Teaching Platform Research Articles

Assessing the impact of interactive multimedia learning platforms on dance education outcomes

This study examined the use of interactive multimedia learning platforms in dance education, guided by the Technology Acceptance Model (TAM) and Self-Efficacy Theory. The research used Structural Equation Modelling (SEM) with a random sample of 362 students from four schools in Beijing. It aimed to explore the relationship between perceived usefulness (PU), perceived ease of use (PEOU), attitudes towards these platforms, and the impact of self-efficacy on performance and learning. The results showed that PU and PEOU significantly improved students' attitudes, which in turn enhanced their self-efficacy and performance. The study suggests that multimedia platforms are more effective than traditional teaching methods in improving learning outcomes, engagement, and satisfaction in dance education. These findings contribute to the growing body of research on educational technology in the arts, highlighting the importance of integrating technological advancements with psychological factors when developing digital learning environments. This study stands out by combining TAM with Self-Efficacy Theory in the context of dance education, providing a comprehensive understanding of the cognitive and emotional factors that affect technology acceptance and learning outcomes. It addresses the challenges and benefits of using multimedia in a physically demanding field like dance, which has not been extensively researched. However, the study is limited by its focus on a specific region and demographic group. Future research should include a broader range of participants to ensure the findings are applicable to various contexts. Despite some limitations, this study offers valuable insights for designing more effective multimedia-based learning systems for dance and other fine arts.

Creating a speech portrait of a modern Chinese teacher in online media

The purpose of the study is to identify the speech characteristics of modern Chinese teachers. The object of the study is the blog(s). Special attention is paid to the visual and auditory design of the video material: the presence of music, the design of the room, the style of the blogger's clothes, the manner of speech. The desire to show their own market attractiveness against the background of competitors, the desire to become popular and have their own audience on the Internet motivates bloggers to show authority in a variety of ways. The research material was two commercials of English language courses on the "bilibili" platform. The coronavirus infection has pushed the Chinese government and private educators to develop online teaching platforms, among which the bilibili video hosting can be cited as example. Users of this platform have the opportunity not only to watch videos, but also to purchase video courses on various topics. The work uses a descriptive method (observation, interpretation, generalization). In the course of the study, the speech analyzer programs Text-Analyzer and Cathoven were used, with the help of which the approximate level of oral text on the CEFR scale was determined. As a result of the analysis, the main features of the speech portrait of the teacher-blogger were highlighted, and the importance of the image on the Internet for attracting an audience was emphasized. The main contribution of the author is a comprehensive study of the image of a modern teacher in Chinese linguoculture. Along with the economic boom and the development of social networks in China, there has been a reassessment of traditional values. The penetration of Western mass culture has had a strong impact on the population, especially on the younger generation, who use the Internet to a greater extent and consume entertainment and educational content. This influence has not spared modern Chinese teachers. Studying the image of a Chinese teacher in modern realities will help to update information about Chinese culture, its synthesis with modern mass culture and traditional Confucian values.

Exploring university students’ perceptions and attitudes toward associated factors of electronic learning during the COVID-19 pandemic

This study examines the perceptions and attitudes of university students toward electronic learning (EL) during the COVID-19 pandemic, analysing the factors that influence their acceptance and engagement with online education platforms. A combination of technological, pedagogical, institutional and individual considerations has been assessed to understand the challenges and opportunities presented by the transition to EL. Factors such as performance expectancy, social influence, facilitating conditions, perceived usefulness and ease of use are observed to shape student acceptance. Furthermore, individual innovativeness and EL preparedness are identified as positive influences on EL adoption. The research findings highlight the importance of addressing the digital divide to ensure equitable access to EL systems and suggest that enhancing digital infrastructure, fostering digital literacy and involving students in developing EL policies could improve educational outcomes in higher education institutions.

P187 CO-DESIGNING AN INTERVENTION FOR CARDIOVASCULAR DISEASE RISK ASSESSMENT AND MANAGEMENT AFTER HYPERTENSIVE DISORDERS OF PREGNANCY

Background and objective: Women with a history of hypertensive disorders of pregnancy (HDP) are at two-to-fourfold increased risk of developing cardiovascular disease (CVD) within 10 years post-pregnancy. Despite clinical practice guidelines recommending general practitioners (GPs) for ongoing CVD preventative care, no intervention strategies exist within primary care aimed at improving risk assessment or management for women after HDP. This study aimed to co-design an intervention to enhance the implementation of CVD risk assessment and management following HDP for primary care settings in Australia. Methods: Researchers used the Integrated Knowledge Translation (IKT) framework and conducted five co-design meetings with the investigative team and end-users. Meetings were informed by the Behaviour Change Wheel (BCW) framework for intervention development and incorporated research findings from a systematic review and meta-analysis, surveys, and an online discussion. Data from activities and audio recordings following each meeting were analysed iteratively to inform ongoing intervention development. Results: The 18 end-users included women with lived HDP experience (n=8), obstetricians (n=2), midwives (n=5), and GPs (n=3). The target priorities were to improve communication between hospital staff and GPs following HDP occurrence and increase knowledge of GPs and women regarding CVD prevention post-HDP. Part 1 of the intervention is delivered within the hospital setting via physical resources to address communication gaps between hospital and primary care providers for women after post-HDP. Part 2 is delivered via an update to existing GP education platforms and resources for use within GP consultations to provide education for women and GPs on CVD prevention post-HDP. Conclusions: The IKT and BCW frameworks played a crucial role in development of a tailored intervention aimed at bridging gaps in current primary care practice and enhancing implementation of CVD risk assessment and management for women following HDP. This an important step in addressing CVD risk in women of childbearing age.

A Bibliometric Analysis of The Production-Oriented Approach in College English in China from 2015 to 2024

This paper studies the temporal distribution, author collaboration, research hotspots, theme clustering, and research changes and trends based on 516 CNKI literature in the field of Production-Oriented Approach (POA) for college English in China from 2015 to 2024. It reveals that research on the Production-Oriented Approach for College English in China from 2015 to 2024 can be divided into the Initial Fast Exploration Stage (2015–2017), Fast Development Stage (2018–2021), and Sustainable Development Stage (2022–2024). High-frequency keywords such as college English teaching, college English writing, blended teaching, teaching assessment, etc. are hotspots for current scholars' attention. The themes of research on the POA of college English in China mainly include teaching practice and application of the Production-Oriented Approach, exploration of the Production-Oriented Approach teaching model and design, and teaching assessment of the POA. “Teaching Reform,” “Blended Teaching," and “Teacher-Student Collaborative Assessment” are the current research frontier issues in the development of a Production-Oriented Approach for college English in China. Overall, the POA represents a significant advancement in China's college English teaching field. Its emphasis on integrating language learning with practical application and whole-person education addresses many of the shortcomings of traditional college English language teaching. To improve teaching development in the reform of POA for college English and to better prepare Chinese students for international communication, future research should prioritize themes such as investigating how digital tools and online platforms in education can enhance the implementation of POA and innovative approaches to teacher education that align with POA principles.

Transforming higher education: a decade of integrating wikipedia and wikidata for literacy enhancement and social impact

AbstractThis study examines a decade-long implementation of a course model leveraging Wikipedia and Wikidata as primary educational platforms in higher education. In alignment with the UNs’ SDG 4, this initiative emphasized inclusive, equitable education and lifelong learning opportunities. The study scrutinizes the formulation and deployment of three elective courses, rooted in this model, which were designed to augment students’ academic, digital, collaborative, and communication skills through the creation of Open Educational Resources (OERs), achieving significant social impact—evidenced by over 2000 new and 7000 edited articles, accruing 75 million public views. The research addresses three principal areas: the development and application of the model; course outcomes, including OERs produced, academic achievements, and students’ learning experiences; perceived challenges and benefits from the perspective of both students and faculty. A mixed-methods approach was employed to examine data from 17 iterations, involving 616 participants. Students’ learning experience was extracted from post-course questionnaires completed by 70% (n = 429). Findings demonstrate the role of Wikipedia and Wikidata in fostering knowledge creation, digital and data literacies and critical thinking, with the research contributing to the conversation surrounding Open Educational Practices. Findings include details on incorporating issues of diversity, equity, inclusion (DEI) and knowledge gaps into the curriculum design, and map challenges and benefit for students and faculty. This extensive study offers valuable insights into the effectiveness of embedding OERs in higher education, spotlighting the pedagogical implications and social impact of this approach. It discusses the relevance of this educational strategy in the context of Generative AI technologies.

Computer Allied Intelligence in the Education Resource-Sharing Based inContract Deep Learning

A resource-sharing platform is an online space where individuals or organizations can exchange or access various resources, such as knowledge, skills, tools, or assets. These platforms facilitate collaboration and cooperation among users by providing a centralized hub for sharing resources efficiently. In university higher education, a resource-sharing platform serves as a vital tool for students, faculty, and staff to optimize access to a wide array of educational resources. These platforms enable the sharing of academic materials, such as textbooks, lecture notes, and research papers, fostering collaborative learning environments. This paper proposed the proposed method of Distributed Consensus Blockchain Deep Learning (dCBDL) for a resource-sharing deep learning platform in higher education aims to revolutionize collaborative learning and resource utilization. Initially, the dCBDL model uses a blockchain network that serves as the underlying infrastructure for the platform. This blockchain will store transaction records, verify the authenticity of shared resources, and ensure data integrity and immutability. The proposed model uses smart contracts and decentralized storage with a consensus mechanism for data processing in higher education. Finally, the proposed dCBDL model uses the deep learning model for the classification and assessment of student performance in higher education. The proposed model achieves a classification accuracy of 98% which is significantly higher than the conventional techniques such as blockchain architecture and SVM and LSTM classifiers.

Implementasi Project Based Learning untuk Mewujudkan Profil Pelajar Pancasila di Sekolah Dasar Negeri

This research aimed to analyze the implementation of Project Based Learning to create a Pancasila student profile at SD Negeri Bakulan, Yogyakarta. This type of research was qualitative in the form of a case study through interviews, observation, and document study. The research results showed good planning at SD Negeri Bakulan regarding the implementation of PjBL, which was characterized by team formation, scheduling, creating general themes, creating teaching modules, and outreach to students’s parents. The implementation stage was carried out by following the steps of the PjBL learning model. After the implementation stage, reflection and evaluation were carried out for each PjBL activity. Supporting factors in implementing PjBL at SD Negeri Bakulan include good cooperation from teachers, teacher readiness in planning and implementing it, high student enthusiasm, good parental enthusiasm, the existence of facilities and infrastructure as well as tools and materials that were readily available, and there were examples of implementing project learning on the independent teaching platform. . Meanwhile, factors that hinder the implementation were the students feeling bored in the middle of the process and teacher creativity still needs to be further developed.

Students’ Attitudes on The Role of Artificial Intelligence (Ai) In Personalized Learning

Educational institutions are increasingly incorporating new technologies into their classrooms, such as artificial intelligence (AI), enabling more innovative teaching methods and learning experiences. Unlike traditional teaching methods, where lecturers adapt their lectures to the needs of the average student, AI-powered educational platforms are more dynamic and productive, as they can be adapted to the preferences, learning styles and pace of each student, enabling personalized learning. The aim of this study is to gather information that will help educators, legislators, and AI developers optimize AI’s role in education for increased student achievement by examining students’ attitudes toward the implementation of AI in personalized learning. The findings of this study may have an immense effect on how AI is used in educational settings in the future, because they may provide better understanding that would enable students to receive more individualized instruction and autonomy while also increasing pedagogical opportunities and reducing an excessive amount of administrative work for educators. 219 students of Megatrend University in Belgrade participated in the research (all three study levels), to whom the questionnaire was sent by e-mail. The results indicate that students believe that: a) If the application of AI makes learning personalized, the greater the possibility for students to identify their abilities and creativity; b) If lecturers apply the most effective teaching methods using AI, they can significantly automate the monitoring of student progress; c) If innovative and interesting learning opportunities are applied in classes, the greater the interactivity of students in the teaching process; d) AI can examine past student performance to identify areas of difficulty and provide tailored assistance in those areas.

Mobile Learning and Resource Sharing Mode of College English Translation Based on 5G Mobile Communication Technology

The application of 5G and other mobile communication technologies to education and teaching, and the construction of College English Translation mobile learning and resource sharing model and related models have important scientific value and significance for the effective organization and management of learning resources and the improvement of the speed and efficiency of college english translation resource retrieval. This research mainly combines the characteristics of complementarity and expansion of mobile learning technology for traditional online learning technology. Based on Moodle online teaching platform, this research develops a mobile learning and resource sharing mode for college english translation based on 5G mobile communication technology, designs and implements a mobile learning model based on Moodle platform, and designs the system architecture, functional modules, learning mode and learning process, Finally, the main functional modules of the system model are implemented and tested. To promote mobile learning in the teaching field to play a helping role in a wide range. The experimental results show that the AKAZE algorithm is used to optimize the model, and the overall accuracy rate reaches 74.7%, and the test probability value P (siq)=0.00, which is significantly less than the significant level of 0.05. Therefore, we believe that the application of mobile learning instructional design mode will help students improve their academic performance.

The Role of Digital Educational Platforms in Shaping New Models of Economic Development

The article explores the role of digital educational platforms in shaping new economic development models, addressing the current challenges in the global economy. The study aims to analyze how these platforms impact human capital development and innovation ecosystems. Using analysis, modeling, and comparative methods, the research examines the interactions among participants in the educational process and their effects on economic growth. The findings reveal that digital educational platforms facilitate the creation of integrated ecosystems that bring together businesses, educational institutions, and regulators, thereby fostering economic activity driven by knowledge and innovation. The study illustrates the system of interaction between participants within a digital educational, highlighting how these platforms streamline and integrate educational processes into modern society, where universities are evolving into centers not only for knowledge accumulation and transfer but also for its commercialization. In this context, two global information systems are increasingly in demand: digital educational platforms and an innovation ecosystem organized by industry or region. The article characterizes key aspects of human capital development and the enhancement of economic competitiveness through the use of digital platforms. It offers recommendations for integrating these technologies into global educational processes and assesses their potential impact on sustainable economic development. The practical value of the study lies in its potential to guide the development of strategies for advancing digital education. The originality of the research is highlighted by its identification of new forms of economic activities emerging from interactions within digital educational platforms. Future research prospects include examining how digital educational platforms affect various socio-economic groups. Type of article: theoretical.

Computer-Mediated Communication: Application to Vocational English Education

Recent research on the use of computer-mediated communication (CMC) tends to focus on how CMC occurs and how to effectively apply Internet-based technologies into classrooms in general while little evidence has been found on the application of CMC tools to teach English language for workplace purposes. Therefore, this article aims to explore the use of CMC as an alternative platform for teaching English for vocational purposes. For this purpose, the current paper is based on library research combining synthesis and analysis of more than thirty empirical and non-empirical articles which were published in journals, conference proceedings, books, and conference presentations. The findings center around specifying: (i) the characteristics of vocational English education and the key theoretical frameworks and pedagogical models that underpin the use of CMC in teaching English for vocational purposes; (ii) the impacts of CMC mode on the students’ language learning outcomes and vocational skill development, and (iii) the needed preparation of educators for the successful use of CMC. The results offer insights into the growth of CMC use as an effective platform in vocational English education.

Enhancing Learning Analytics through Learning Management Systems Engagement in African Higher Education

In the African higher education landscape, the pervasive integration of Learning Management Systems (LMS) is reshaping the educational journey, offering both opportunities and challenges. This study delved into the intricate interplay between students’ engagement with LMS and its consequential impact on Learning Analytics (LA), specifically within the unique context of African higher education institutions. Employing the PRISMA systematic review approach, this research aimed to review significant work by researchers towards LMS and LA use in African universities in the form of contributing authors, keywords, citation statistics and growth patterns. The findings highlighted the transformative potential of LA and LMS use, which have the power to enhance both academic performance and the overall learning experience of African students. This research enhances the understanding of the complex relationship between LMS usage and LA in the African context, revealing how digital tools can address unique online learning challenges. As African institutions tackle 21st-century education challenges, this study provides a valuable roadmap for educators, administrators, and policymakers looking to leverage technology for meaningful educational outcomes. By contextualizing the findings within the African higher education landscape, this research contributes to the global discourse on the evolving role of digital platforms in shaping modern education. Keywords: Educational Technology, Digital Learning, Student Engagement, Learning Experience, Technology Integration

STHKT: Spatiotemporal Knowledge Tracing with Topological Hawkes Process

Knowledge Tracing (KT) is a method that seeks to forecast students’ future performance based on their historical interactions with intelligent tutoring systems. Various KT techniques have been developed from distinct perspectives, such as probability, logic, and deep learning, to scrutinize interaction sequences. However, most current methods predominantly concentrate on temporal or structural information, considering simple question sequences or interaction sequences, but fail to describe the topological dependencies between sequences, which can lead to changes in causal structures,as referred to as dynamic structural information in the paper. The dynamic information includes the clustering effect among concepts and questions, as well as the group effect among students and questions: Questions with the same knowledge concepts tend to present increasingly similar response patterns in the sequence, and concurrently, students who answer similar questions often exhibit closer knowledge states. We introduce the STHKT method, which employs a tripartite heterogeneous graph to capture relationships among concepts, questions, and students. By incorporating temporal information through a topological graph, we employ two Graph Convolution Networks (GCNs) to model the two effects separately. Following this, we apply the Hawkes Process to introduce a spatiotemporal attention mechanism that combines both effects. Through comparative experiments, ablation studies and case studies, we validate the efficacy of key components in the model. Experiment results indicate that the STHKT model can effectively model the two major effects, integrate dynamic structural information, and to some extent improve the accuracy of predicting students’ response probabilities. It is the first time that these two effects have been considered in the process of knowledge tracing, and it is adaptable to large-scale online education platforms.

Perceived Quality of Higher Educational Institutions in Maharashtra: Students Perspective

In recent times, Indian education system has seen an upsurge in post graduate management institutions due to growing demand of management discipline. Mere existence to function in the system will certainly not help the institutions in the long run. Service quality is often seen as a good competitive strategy that not only service organizations, but also educational institutions worldwide employ to increase their competitiveness in the tertiary sector. Hence, providing quality education is the need to be addressed here. Given a fact that students have become more informative and are exposed to different educational platforms, institutions are readily being at their disposal. The present study was carried out in Maharashtra, India where 26 Institutes from three regions Pune, Nagar and Nashik participated in the study. The objectives of study were to analyze students’ perception on the quality of higher education based on their demographic profile and impact of diverse educational background of students on perceived quality of education. SERVQUAL was used to collect the data. The collected data was analyzed using descriptive statistics viz chi-square eta and regression analysis. The results of the study revealed that students’ perception on the quality of higher education and their gender, graduation and region are independent. There is no impact of diverse educational background of students on perceived service quality of HEIs.

Morocco's Webinars Ignite Global Academic Resilience in Doctoral Research

General Background: The COVID-19 pandemic triggered significant disruptions in education worldwide, compelling a shift to online learning across various contexts, including in Morocco. Specific Background: In response to this challenge, the Faculty of Letters and Human Sciences at Mohammed V University in Rabat initiated the "Language, Culture, and Society" (LCS) webinar series. This program provided a virtual platform for doctoral students, aiming to sustain academic progress and emotional well-being during the crisis. Knowledge Gap: Despite the proliferation of online educational initiatives during the pandemic, there is limited research on how such programs specifically impact doctoral students' academic and psychological resilience. Aims: This article aims to explore the transformative role of the LCS webinar series in enhancing the academic journey and personal growth of doctoral students, particularly in alleviating challenges such as despair and reader's block. Results: The LCS webinars emerged as a crucial support mechanism, facilitating academic discourse, skill development, and psychological reinforcement. The program significantly contributed to restoring confidence, refining research trajectories, and fostering a culture of collaboration among an international online community. Novelty: This study provides a unique narrative reflection on the impact of a specific online educational program during a global crisis, emphasizing the dual academic and psychological support offered to doctoral students. Implications: The findings underscore the importance of online platforms in higher education, particularly in crisis contexts. The success of the LCS webinars suggests that similar initiatives could be replicated to support doctoral students globally, offering sustained academic and emotional support through accessible, high-quality online resources. Highlights: Webinar Impact: Enhanced academic progress and growth. Psychological Support: Overcame despair with emotional reinforcement. Global Collaboration: Fostered international scholarly connections. Keywords: COVID-19, online learning, doctoral students, webinars, academic resilience

Learning and Control Platform “Kahoot!”: Theory and Usage Features in ASIPCS

The study examined the place of modern information technologies in education and the importance of “gamification” technology in the organization of secondary and higher education. It was revealed that the most common educational monitoring platform, “Kahoot,” has significant advantages compared to traditional approaches to organizing the educational process. The use of this platform in the process of training bachelors and masters, as well as in advanced training courses for coaches at the Armenian State Institute of Physical Culture and Sport (ASIPCS), showed great interest among students in the “Kahoot” service, a high assessment of the capabilities of this platform in training, consolidation, and control of theoretical knowledge.

Substitutor or Assistant: The Double-Edged Sword Effect of Artificial Intelligence Images on OTPs

Recently, the green concept has become integral to education, leading to the rise of paperless online teaching. With the rapid development of online teaching platforms (OTPs) due to the pandemic, studies on user behavior have gained momentum. However, most studies have focused on students’ online learning attitudes and behaviors, neglecting in-depth analysis of teachers’ behaviors on OTPs. OTPs can either assist or substitute teachers, enhancing efficiency but also causing anxiety. This paper proposes reframing OTPs as assistants to reduce teachers’ resistance. We investigate if the OTP image (assistant vs. substitutor) impacts teachers’ satisfaction in a specific online teaching context, exploring its explanatory mechanisms. A study of 2*2 group experiments revealed that teachers were less threatened by the assistant OTP image and thus more satisfied. Experiment 1 confirmed that the OTP image influenced teachers’ willingness to recommend and satisfaction. Experiment 2 again tested the effect of different images of OTP (facilitator vs. substitute vs. control group) on teacher satisfaction, and the pie verified the mediating role of identity threat in this effect. Experiment 3 verified that self-affirmation as a moderating variable mitigates identity threats due to the alternative image of the OTP. Therefore, in the future promotion of AI products, more emphasis should be placed on assisting users rather than completely replacing traditional human hands, thus weakening the identity threat posed by AI products to users. The findings of this study enrich the study on teachers’ attitudes towards OTPs, dissect the sources of users’ (teachers’) satisfaction with OTPs from the perspective of product/brand (OTP) image, and provide guidance on how OTPs can choose the appropriate image positioning and promotional language.

Machine Learning-Based Personalized Learning Path Decision-Making Method on Intelligent Education Platforms

With the rapid development of information technology, the application of intelligent education platforms has become increasingly widespread. Traditional teaching methods struggle to meet the demands for personalized learning. Personalized learning path decision-making methods, which analyze learners’ behavioral data and mastery of knowledge points, tailor learning paths for each individual. Current research indicates that these methods can significantly improve learning efficiency and effectiveness. However, existing personalized learning path decision-making methods still have shortcomings in predicting the difficulty of knowledge points and dynamically adjusting path recommendations. This paper proposes a machine learning-based personalized learning path decision-making method, focusing on two main aspects: predicting the difficulty of knowledge points for personalized learning and integrating knowledge point localization for personalized learning path decisions. Through accurate prediction of knowledge point difficulty and dynamically optimized learning path recommendations, this method provides more refined and personalized learning support on intelligent education platforms, aiming to enhance learners’ learning experience and outcomes.

Strategies and Implementation of Exploring the Integration of Artificial Intelligence in Ideological and Political Education

The rapid evolution of artificial intelligence (AI) technology heralds significant transformations in education, especially in ideological and political education, where traditional teaching methods are being reassessed due to mounting challenges. This paper embarks on a mission to investigate how AI technology can revolutionize the delivery of political science courses by adopting a “human-computer collaboration” model. The central aim is to enhance the effectiveness and quality of teaching while stimulating students' critical thinking skills. It delves into the landscape and potential applications of AI technology in this field, emphasizing the role of intelligent teaching assistants in augmenting teachers' capabilities for lesson planning and delivery. This study not only outlines the design and implementation of AI tools but also emphasizes their potential to foster a more engaging and intelligent learning environment. By doing so, it contributes to the discourse on leveraging AI to advance teaching platforms and classroom practices, thereby enhancing the educational experience.