Emerging Trends in Global Education refer to the evolving educational philosophies, technological innovations, pedagogical approaches, and institutional transformations that are redefining teaching, learning, research, governance, and lifelong education across the world. Rapid advancements in Artificial Intelligence (AI), Industry 5.0, digital transformation, quantum computing, immersive technologies, intelligent automation, and globally connected knowledge networks are reshaping the objectives and delivery of education. Higher education institutions are no longer confined to traditional classroom instruction; instead, they are becoming dynamic ecosystems that integrate technology, interdisciplinary research, innovation, sustainability, entrepreneurship, and global collaboration. As societies transition toward knowledge-driven and technology-enabled economies, universities must continuously adapt to emerging trends that prepare graduates for professions, challenges, and opportunities that are constantly evolving.The primary objective of emerging trends in global education is to develop educational systems that are flexible, inclusive, technology-enabled, learner-centred, and capable of addressing the complex demands of the twenty-first century. Universities increasingly recognize that graduates require more than academic knowledge to succeed in rapidly changing environments. They must possess critical thinking, creativity, digital literacy, ethical reasoning, adaptability, intercultural competence, entrepreneurial abilities, collaborative leadership, and lifelong learning skills. Emerging educational models therefore emphasize competency-based learning, experiential education, interdisciplinary collaboration, personalized instruction, and continuous professional development while encouraging innovation and responsible citizenship.Artificial Intelligence has become one of the most influential drivers of educational transformation by enhancing teaching, learning, research, administration, and institutional decision-making. AI-powered learning platforms provide adaptive instruction, intelligent tutoring, automated assessment, predictive analytics, multilingual communication, accessibility support, and personalized learning experiences that accommodate diverse learner needs. Universities increasingly employ AI to optimize curriculum design, monitor student progress, improve retention, strengthen academic advising, and support evidence-based institutional planning. AI also accelerates research through intelligent literature analysis, simulation, predictive modelling, data mining, and knowledge discovery. Nevertheless, responsible implementation requires ethical governance that ensures transparency, fairness, accountability, privacy protection, explainability, inclusiveness, and respect for human rights.Industry 5.0 represents a significant evolution beyond industrial automation by emphasizing collaboration between intelligent technologies and human creativity. Within higher education, Industry 5.0 encourages universities to prepare graduates capable of working alongside Artificial Intelligence, robotics, cyber-physical systems, advanced manufacturing, intelligent healthcare technologies, sustainable engineering, and digital innovation ecosystems. Educational programmes increasingly integrate technological expertise with ethical leadership, emotional intelligence, sustainability, and human-centred innovation. This balanced approach ensures that technological progress enhances human well-being while supporting inclusive economic development and environmental responsibility.Digital transformation has fundamentally redefined educational delivery by integrating cloud computing, learning management systems, digital libraries, blockchain, Internet of Things (IoT), virtual laboratories, intelligent communication platforms, big data analytics, and collaborative online learning environments. Students now access educational resources anytime and anywhere through digital devices, enabling flexible learning pathways that accommodate diverse educational and professional needs. Virtual classrooms, hybrid education, online assessment, remote research collaboration, and digital credentialing have become integral components of higher education. Universities continue to invest in secure digital infrastructure that enhances educational accessibility, institutional efficiency, cyber security, and global academic collaboration.Research and innovation remain central to emerging educational trends because universities generate scientific knowledge and technological solutions that address societal challenges. Interdisciplinary research increasingly combines Artificial Intelligence, biotechnology, quantum computing, environmental science, healthcare, economics, engineering, social sciences, and educational technology to solve complex global problems. Universities establish innovation centres, technology incubators, entrepreneurship hubs, interdisciplinary laboratories, and collaborative research networks that encourage creativity, commercialization, and responsible technological advancement. Such initiatives strengthen national innovation ecosystems while preparing students to become researchers, entrepreneurs, and future leaders.Curriculum development is undergoing continuous transformation to reflect emerging technologies, evolving labour market requirements, and global sustainability priorities. Universities increasingly adopt competency-based education, project-based learning, interdisciplinary programmes, experiential learning, micro-credentials, digital certifications, flexible academic pathways, and lifelong learning opportunities. Subjects such as Artificial Intelligence, data science, cyber security, sustainability, digital ethics, entrepreneurship, innovation management, climate resilience, quantum technologies, and global citizenship are being integrated across disciplines. Modern curricula emphasize practical application, collaborative learning, and real-world problem-solving while maintaining strong theoretical foundations.Faculty members remain central to educational transformation despite rapid technological advancement. Their role has expanded from knowledge transmission to mentoring, facilitation, research leadership, innovation management, interdisciplinary collaboration, and ethical guidance. Educators integrate intelligent educational technologies into teaching while encouraging critical inquiry, creativity, collaborative learning, reflective practice, and evidence-based reasoning. Continuous professional development enables faculty members to remain current with emerging technologies, responsible AI, digital pedagogy, sustainability initiatives, and international educational standards, thereby ensuring high-quality learning experiences.Student-centred learning has become a defining characteristic of future education because learners increasingly require personalized educational experiences that reflect their interests, abilities, aspirations, and career objectives. Universities provide adaptive learning pathways, individualized academic support, experiential learning opportunities, entrepreneurship programmes, global mobility initiatives, digital portfolios, career counselling, and interdisciplinary projects that encourage students to take active responsibility for their learning. Such approaches strengthen learner motivation, creativity, resilience, communication, leadership, and lifelong learning capabilities while preparing graduates for dynamic professional environments.Institutional governance provides the strategic framework for implementing emerging educational trends effectively. Universities establish digital transformation strategies, innovation policies, sustainability frameworks, ethics committees, quality assurance systems, cyber security protocols, research governance mechanisms, and international partnership offices that coordinate institutional modernization. Transparent governance promotes accountability, stakeholder participation, financial sustainability, responsible technology adoption, and evidence-based decision-making while ensuring that educational innovation aligns with institutional missions and societal expectations.International collaboration has become increasingly important because educational innovation benefits from global partnerships and shared expertise. Universities participate in multinational research projects, joint degree programmes, student and faculty mobility initiatives, international conferences, virtual exchange programmes, collaborative innovation ecosystems, and global academic networks. These partnerships facilitate knowledge sharing, technological advancement, intercultural understanding, and collaborative problem-solving while supporting the implementation of the United Nations Sustainable Development Goals (SDGs) and strengthening global educational quality.Sustainability remains a fundamental principle guiding emerging educational trends because future educational systems must balance technological advancement with environmental protection, social inclusion, and economic resilience. Universities integrate sustainability into teaching, research, campus operations, innovation, entrepreneurship, governance, and community engagement while encouraging responsible consumption, renewable energy, climate resilience, ethical leadership, circular economy practices, and environmentally responsible technological development. Sustainable education ensures that innovation contributes positively to both present and future generations.Assessment and continuous improvement are evolving alongside technological innovation. Universities increasingly employ competency-based assessment, digital portfolios, project-based evaluation, learning analytics, adaptive testing, peer assessment, reflective learning, and AI-assisted evaluation to measure student achievement comprehensively. Artifici
Game-based teaching (GBT) has gained widespread adoption in modern education, yet teachers bear heavy burdens in designing GBT activities and interpreting student learning performance, while centralized educational data storage brings prominent security and credibility risks. To tackle the above bottlenecks, this paper proposes SmartTA, an integrated teaching assistant system combining GBT recommendation modules, automated machine learning (AutoML), and blockchain. Specifically, SmartTA supplies customized GBT cases and exam scoring suggestions for teachers, and leverages AutoML to automatically mine student learning behaviors with zero coding requirements. Three groups of experiments are conducted to validate the system: AutoML achieves a maximum prediction accuracy of 93% on six public educational datasets; the Hyperledger Fabric-based blockchain prototype enables data insertion with an average latency of approximately 2.2 seconds and query latency of approximately 150 ms; 20 frontline educational practitioners provide 85% positive user feedback. The experimental results suggest that SmartTA may help reduce teachers’ lesson preparation workload, support improved instructional quality, while enabling tamper-resistant data storage via blockchain. This study realizes the practical fusion of AutoML and blockchain for GBT scenarios, and establishes a novel, secure, data-driven teaching assistance paradigm that is accessible to non-technical educators.
Abstract Online Education in Higher Education is rapidly evolving through the integration of Large Language Model (LLM)-powered intelligent systems, which enable personalized tutoring, dynamic content generation, and automated assessment. However, the widespread adoption of LLMs in education is hampered due to their inherent limitations, including susceptibility to hallucinations, insufficient domain-specific knowledge validation, and output inconsistency. These deficiencies can lead to misleading or erroneous content, potentially causing significant negative learning outcomes. A core challenge lies in ensuring that such errors are immutably logged and traceable, thereby establishing a mechanism for accountability among the entities deploying these LLM services. To address these challenges, this paper proposes a novel framework that Integrates LLM with consortium blockchain for personalized and verifiable online education. Our design features a synergistic architecture in which LLM based services provide the intelligent educational interface, while a permissioned consortium blockchain serves as a secure and tamper proof ledger. This blockchain infrastructure records critical educational transactions ranging from learning process data and academic credentials to the outputs generated by the LLMs. This integration not only secures academic credentials but also establishes a fully auditable trail, making it possible to trace responsibility for educational deficiencies caused by AI errors. Collectively, this work demonstrates a robust and accountable framework for leveraging LLMs in education, effectively mitigating the risks of AI inaccuracies through the verifiable and immutable nature of consortium blockchain.
Open access
Artificial Intelligence in Healthcare and Education
Online Learning and Analytics
Intelligent Tutoring Systems and Adaptive Learning
The contemporary education landscape is often marred by escalating costs and centralized pedagogical structures, which collectively create significant barriers to entry for millions of potential learners worldwide. This paper presents \textbf{Skill Link}, a sophisticated decentralized platform designed to democratize skill acquisition through a specialized credit-based barter system. Unlike conventional e-learning platforms that rely on traditional currency transactions, Skill Link enables a frictionless exchange of knowledge by utilizing a virtual credit economy where participants earn and spend "learning credits." To address the critical issue of credential fraud in decentralized environments, the platform integrates Ethereum-based blockchain technology to ensure the absolute immutability and verifiable authenticity of all earned certificates. Key innovations include a multi-tiered course classification system, an automated mock assessment framework with negative marking capabilities, an intelligent context-aware AI assistant powered by advanced language models, and a rigorous verification mechanism for professional social links (LinkedIn, GitHub, Indeed). Developed using the robust Django framework, Python-based Web3 utilities, and a secure PostgreSQL/SQLite back-end, Skill Link provides a highly secure, transparent, and scalable ecosystem for peer-to-peer knowledge sharing, ultimately fostering a global community of experts and lifelong learners. The system's architecture emphasizes data integrity through atomic transactions and cryptographic verification, ensuring a trustless environment for global skill exchange.
This article presents cutting-edge developments in data-passing architectures that are revolutionizing AI-driven learning systems. By examining recent breakthroughs in streaming data architectures, data lakehouse designs, and feature stores, the article identifies how these innovations overcome traditional bottlenecks in distributed training environments. It explores critical challenges in multi-platform data passing, including data quality maintenance, security considerations, and performance optimization. The discussion extends to self-healing architectures that significantly enhance system resilience through autonomous fault detection and recovery mechanisms. Additionally, emerging trends in data-sharing protocols, from blockchain-based decentralized architectures to federated learning approaches, demonstrate how collaborative AI ecosystems can maintain privacy while maximizing data utility. Through a comprehensive analysis of these architectural innovations, the article illustrates how organizations can create more powerful, resilient, and collaborative AI-driven learning systems that operate seamlessly across previously siloed environments.
In recent years, Learning Management Systems (LMS) have acquired substantial appeal, notably because to the COVID-19 pandemic, delivering greater efficacy and efficiency. Within LMS, online tests have evolved as a crucial instrument for measuring students’ performance and knowledge of course content, playing a vital part in deciding their development. It is critical that online test results be both trustworthy and easily accessible. Students' grades might be negatively affected by any security flaw, such hacking. Conventional online test systems frequently store data centrally in databases like MySQL, leaving them subject to unwanted access and modification. Secure, peer-to-peer administration and assessment of academic tests is made possible in this article using a blockchain-based infrastructure. To guarantee data integrity, the framework utilises hashing algorithms. To strengthen security, it incorporates proof of stake processes. Blockchain effectively protects data integrity due to its decentralised data storage and the use of cryptographic hashing for each block. The study illustrates the usage of blockchain for designing online tests, recording each question and response directly on the blockchain. We were able to do this by developing a module that communicates with Moodle, an LMS. By comparing it to Moodle's default centralised storage, our addon alters the storage of exam results, making the data stored on the blockchain safe and impenetrable. Exam data is securely encrypted using the blockchain, which prevents tampering and ensures its integrity. Based on our findings, there are no inconsistencies when comparing data saved on the blockchain to Moodle's conventional method. To safeguard student information from tampering, the blockchain network offers a trustworthy and unchangeable platform. Finally, our blockchain-based paradigm provides a strong answer to the problem of how to make online test scores more secure and trustworthy. We guarantee data integrity and transparency by using blockchain's decentralised and tamper-proof nature. This allows for a more reliable evaluation of academic achievement.
Fei Ren, Bo Zhao, Jun Wang, Juxiang Zhou · 5 authors
With the rapid development of information technology, blended learning has become a crucial aspect of modern education. However, the fragmented use of various teaching platforms, such as Xuexitong and Rain Classroom, has led to the dispersion of teaching data. This not only increases the cognitive load on teachers and students but also hinders the systematic recording of teaching activities and learning outcomes. Moreover, existing blended learning evaluation systems exhibit significant shortcomings in large-scale data storage and secure sharing. To address these issues, this study designs a blended teaching evaluation management system based on blockchain and searchable encryption. First, an on-chain and off-chain collaborative storage model is established using the Ethereum blockchain and the InterPlanetary File System (IPFS) to ensure secure and large-scale storage of student work data. Next, a role-based access control scheme utilizing smart contracts is proposed to effectively prevent unauthorized access. Simultaneously, a searchable encryption scheme is designed using AES-CBC-256 and SHA-256 algorithms, enabling data sharing while safeguarding data privacy. Additionally, the smart contract comprehensively records students’ grade information, including weekly regular scores, midterm scores, final scores, overall scores, and their rankings, ensuring transparency in the evaluation process. Based on these technical solutions, a general-purpose teaching evaluation management system (B-Education) is developed. The experimental results demonstrate that the system accurately records teaching activities and learning outcomes, improving the transparency of teaching evaluations while ensuring data security and privacy. The system’s gas consumption remains within a reasonable range, demonstrating good flexibility and usability. Educational institutions can flexibly configure course evaluation criteria and adjust the weighting of various grades based on their specific needs. This study provides an innovative solution for blended teaching evaluation, offering significant theoretical value and practical implications.
Abstract The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the current state of the art is in terms of the pedagogical applications and technological functions of these conversational agents and to identify the key existing research gaps, and future research directions, in the field. A literature survey of the state of the art of pedagogical AI conversational agents in higher education was conducted. The resulting literature sample (n = 92) was analysed using thematic template analysis, the results of which were used to develop a conceptual framework of pedagogical conversational agents in higher education. Furthermore, a survey of the state of the art was then presented as a function of the framework. The conceptual framework proposes that pedagogical AI conversational agents can primarily be considered in terms of their pedagogical applications and their pedagogical purposes , which include pastoral , instructional and cognitive , and are further considered in terms of mode of study and intent . The technological functions of the agents are also considered in terms of embodiment (embodied/disembodied) and functional type and features . This research proposes that there are numerous opportunities for future research, such as, the use of conversational agents for enhancing assessment, reflective practice and to support more effective administration and management practice. In terms of technological functions, future research would benefit from focusing on enhancing the level of personalisation and media richness of interaction that can be achieved by AI conversational agents.
Open access
AI in Service Interactions
Online Learning and Analytics
Intelligent Tutoring Systems and Adaptive Learning
Alexander Mikroyannidis, Allan Third, John Domingue
Today’s fast-paced economy and the impact of the COVID-19 pandemic on the job market have made more prominent the need for flexible accreditation and lifelong learning. This paper introduces a novel approach for supporting lifelong learning using Smart Badges as Blockchain-based decentralised micro-accreditation. The implementation of this approach is based on granular verification, which has been achieved via LinkChains MerQL. A user evaluation has been conducted with stakeholders from the education community, the results of which have indicated the strengths and weaknesses of this approach. Liaising with stakeholders from the education community has provided valuable insights into the different aspects of lifelong learning that require support, as well as into the training needs of the education community related to the use of decentralisation technologies.
This research paper explores the intersection of zero-knowledge proofs (ZKPs) and machine learning (ML), presenting a comprehensive overview of recent advancements, applications, and challenges in this fast growing area. The jointers of ZKPs and ML techniques shall go a meter further to fuse privacy, security, and integrity in a number of solutions, which include forming of groups for data sharing and safe machine learning. Through the investigation of the well-respected sites in that area and also the thorough description of formulas and their experimental outcome, this paper looks for the clarification of the current state of affairs and the possible future directions of ZKPs in the AI world. By inserting the verification mechanism of ZKPs into machine learning ecosystem, it allows devising novel solutions for the problems of privacy and confidentiality that have for long been not solved. With this approach, the concatenation of parties collectively performs the process of dealing with private inputs without revealing any of these data and this, in return, opens the possibilities of secure multi-party computation. Furthermore, ZKPs protect data sharing as it gives people the opportunity to construct confidential data and share them to model training without compromising any one’s private details. Being a part of the dynamic conversations, which focus on the game-changing capacity of transparent zero-knowledge proofs (ZKPs), this paper brings the role of ZKPs in preserving the confidentiality and integrity of artificial intelligence (AI) applications into the centre of attention. As scientists still fight to improve protocols and circumvent computational complications, ZKPs are likely to establishment as critical tools in the effort to increase ML systems in the digital sphere.
Open access
Online Learning and Analytics
Intelligent Tutoring Systems and Adaptive Learning
Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar · 5 authors
Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data on student performance and behavior. This enables them to create personalized learning experiences that cater to the unique needs of each student. Machine learning can also track and assess student progress, providing educators with valuable insights into the effectiveness of their teaching strategies. Furthermore, it can optimize the design of physical education curricula and assessments, making them more efficient and effective. Additionally, machine learning offers a more objective and accurate approach to evaluating and grading students. This paper discusses the challenges and opportunities associated with integrating machine learning into physical education, including ethical considerations and potential limitations.
Harshitha Reddy Chitukula, S. Phanindra Reddy, M.D.N. Akash and Ramesh Karnati In this paper, we explored the potential impact of Web3 technologies on the future of social media. Web3 technologies, such as blockchain and decentralized networks, offer new opportunities for social media users to own and control their data, leading to increased privacy and security.
Our study builds on theories emphasizing connectivity for learning on social media to study learning networks on Twitter (e.g., Haythornthwaite, 2019;Siemens, 2005).Considering the nature of power law distribution on social media (Yoshida, 2021), we focus on a group of influencers from the Non-Fungible Token (NFT) community to uncover online learning networks and their emergent practices.By employing an exploratory Social Network Analysis (Nooraie et al., 2020) and qualitative analysis, we examine the way in which influencers form learning relations through conversational interactions and content, and the modalities and discursive strategies used in their tweets.We find that influencers built a strong learning network through sustained interactions and content relations among themselves and with a wide community outreach.This analysis contributes to the way that learning networks are analyzed and found on Twitter.
Tarang Rajpal, Hrishikesh Patil, Varad Deshmukh, Dhananjay Pai · 5 authors
ChainBank is an innovative decentralized autonomous organizational system specifically designed to support students in improving their financial habits. Students have the opportunity to invest their money in a distributed pool and receive tokens in return, while also gaining the ability to actively engage in decision-making through voting on proposals. ChainBank offers its members a powerful voting feature, enabling them to collectively make important decisions regarding the platform’s operations. ChainBank’s primary objective is to target regular students who often struggle with irregular financial habits. Engaging with ChainBank helps students to develop essential skills and knowledge that will positively impact their financial well-being both now and in the future.
The Internet has revolutionized education and learning, presenting both opportunities and challenges with the continuous evolution of web-based technologies. The earlier version of the web, known as Web 1.0, was primarily a readonly medium, while Web 2.0 allowed for greater interactivity with read/write capabilities. Now, the emerging version of the web, Web 3.0, is considered to be a technologically advanced medium that not only facilitates read/write capabilities but also enables a machines to carry out some of the thinking that was previously expected only of humans. In a relatively short period of time, Web 2.0 and Web 3.0 have introduced new tools and technologies that have greatly facilitated web-based education and learning. This paper will explore the definition, evolution, and characteristics of Web 3.0, as well as discuss potential future technologies, trends, tools, and services that can support online learning, personalization, and knowledge construction powered by the Semantic Web.
Abstract The potential of the metaverse in the field of education is an area of increasing interest, with many researchers exploring the space to increase the ease and efficacy of student education while reducing time and labor requirements to deliver effective teaching. However, there has been little work into the systematic and technological aspects of delivering education through the metaverse. To fill this gap, we propose a metaverse education system that takes good advantages of virtual reality and Web3 blockchain techologies to create a social learning environment. With this added emphasis on social aspects, learners are able to socialize and engage in collaborative efforts to improve their own knowledge. Using blockchain technology, the system can also help to ensure security and transparency while also keeping progression and grading fair for all participating students.
Blockchain technology is a distributed database with features such as no forgery, full traceability, openness, and transparency which is superior in establishing trust mechanisms and brings new opportunities for finance, healthcare, technology, and education. As a required course of all universities in China, College English has a large demographic covering millions of students. But the traditional EFL summative assessment model fails to fully reflect the L2 learner’s learning process and increment performance. The current paper focuses on the novel applications of blockchain in the educational domain and how blockchain technology reshapes the EFL Formative Assessment framework in the consensus mechanism to achieve a decentralized and highly trusted learning process record and evaluation. This innovative approach aims at improving the openness, transparency, and fairness of the EFL learning process by recording and monitoring the teachers’ and students’ behaviors. The research findings of this paper provide preliminary exploration for L2 evaluation and supply some inspiration to policymakers, EFL practitioners, and technology developers about the potential usages of digital credentials anchored on blockchains.
Md. Amir Hossain Fahad, Redoyan Chowdhury, Hasan-Al– Shabbir
Web development has greatly advanced from basic static web pages to dynamic, datadriven applications utilizing modern technology. Specifically, this article looks at the past, present, and future of web development, focusing on the importance of artificial intelligence (AI), progressive web apps (PWAs), security measures, and performance improvement. The adoption of contemporary frontend and backend technologies has improved user experience, scalability, and security, while nascent trends like Web3, blockchain integration, and decentralized apps (DApps) are poised to transform the digital environment. Even with these advances, there are still problems, such as cybersecurity risks, accessibility issues, and the need to keep improving online performance. This evaluation shows how important it is to welcome new technologies while also addressing important problems in order to create a safe, effective, and welcoming digital world. Future research must concentrate on enhancing cybersecurity frameworks, refining AI-driven web development, and investigating decentralized computing paradigms. Utilizing advanced technology, web developers may design more intelligent, responsive, and user-centric online apps that satisfy the increasing expectations of the digital age.
Maria José Sousa, Francesca Dal Mas, Sónia P. Gonçalves, Davide Calandra
Several scholars have examined the potential use of AI and Blockchain in education, primarily focusing on the contributions of such technologies with a goal to improve learning possibilities and outcomes for students [...].
Abstract This study explores the use of blockchain in the course design and evaluation in Chinese universities, and explores the value of teachers’ views and experiences on blockchain in the course design. Previous studies have shown that blockchain has a positive effect on the improvement of online teaching management and evaluation quality. Most of the current research focuses on the management of online teaching by using blockchain, and this qualitative case study investigates the design and evaluation of online course based on blockchain by five teachers of different specialties. Semi-structured interviews and course materials were collected from five teachers for a TPACK framework analysis. The result of the survey emphasizes that the redesign of online courses based on blockchain can improve the matching between blockchain and courses, the quality of teaching and the trust of various parties in online education. The block chain-based the online course of both theory and practice design and evaluation, which is oriented by the index method of capability evaluation, is an appropriate idea and has achieved good results. The experimental course focuses on the integration of blockchain and experimental platform. The immersive and interactive course presentation and the personalized examination based on machine learning are effective. But follow-up should pay attention to the different requirements of course design of different disciplines, using a variety of data sources for analysis, to take measures to enhance the enthusiasm of teachers to adopt new technologies.
In web-based education and learning, the constant growth of the Internet has thrown up inconceivable opportunities and problems. Web 3.0, the most recent version of the web, is believed to be a technologically sophisticated medium that allows users to Read/Write/Execute and also allows robots to perform some of the thinking formerly reserved for human beings. Online marketing with web 3.0 is also known as intuitive Web, which is a Semantic Web that allows web services to communicate with one another. Individualized and behavioral Web 3.0 will be the norm. Web 3.0 has generated new tools and technology for aiding web-based education and learning in a short amount of time. To begin, this article addresses certain Web 3.0 concepts, development, and features. We explored the influence of web 3.0 on marketing in this study, as well as the many aspects that contribute to marketing uplift. Web 3.0 is a word used to describe the interaction that occurs as a result of the evolution of Web use and the transformation of the Web into a database. Smart web with intelligence analysis, personalisation, interoperable web, virtualization (virtual 3D environments), and multimedia are some of the most significant elements of these technologies. The broad adoption of Web 3.0 technologies in educational settings has resulted in the creation of e-learning 3.0. Web 3.0 is defined by facilitating cooperation and is powered by co-creation tools.
M.E. Sousa‐Vieira, David Ferrero-Castro, J.C. López-Ardao
Badges are non fungible tokens used to document or certify achievements in academics or in any other domain. Besides their utility as proof of achievement, badges are of interest in higher education as pure incentives to push the students and learners in general toward pursuing well-defined goals and skills. In this respect, badges can be naturally incorporated into digital learning platforms also as part of informal learning activities, and stimulate participation, merit, and visibility for the students. However, the level of engagement of learners into these learning activities depends crucially on how the system of badges and rewards has been designed and on how it is applied, if it is to be used effectively. In this paper, we report on the design and implementation of a smart badges system, and an example of its use inside a gamification methodology for informal learning in a master level course, and discuss the benefits and the observed gains in learning performance that can be obtained.
In institutes of higher learning, most of the time course material development and delivery follow a centralized model which is fully lecturer-controlled. In this model, engaging students as partners in learning is a challenging problem as: 1) students are usually hesitant to contribute due to the fear of getting it wrong, 2) not much incentive for them to put in the extra effort, and 3) current online learning systems lack adequate facilities to support seamless and anonymous interactions between students. In this work, we propose EtherLearn, a blockchain based peer-learning system to distribute the control of how course material and formative assessments could be developed and delivered over the set of stakeholders in the particular course. EtherLearn leverages features of the rising blockchain technology, e.g., decentralization, anonymity, transparency and security to address the aforementioned concerns in university learning environments. To this end, we have successfully implemented a proof of concept for EtherLearn based on the Ethereum blockchain network. We have also conducted preliminary evaluations to demonstrate that it can be useful in decentralizing learning resource creation and student sharing in an encouraging teaching and learning environment.
Anissa Cheriguene, Taieb Kabache, Chaker Abdelaziz Kerrache, Carlos T. Calafate · 5 authors
Technology advancements promote a redefinition of traditional instructional methodologies, as well as the roles of teachers and learners towards an efficient e-learning ecosystem. To date, all existing solutions are combined with the conventional face-to-face learning process. However, the latter can be unexpectedly hindered in some emergency cases, like the Coronavirus (COVID-19) pandemic. To handle such unexpected scenarios, this paper presents NOTA, a novel online teaching and assessment scheme that takes advantage of Blockchain technology to maintain the expected teaching quality and assessment fairness while respecting the courses' and examinations' schedule. Besides, NOTA also motivates both learners and teachers to persist in their endeavours, even from home, through Blockchain's incentive strategies. The preliminary results taken during the CoronaVirus period showed a very high satisfaction ratio, exceeding the 90%. This made us feel very optimistic about the potential of our proposal when deployed at a larger scale.