the purpose of exploring the theoretical framework for developing a 6G-assisted network to realize the multi-party participation in the modern government-industry-education Integration system. The literature review showed the network should involve all cooperation entities into the communication system to intensify all coordination guided by the triple helix theory, should be strong enough to store all kinds of resources to support the optimized sharing, be efficient to track student training processes and learning data to provide scientific evaluation to student development in personal qualities and competencies, be supportive to develop a cooperating culture to form a healthy ecosystem in which all enterprises actively participate and invest in vocational education.

This study analysed two internationally recognised measurements of professional skills: the Programme for the International Assessment of Adult Competencies (PIAAC) and the Digital Competence... Show More

This study analysed two internationally recognised measurements of professional skills: the Programme for the International Assessment of Adult Competencies (PIAAC) and the Digital Competence Framework for Citizens (DigComp 2.2). This analysis aimed to establish a baseline and reference point for a comprehensive understanding of these two scales with the objective of exploring the most relevant competencies and assessing their potential benefits in fostering a technology-driven environment in higher education institutions in Saudi Arabia. The research yielded significant findings regarding the essential competencies that university students should possess, drawing insights from the two assessments and identifying gaps in existing manuals. The research outcomes include valuable insights and best practices that can empower a new generation of university learners to effectively engage with the requirements of Education 4.0.

The concept of “great ideological and political education” requires comprehensive ideological education to better achieve the educational goals of “innovation and entrepreneurship.” This article... Show More

The concept of “great ideological and political education” requires comprehensive ideological education to better achieve the educational goals of “innovation and entrepreneurship.” This article analyzes and explores the intelligent teaching methods of ideological and political education in universities under the background of “innovation and entrepreneurship,” and constructs an intelligent teaching system of ideological and political education in universities under this background. The experimental results show that the stability of the system reaches 95.2%, and the learning efficiency of students has been improved by 11.5%. This work provides important application guidance for big data analysis and IoT sensor data.

Mobile learning (M-learning) has become a crucial tool for both students and educators. The unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM), and... Show More

Mobile learning (M-learning) has become a crucial tool for both students and educators. The unified theory of acceptance and use of technology (UTAUT), the technology acceptance model (TAM), and outside factors were all included in this study's integrative review approach to examine the variables affecting university students' intention to use M-learning and mobile effectiveness. A study at King Faisal University examined the viewpoints of 364 undergraduate and graduate students using a random sampling technique to have better understand the impact of such technological innovation on teaching. Participants in the study were invited to complete a survey created expressly for this study in order to find out if they would still be open to using M-learning to advance the cause of sustainable education. The paradigm of the study was evaluated using a structural equation modeling (SEM) approach and was based on the UTAUT and TAM technology adoption models. The findings demonstrated that each element of the research model had a positive influence on learners' behavioral intention to use M-learning (BIM); it also demonstrated the impact of that intention on long-term educational sustainability. The link between independent characteristics and users' enjoyment and adoption of M-learning is moderated by mobile usability and behavioral control to utilize M-learning. The results also showed that BIM and the utility of mobile devices increased the degree to which M-learning is liked. Mobile usability and BIM both favorably affect sustainable education in terms of user satisfaction and M-learning adaptation. These findings suggest that mobile usability and behavioral intention to utilize M-learning are the main factors influencing the adoption of M-learning in Saudi Arabia's higher education.

This study aims to assess the implementation of smart campus and the students' learning engagement at Zhongshan College, China. A well-structured questionnaire was developed, and information was... Show More

This study aims to assess the implementation of smart campus and the students' learning engagement at Zhongshan College, China. A well-structured questionnaire was developed, and information was collected from 277 students and 377 teachers. The results indicate that both groups of respondents highly agree on the construction levels of the smart campus in terms of security operations, academic technology assistance, public relation services, and stakeholders' experience. Furthermore, respondents emphasized that the level of smart campus construction affects students' learning engagement. Specifically, students' personalized learning engagement is affected by the level of smart campus construction in security operations and public relations services. And the degree of students' use of smart learning resources is significantly related to the smart campus construction levels in all four dimensions. This study fills research gaps and provides valuable guidance for the development of smart campuses.

Given the current rapid development of informatization, people will increasingly use online teaching methods to learn for their quality improvement. Starting from the fundamental theories, such as... Show More

Given the current rapid development of informatization, people will increasingly use online teaching methods to learn for their quality improvement. Starting from the fundamental theories, such as the concept, classification, basic process, task, and method of data mining under the background of Internet Plus, this article analyzes the problems that must be considered in data mining application. Secondly, the Apriori algorithm is studied, the FP-Tree flow chart is established, and the Internet Plus vocational education teaching system model is constructed using multiple databases as data sources. Finally, the results of the teaching system are analyzed and verified, with the model analysis showing that the minimum confidence boost of the system is 0.65, and the minimum support reaches 0.03. The maintainability of the database based on the association rules Apriori algorithm is good; the data entry can be completed smoothly, and the update, deletion, and modification can also be completed smoothly.

In the 6G network environment, the flipped classroom teaching mode has broader prospective applications for improving the drawbacks of traditional classroom teaching methods. This study aims to... Show More

In the 6G network environment, the flipped classroom teaching mode has broader prospective applications for improving the drawbacks of traditional classroom teaching methods. This study aims to explore the advantages of the flipped classroom teaching mode in the 6G network environment and provide feasible teaching strategies and guidance for English teachers. First, the authors collected information about Chinese English learners. Next, they divided the obtained dataset into two groups: the control group and the experimental group. The students in the control group continued to use traditional teaching methods for English teaching, while the students in the experimental group adopted a flipped classroom teaching mode supported by 6G technology. The results indicate that flipped classroom information technology in the 6G network environment has a good effect on English teaching. This article provides a useful reference for the education field and promotes the application of flipped classroom information technology in English teaching in the 6G network environment.

The purpose of this article is to investigate how 5G and wireless communication technologies (5G+WCT) might be applied to English language classroom programs in higher education. The paper describes... Show More

The purpose of this article is to investigate how 5G and wireless communication technologies (5G+WCT) might be applied to English language classroom programs in higher education. The paper describes the complimentary roles of 5G and wireless communication technologies in English language teaching, includes student data collecting and standardization as part of the pre-processing, and optimizes the teaching system using an enhanced ant colony algorithm (BACO). Furthermore, the thesis delineates diverse approaches to verify and assess the program's efficacy. Through the creation of cutting-edge instructional strategies and data collection techniques, this study fosters innovation in English language instruction in higher education. The study offers promise for real-world application and is significant for raising student success, instructional quality, and educational efficacy. However, since 5G technology is still developing, the results of this study could not be applicable in the future or would need to be updated.

Landscape garden design is an important design foundation course for undergraduate students of landscape architecture in China, but the current classroom teaching has the problem of limited spatial... Show More

Landscape garden design is an important design foundation course for undergraduate students of landscape architecture in China, but the current classroom teaching has the problem of limited spatial dimension of the course. This paper proposes a virtual scene model construction method through the computer software with the creation of the need to display the scene. This virtual reality technology has immersive, interactive, and risqué characteristics. This paper focuses on the key points of virtual reality technology, discusses the specific implementation method of virtual reality technology in the “landscape garden design” course, and introduces the interactive control principle. The results of the research show that virtual reality technology to assist teaching can cultivate students' spatial thinking and enhance students' spatial simulation experience, greatly reducing the cost of traditional teaching.

The purpose of this paper is to study the practice of multimedia technology in the teaching of scientific and technical English. With the rapid development and popularisation of computer technology... Show More

The purpose of this paper is to study the practice of multimedia technology in the teaching of scientific and technical English. With the rapid development and popularisation of computer technology and the deepening of educational concepts, multimedia-assisted English teaching has become one of the most important foreign language teaching modes at present. This study firstly analyses the impact of multimedia technology on English teaching, secondly faces the advantages and challenges of multimedia technology in the teaching process, and finally explores the use and effect of multimedia technology in scientific and technological English teaching based on the data of the survey and research. The results of the study show that for college English teachers in colleges and universities, they should fully explore the advantages of multimedia technology in the process of using it and use it skillfully in teaching practice, which will have a positive effect on improving the quality of English teaching and deepening the reform of college English teaching.

The current study aims at assessing the factors which could affect students' use of ChatGPT. The study proposed a theoretical model that included five factors. Data were collected from 136 students... Show More

The current study aims at assessing the factors which could affect students' use of ChatGPT. The study proposed a theoretical model that included five factors. Data were collected from 136 students using a questionnaire. The data were analyzed using two steps: CFA for measuring the model and SEM for analyzing the relationships and testing hypothesis. The findings revealed that both performance expectancy and facilitating conditions significantly influenced students' intentions to use ChatGPT. Contrary to expectations, both social influence and effort expectancy had insignificant effects. By elucidating the core factors influencing the utilization of ChatGPT, this study can provide valuable insights for policymakers. Furthermore, this study contributes to the existing literature and lays the foundation for future research seeking a deeper understanding of the factors influencing the use of other AI technologies in teaching and learning.

As technology continues to evolve, the process of English translation has become easier. A technology called widget, which is used in modern research, provides an efficient graphical user interface... Show More

As technology continues to evolve, the process of English translation has become easier. A technology called widget, which is used in modern research, provides an efficient graphical user interface for the interaction between the user and the application. This paper compares the newly proposed wireless widget system with existing models of English translation strategies for internet of things (IoT), cloud computing (CC), artificial intelligence and edge computing (AI+EC), and pure internet concepts. These models were compared on metrics such as accuracy, search completion rate, and throughput. The results show that the proposed system outperforms the existing models with an accuracy rate of 98%, a search completion rate of 96%, and a maximum throughput of 96%. The model shows high performance advantages and can effectively improve the efficiency of translation work.

In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction... Show More

In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction method to further explore the reform model of university English teaching in the context of educational ecology. First, this paper discusses the development of the layered progressive approach in various countries and the current status of the layered progressive approach. By allowing the use of the model of the layered progressive approach, the data related to the reform of university English teaching were analyzed and organized. The combination of internal optimization, data-theoretic learning algorithms, and data federation algorithms for the model of the hierarchical incremental approach are also investigated. The results of the study show that the layered progressive model of college English teaching reform has good results through specific practical applications in a strengthened educational ecosystem.

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper... Show More

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, the authors selected and analyzed 199 SCI and SSCI papers on HEI published from 2000 to 2023 by VOSviewer and CiteSpace software. The results indicate that the publication volume of HEI research has grown significantly in recent years. The author network shows the collaboration and contribution of different researchers and institutions, while the journal network reveals the multidisciplinary nature and scope of the field. The keyword network and the burst keyword analysis identify the main research themes and the emerging hot topics in HEI. The co-citation network of sources illustrates the theoretical and methodological foundations and influences of the field. The paper concludes with some implications and suggestions for future HEI research.

To effectively avoid subjective bias in manual evaluation. This article proposes a MIDI piano teaching performance evaluation method based on bidirectional LSTM. This method utilizes a three-layer... Show More

To effectively avoid subjective bias in manual evaluation. This article proposes a MIDI piano teaching performance evaluation method based on bidirectional LSTM. This method utilizes a three-layer bidirectional LSTM neural network mechanism to make it easier for the model to capture useful information. In addition, the Spark clustering training model is constructed using the deeplearning4j deep learning framework, and the model parameters are adjusted through the UI dependency relationships provided by deeplearning4j to improve work efficiency. The experimental results verified the superiority of the bidirectional LSTM model. The methods provided in this article can improve students' independent practical abilities and reduce the pressure on teachers during the teaching process. These measures can promote the development of music education, improve students' music literacy and learning skills, and make positive contributions to the music education industry.

By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector... Show More

By using modern data analysis techniques, this study aims to construct an innovative university English teaching effectiveness evaluation model based on particle swarm algorithm and support vector machine. The model is designed to improve assessment accuracy and personalization. The research process includes the methodology of data collection, preprocessing, model construction and evaluation. The experimental results show that the model can more accurately assess students' English learning effectiveness and provide customized suggestions for personalized education. This research is important for improving the quality of university English education, promoting personalized learning, and providing support tools for educational decision makers.

Students from economically disadvantaged nations (EDN) face significant challenges in accessing high-quality education and securing global internships due to inadequate resources, funding, and... Show More

Students from economically disadvantaged nations (EDN) face significant challenges in accessing high-quality education and securing global internships due to inadequate resources, funding, and infrastructure. The COVID-19 pandemic has highlighted the potential of online platforms for providing accessible, remote education and internship opportunities, aligning with UNESCO's sustainability education objectives. Using the SWOT analysis tool within the context of the experiential learning-driven integrated reflective cycle model (IRC), the research compares onsite and online internship types in higher education to identify areas where interventions can be applied to enhance the online internship experience. The study analyzed 42 interns, both on-site (OSIs) and online (ONIs), to evaluate the constructs of 'experience,' 'action,' 'preparation,' and 'theory”. The findings suggest that OSIs have weaknesses such as poor goal planning, a lack of awareness of relevance, and low communication confidence, while ONIs include a lack of exposure to teamwork and in-person experiences.

The metaverse is a mixed blend of digital and tangible worlds, indicating the future directions of Internet sector development. This study aimed to assess the factors affecting students' intentions... Show More

The metaverse is a mixed blend of digital and tangible worlds, indicating the future directions of Internet sector development. This study aimed to assess the factors affecting students' intentions to use a metaverse platform. The unified theory of acceptance and use of technology was applied as the research model. Data were collected using a survey of 240 students. Two steps in SEM AMOS were conducted to analyze data. The results demonstrated that effort expectancy and social influence positively affect students' intentions to utilize metaverse technology. However, effort expectancy had an insignificant effect on students' intentions to utilize metaverse technology. These findings shed light on the acceptance and adoption of metaverse and identify influencing factors that could increase metaverse utilization. Moreover, this study offers a distinctive and fresh perspective on metaverse technology that can be used as a basis for future research in this field.

With the development of technology, people expect real-time communication with computers. Wearable devices, such as those for monitoring physiological signals, have rapidly developed and are now... Show More

With the development of technology, people expect real-time communication with computers. Wearable devices, such as those for monitoring physiological signals, have rapidly developed and are now being applied in college and university evaluation. Due to the non-standard and unscientific practices in teaching, teachers may experience psychological obstacles when evaluating students. To ensure successful evaluation, we must motivate teachers to correctly understand and actively participate in the evaluation process, thus facilitating communication between people and computers. Emotion recognition based on multi-physiological signals, such as ECG, pulse, electromyography, electrodermal, and respiratory signals, is an effective method for achieving this. This dissertation conducts in-depth research on the methods for emotion recognition based on multi-physiological signals. It explores feature extraction methods, feature selection, and fusion to provide objective assessments of physiological and psychological activity states, which are used as a basis for accurate emotional judgments.

Firstly, this paper analyzes the role of AI in the reading management of English language and literature, establishes the implicit knowledge base of neural network, designs the auxiliary reading... Show More

Firstly, this paper analyzes the role of AI in the reading management of English language and literature, establishes the implicit knowledge base of neural network, designs the auxiliary reading system for learning English language and literature, and optimizes the English language and literature management model of AI. The experimental results show that its reading efficiency is increased by 0.48%, and the performance of the credibility model is improved by 0.53% compared with the original system, which greatly optimizes the running time of the system. To some extent, it helps users to manage their time in English language and literature reading, and greatly improves users' reading efficiency and quality. Based on this advantage of AI algorithm, this paper introduces that the algorithm optimizes the reading management model and the training process of neural grid, and constructs a model of English language and literature assisted reading system based on AI. The system can better meet the needs of users in English language and literature reading management.

The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses... Show More

The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses the characteristics of mobile Internet in the classroom, WeChat platform, English learning app and other forms of teaching, the changes and influence of mobile Internet on English teaching, and its application in university English teaching. According to the actual teaching situation, a comprehensive evaluation system based on the learning process and results was established. The results show that the university English teaching model based on mobile Internet and the innovative evaluation and examination system can effectively improve the teaching efficiency and students' independent and sustainable learning ability. Through the reform of university English teaching, students' academic performance and learning ability have been improved. The research results are of great practical significance for promoting the reform and innovative practice of university English teaching.

With the development and the popularization of sports dance, sports dance teaching has become a required elective course in universities. Sports dance can not only improve students' comprehensive... Show More

With the development and the popularization of sports dance, sports dance teaching has become a required elective course in universities. Sports dance can not only improve students' comprehensive quality, but also affect college students' healthy psychology. The use of VR (Virtual Reality) technology in dance education will definitely develop and promote dance education. This paper studies an effective feature extraction method for the characteristics of dance movements based on VR. The edge features of all video images in each segment are accumulated into one image, and the directional gradient histogram features are extracted from it. The results show that compared with the current robust regression method and cascade regression method, our method has higher positioning accuracy on the pollution test set, and more than 75% of the sample errors in this method are within 0.1. This also verifies the effectiveness of this motion recognition algorithm for dance motion recognition. Dance can effectively resist the psychological barriers of college students and improve their comprehensive quality.

This investigation underscores the significant impact of PE strategy selection on both the cognitive and operational aspects of translation. Highlighting the critical role of PE skills development... Show More

This investigation underscores the significant impact of PE strategy selection on both the cognitive and operational aspects of translation. Highlighting the critical role of PE skills development in translator education, the study proposes several avenues for further research, including broadening participant demographics, integrating diverse and mixed-methods approaches, keeping pace with technological advancements, and engaging in longitudinal studies. These insights offer valuable directions for refining PE methodologies, enhancing translator training programs, and ultimately, elevating the quality of translations.

The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive... Show More

The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing innovative talent cultivation capability. First, by CIPP model (Context, Input, Process and Product Evaluation), an assessment indicator system is built, consisting of 89 indicators in 21 categories. Then, based on indicator characteristics, this paper uses public data statistics, database retrieving, student survey, teacher survey, support personnel and expert investigation, to collect indicator values. After this, by a powerful machine learning algorithm, gradient Boosting regression tree, a capability assessment model is established. And based on collected data, established model is compared with several regression models in innovative talent cultivation capability assessing. Results confirm the performance superiority of our solution.

At present, IT (Information Technology) with computer network as its core has begun to integrate into CET (College English Teaching) practice, which has brought unprecedented influence on ELT... Show More

At present, IT (Information Technology) with computer network as its core has begun to integrate into CET (College English Teaching) practice, which has brought unprecedented influence on ELT (English Language Teaching). This paper adopts the strategy of active learning to build SVM, overcomes the shortcomings of typical SVM, and comprehensively considers various actual situations to build an assessment model of college English classroom instructional quality. The experimental results show that the classification accuracy of this algorithm can reach 96.21% on Zoo data set and 94.36% on Iris data set. This study is of great theoretical and practical value for improving the level of college English classroom teaching in the IT ecological environment.

Aiming at the problems of inadequate user feature extraction, cold start and sparse data, a personalized course recommendation algorithm that utilizes TB-BGAT is suggested. First, the Tiny... Show More

Aiming at the problems of inadequate user feature extraction, cold start and sparse data, a personalized course recommendation algorithm that utilizes TB-BGAT is suggested. First, the Tiny Bidirectional Encoder Representation from Transformers (TinyBERT) model is utilized to output character-level word vectors; then, Bidirectional Recurrent Neural Network (BiGRU) model is utilized to obtain the embedded contextual semantic features. Finally, the attention mechanism is utilized to allocate weights to various course features by assigning their importance and to obtain the output results. The results of experiment on the publicly available dataset MOOCs-Course prove that the proposed method improves at least 3.62%, 3.04%, and 3.33% in precision, recall, and F1-score, correspondingly, in contrast to several other state-of-the-art course resource recommendation algorithms. The proposed method can enhance the effectiveness of the course recommendation model, enhance the quality of learners' online learning, and provide good technical support for online education learning platforms.

With the continuous advancement of educational informatization deepening of teachers' professional development, educational technology ability has become a necessary quality and skill for college... Show More

With the continuous advancement of educational informatization deepening of teachers' professional development, educational technology ability has become a necessary quality and skill for college teachers. This article introduces the basic concept of the TPACK framework and the design concept of intelligent disciplinary systems and elaborates in detail on how to apply the TPACK framework to the design and development of intelligent disciplinary systems. Through case analysis, this article demonstrates the advantages of intelligent subject systems in improving teaching quality and promoting active learning among students. Finally, this article discusses the future development direction and application prospects of intelligent disciplinary systems. The intelligent subject system based on the TPACK framework provides a new teaching solution for the education field, which helps to promote the process of educational informatization and personalized teaching. Cultivate students' rigorous scientific literacy and good practice habits, and master standardized experimental analysis methods.

Under the background of “Internet plus”, the application of English multi-modal reading teaching mode is of great significance. With the continuous development of Internet technology, the field of... Show More

Under the background of “Internet plus”, the application of English multi-modal reading teaching mode is of great significance. With the continuous development of Internet technology, the field of education has also been deeply influenced, especially in English reading teaching. Therefore, this study aims to explore how to integrate multi-modal resources into English reading teaching under the background of “Internet plus”. Through literature review and case analysis, it is found that multi-modal reading teaching mode can improve students' reading interest and effectiveness. The results show that the use of images, audio, video and other forms of media resources in the teaching process can help students better understand and absorb English reading materials. Therefore, this paper proposes that in the era of “Internet plus”, teachers should actively design multi-modal English reading teaching activities with the help of various digital media resources, so as to improve students' reading level and ability and promote the development and innovation of English teaching.

To address the deficiency in the analysis of individual students within existing research on in-classroom social networks and the constraints of traditional centrality metrics in identifying... Show More

To address the deficiency in the analysis of individual students within existing research on in-classroom social networks and the constraints of traditional centrality metrics in identifying influential nodes, this paper presents the NEDC-GTOPSIS evaluation method for evaluating node influence in multi-layer heterogeneous networks. Initially, students' friendship, interaction, and attribute information are leveraged to compute neighborhood overlap and attribute similarity between nodes, to construct the Composite Relationship Network. Subsequently, the Seat Similarity Network is constructed by applying the Nearest-Neighbor Effective Distance Criterion to compute seat similarity across various class sessions among nodes. Finally, the structure characteristics of two networks serve as influence decision indicators, and the GRA-TOPSIS algorithm, based on the combined weight method, evaluates nodes' influence. Experiments demonstrate that, compared to traditional single-layer relational networks and classical algorithms, this method can more effectively assess influential student nodes.

The effort to implement personalized teaching in blended learning environments faces various challenges, such as the diversity of needs among learners; educators must find ways to identify... Show More

The effort to implement personalized teaching in blended learning environments faces various challenges, such as the diversity of needs among learners; educators must find ways to identify, understand, and address these differences. This study explores how to construct a learner profile model in blended learning environments, develop personalized teaching strategies based on learner profiles, and evaluate the effectiveness of these strategies. The results demonstrate that personalized teaching strategies significantly enhance learner engagement, autonomy, and academic performance. These strategies have been validated through satisfaction surveys conducted with both teachers and students. The study provides a theoretical framework and practical guidance for personalized teaching while also highlighting challenges in implementation. It is recommended that future research expand sample sizes, integrate quantitative and qualitative research methods, and pay closer attention to learners' personalized needs to further enhance the practicality and effectiveness of personalized teaching strategies.

AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to... Show More

AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to examine the role of AI chatbots in education, ethical considerations, and sentimental analysis regarding the utilization of ChatGPT in education. ChatGPT has revolutionized education, but their use raises ethical concerns. They can enhance language learning, but may lead to plagiarism and information overload. Students may not develop discrimination skills and may rely on ChatGPT, leading to concerns about academic dishonesty and a failure to develop cognitive and analytical skills. The use of ChatGPT in clinical education also raises accountability and liability concerns regarding the use of patient information for educational purposes. Guidelines should be established to ensure privacy rights are upheld. Finally, the positive sentiment category was populated by predominantly positive sentiments, followed by neutral and negative sentiments. Future research on ChatGPT in education should focus on its application effectiveness in various educational settings and ethical considerations.

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors... Show More

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using multimodal data fusion techniques, the study conduct exploratory analyses on various data types, including learner academic performance, psychological assessments, learning behavior, and physiological information. This leads to the construction of a personalized education learning support service model. The model focuses on objectives such as monitoring learning behavior, identifying preferences, recognizing abilities, optimizing paths, and recommending resources. The goal is to provide learners with sustained support services throughout the personalized learning process, addressing individual needs, fostering enthusiasm, and maintaining long-term motivation.

With the development of social economy, the globalization of the world has become an inevitable trend. However, the cultures of various countries and nationalities in the world are constantly... Show More

With the development of social economy, the globalization of the world has become an inevitable trend. However, the cultures of various countries and nationalities in the world are constantly communicating and merging with each other; the folk art in China has been greatly impacted, and the traditional culture with distinctive national characteristics has been rejected. Strengthening folk art education is needed not only to improve people's personality and cultivate people's aesthetic taste, but also to protect traditional culture and impart national spirit. With the rapid development of information technology relying on hand-held learning equipment, mobile internet technology, and network multimedia technology, life-long learning is possible. Using smart mobile devices to study the art teaching of folk art is conducive to in-depth exploration, applying the learning methods of folk art to our own study and life, and protecting and inheriting the infringed folk art.

This paper employs BP Neural Network (BPNN) theory to evaluate innovation and entrepreneurship education in universities. It utilizes students' evaluation indexes as input vectors and determines the... Show More

This paper employs BP Neural Network (BPNN) theory to evaluate innovation and entrepreneurship education in universities. It utilizes students' evaluation indexes as input vectors and determines the number of hidden layer neurons. Experimental results serve as output vectors. The BPNN method proves reasonable and feasible for vocational education course evaluation, exhibiting a 14.96% higher accuracy than traditional genetic algorithms. The paper discusses the model, configuration, characteristics, training process, algorithm enhancement, and limitations of neural networks, followed by an introduction to genetic algorithms. Through analysis of principles, basic operations, and common operators, it establishes a theoretical foundation for subsequent discussions.

The COVID-19 period ushered in a paradigmatic shift towards exponential growth of ubiquitous e-learning. Despite the well-documented benefits of e-learning, which received unprecedented attention... Show More

The COVID-19 period ushered in a paradigmatic shift towards exponential growth of ubiquitous e-learning. Despite the well-documented benefits of e-learning, which received unprecedented attention during the COVID-19 pandemic, little has been reported on factors influencing student dropout rates in courses delivered via e-learning. In this paper, the authors explore the factors contributing to student discontinuations in nonvolitional postpandemic conditions. Adopting a multimethod qualitative research design, the authors investigated the factors leading to increased student dropout rates from e-learning programs. The researchers used thematic analysis to interpret the data, resulting in the emergence of five themes. The findings reveal several factors contributing to failure to complete studies on programs delivered via e-learning. Although not exclusively conclusive, the study's findings indicate skills gap solutions and resource concerns which need to be addressed to convert market demand and enrolment into optimum completion rates, thereby increasing e-learning's success.

The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content... Show More

The objective of this work is to predict the employment rate of students based on the information in the SSM (student status management) in colleges and universities. Firstly, the relevant content of SSM is introduced. Secondly, the BP (Back Propagation) neural network, the LM (Levenberg Marquardt) algorithm, and the BR (Bayesian Regularization) algorithm are introduced. In addition, the LM algorithm is combined with the BR algorithm to optimize the BP neural network, so as to establish a prediction model of the employment rate of college graduates based on the LM-BP neural network (the established prediction model). Finally, the established prediction model is verified after the historical data of college students in the SSM are managed and processed using the big data analysis technology. It suggests that the established prediction model shows higher prediction accuracy, more stable prediction performance, more ideal prediction effect, and higher practical application value.

With the rapid development of Internet technology, distance online education and training is becoming an important part of the education and training market. Based on the theory of perceived value... Show More

With the rapid development of Internet technology, distance online education and training is becoming an important part of the education and training market. Based on the theory of perceived value, taking the distance online education and training platform as the research object, this paper establishes a sample database, analyzes the reliability, validity, correlation and regression of the data, obtains the main factors of parents' perceived service quality, and analyzes the relationship between parents' perceived service quality and satisfaction and willingness to act, so as to provide ideas for improving the brand awareness of distance online education and training. The research results provide theoretical data support for parents to perceive the brand recognition of distance online education and training.

This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an “interest” parameter into ARM, dynamically adapting content to... Show More

This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an “interest” parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's efficacy by correlating learning content with academic performance, specifically CET-4 and CET-6 scores. Comprehensive preprocessing ensures data quality and privacy, employing techniques like de-identification, data perturbation, and aggregation. Advanced data analysis, including cross-validation and multivariate techniques, bolsters findings' reliability. Results highlight the ARM model's capacity to generate personalized learning paths, transcending conventional methods, and its potential as a cornerstone for data-driven education reforms. Future research will explore machine learning refinements and cultural adaptability to broaden its impact, fostering equitable, high-quality digital English education worldwide.

In the context of the multimedia era, college counselors and college students should make progress together. This article aims to explore the practical issues of applying multimedia and visual-image... Show More

In the context of the multimedia era, college counselors and college students should make progress together. This article aims to explore the practical issues of applying multimedia and visual-image technology to the training of college counselors. We propose a three-dimensional multimedia visual image recognition technology based on convolutional neural networks (CNNs) and apply the algorithm to image-recognition tasks to provide support and assistance for college-counselor training in network and multimedia environments. By combining a CNN with image recognition, our research results show that this method can effectively adapt to different types of image-recognition tasks. This means that our algorithm can be fully applied to these tasks and provide strong support for the training of college counselors.

In the context of college physical education curriculum reform, fostering students' interest and promoting lifelong physical exercise have become crucial. Aerobics, an integral component of physical... Show More

In the context of college physical education curriculum reform, fostering students' interest and promoting lifelong physical exercise have become crucial. Aerobics, an integral component of physical education, plays a key role in achieving these objectives. However, existing data flow analysis technologies lack integration, limiting their ability to leverage information from various sources. To address this issue, this paper proposes an aerobics teaching model utilizing few-shot learning technology for data flow analysis. The model incorporates a label feature network based on metric learning, enhancing its ability to analyze multi-scale features and label features within classes. Comparative analysis demonstrates an 8.12% improvement in accuracy compared to traditional image feature combined classifier models.

In innovation and entrepreneurship education, how to effectively use big data technology to improve the quality of education has become an urgent problem. In this article, the authors summarize the... Show More

In innovation and entrepreneurship education, how to effectively use big data technology to improve the quality of education has become an urgent problem. In this article, the authors summarize the development of big data technology and its application background in higher education and point out the limitations of traditional education quality evaluation methods. They discuss the research status of the quality evaluation of innovation and entrepreneurship education in colleges and universities at home and abroad and the application of big data in education quality evaluation. Using the fuzzy comprehensive evaluation method, they constructed a quality evaluation model of innovation and entrepreneurship education in colleges and universities based on big data and proposed a corresponding evaluation process and index system. Finally, through empirical analysis, they verified the effectiveness and operability of the evaluation model. This research has theoretical and practical significance for improving the quality of innovation and entrepreneurship education in colleges and universities.