教育数字化转型

The digital transformation of teaching processes is guided and supported by the use of technological, human, organizational and pedagogical drivers in a holistic way. Education 4.0 aims to equip students with cognitive, social, interpersonal, technical skills, among others, in the face of the needs of the Fourth Industrial Revolution and global challenges, such as mitigating the causes and effects of climate change based on people's awareness. This work presents the development and experimentation of a method, called TADEO -- acronym in Portuguese language to Transformação Digital na Educação (digital transformation in education), to guide the design and application of teaching and learning experiences from groups of drivers of the digital transformation in education, aiming to achieve Education 4.0 objectives. The TADEO method was applied in the context of classes of basic subjects of elementary and higher education to increase students' understanding of climate change through the development of projects to mitigate environmental problems caused by anthropogenic action and, at the same time, exercise students the soft and hard skills required by 21st century learning and work. The results of the evaluations of students and educators participating in the teaching and learning experiences guided by the TADEO method point to the achievement of the expected purposes.

A significant number of educational stakeholders are concerned about the issue of digitalization in higher educational institutions (HEIs). Digital skills are becoming more pertinent throughout every context, particularly in the workplace. As a result, one of the key purposes for universities has shifted to preparing future managers to address issues and look for solutions, including information literacy as a vital set of skills. The research of educational technology advances in higher education is now being discussed and debated, with various laws, projects, and tactics being offered. Digital technology has been a part of the lives of today’s children from the moment they are born. There are still many different types of digital divisions that exist in our society, and they affect the younger generation and their digital futures. Today’s students do not have the same level of preparation for the technology-rich society they will have. Universities and teaching should go through a significant digital transformation to fulfill the demands of today’s generation and the fully digitized world they will be living in. The COVID-19 pandemic has quickly and unexpectedly compelled HEIs and the educational system to engage in such a shift. In this study, we investigate the digital transformation brought about by COVID-19 in the fundamental education of the younger generation. Additionally, the study investigates the various digital divides that have emerged and been reinforced, as well as the potential roadblocks that have been reported along the way. In this paper, the study suggests that research into information management must better address students, their increasingly digitalized everyday lives, and basic education as key focus areas.

This study addresses a gap in the literature regarding the implementation of digital strategies in educational institutions, particularly universities. Despite significant advancements in the development of digital strategies, there remains a lack of commitment and vision for their effective implementation. This study systematically reviewed the literature to evaluate digital transformation in education across three dimensions: campus environment, teaching methods, and learning experiences. Employing the Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines, this study identified ten pertinent articles for thematic analysis. These findings highlight the critical role of digital transformation in various aspects such as data collection, management, academic advising, and personalized learning, revealing a trend towards improved educational outcomes through blended learning, video conferencing, AR/VR, and adaptive learning technologies. This research underscores the transformative impact of digital strategies on education, suggesting a paradigm shift in teaching/learning methods, emphasizing the need for educational institutions to embrace these changes proactively.

This study meticulously investigates the multifaceted dimensions of digital transformation within the educational sector, aiming to elucidate its framework, implementation strategies, impacts on educational outcomes and community implications. Utilizing a comprehensive approach, the research amalgamates an in-depth examination of various case studies and best practices to offer a thorough understanding of integrating digital technologies into educational systems. The methodological approach encompassed qualitative analysis and systematic reviews of existing literature and case studies, enabling a holistic exploration of the subject matter. Key findings from this study reveal that the effective implementation of digital transformation necessitates robust technological infrastructure, innovative pedagogical approaches, comprehensive policy and regulatory frameworks. The integration of digital tools has shown significant potential in creating dynamic, personalized learning environments, enhancing student engagement and fostering inclusive education. However, the study identifies critical challenges such as inadequate funding, insufficient training and the persistent digital divide, which must be addressed to fully realize the benefits of digital transformation. The exploration of community and cultural impacts underscores that digital transformation can drive community development and cultural advancement by providing equitable access to educational resources and supporting holistic student growth. Emerging trends highlight the necessity of continuous innovation and ethical considerations in leveraging digital technologies for educational purposes. Conclusively, this study offers actionable recommendations, including the development of targeted strategies to bridge the digital divide, investment in continuous professional development for educator, the formulation of inclusive policies by policymakers and educational institutions. These measures are essential to harness the transformative potential of digital technologies in education, ultimately fostering an inclusive, equitable and innovative educational environment.

… , continuing education, etc. This article aims to describe the specificity of digital education, … Having shown the core of the digital education and the state of its implementation in modern …

In the current globalization trend, digital transformation is an indispensable requirement that affects all aspects of life. Within the education domain, it creates opportunities for tertiary education institutions to replace traditional teaching, learning, research, and operation methods with more innovative, creative, and cost-effective methods. This article aims to examine recent technological advancements to promote the transformation in tertiary education. Our research methodology consists of two main activities: 1) identifying relevant literature on the use of technology to promote transformation in tertiary education by adopting PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines; 2) conducting a thematic analysis based on the findings of the literature review; to explore the relationships between them in order to better understand the link between technological trends and digital transformation in tertiary education. The findings indicate that the current technology trends that are being concerned and deployed in the educational environment are Artificial intelligence, the Internet of Things, blockchain technology, and other relevant platforms and technologies such as Social networks, Mobile platforms, Big data analytics, Cloud computing, Robotic Process Automation, Virtual reality and Augmented reality and Additive manufacturing. The article also discusses the adjustment of tertiary education in the process of digital transformation with the support of technology and points out the shortcomings as well as research directions in the coming time.

Digital transformation in the global higher education industry determines the future roadmap to a sustainable education management strategy. This research paper aims to develop a qualitative model that advocates how digital transformation as a propelling force could be used to build competitive advantages for universities. Building competitive advantage is a relative, evolving, and important concept in strategy formulation. In recent years, specifically in the education industry, the notion of building competitive advantage is challenged by global phenomena such as digital transformation globalization, information exchange, digitization and social media in most of the global industries. These phenomena have collectively made the process of building competitive advantage rapidly changing, short-term and contextual. These findings aid the evolution of strategic management practices in universities by providing empirical insights in determining the impactful changes and their connection to evolutionary learning. It also stresses the importance of using the developed model as a decision support system to generate, regulate and retain student experience and expectations. This research paper provides first-hand insight into the impactful changes affecting universities’ vision and how they can turn these changes to their advantages and set a road map to design-develop models to integrate and regulate these essential changes in their strategies using evolution learning mechanism and digital transformation strategy.

This study investigates the challenges hindering the implementation of Digital Transformation (DT) in Higher Education Institutions (HEIs) by thoroughly reviewing the literature. It identifies multiple dimensions and subdimensions of these barriers to offer valuable insights to help HEIs navigate their transformation processes successfully. By doing so, they can effectively address the changing requirements of students and society in an increasingly digital environment. This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, synthesizing data from 20 relevant peer-reviewed articles published between 2019 and 2024. NVivo and Zotero were utilized as methodological instruments for coding, thematic analysis, and text mining to extract insights from the chosen articles to construct a Concept-centric Matrix on Barriers to Digital Transformation (DT) in Higher Education Institutions (HEIs). The result of this study is summarized in a Concept-centric Matrix on Barriers to DT in HEIs consisting of nine (9) dimensions such as (i) Digital Vision, Strategy, and Policies; (ii) Digital Leadership and Management; (iii) Digital Organization; (iv) Digital Resources; (v) Digital Competence; (vi) Digital Stakeholder Management; (vii) Digital Culture; (viii) Digital Academic; and (ix) Digital Ethics. Each dimension has subdimensions of barriers (n=80). Despite various sectors anticipating significant disruption from DT, many HEIs feel inadequately prepared to adapt because of the barriers to its implementation. The ongoing DT within HEIs reveals a complex landscape marked by various intertwined barriers that necessitate a strategic reevaluation and a commitment to fostering an inclusive, responsive educational environment.

… applications has become the combination of educational … a digital transformation of all functions of higher educational institutions, which provides a qualitatively new level of educational, …

Schools, universities, and other educational entities are increasingly aware of the untapped potential of digital transformation, an essential process for increasing efficiency and collaboration, and reducing costs and errors in the management of at-scale training systems. In this context, the “Riconnessioni” project was promoted by the Compagnia di San Paolo in agreement with the Ministry of Education but planned, started and developed by the Foundation for the School. The digital transformation started with a defined strategy that leveraged opportunities presented by new technology while meeting the objectives of system stakeholders. Through several steps, that strategy was developed for education connecting everything to support tomorrow’s digital world and creating strong strategic partnerships able to build an ecosystem connecting people, processes, and things into a powerful, secure, and smart communications network. This paper reports on the three-year Riconnessioni project, which is combining the energies of teachers, managers, administrative staff, students, among others, and experimenting with new learning models, taking advantage of opportunities that emerged from perceptions stemming from concerns and systemic issues. To date, more than 150 schools in Italy have been included in the project, together with 550 teachers selected to scale up the instructional process. Using a methodology called “cascade training”, the 550 selected teachers were able to spread the knowledge to more than 2,600 colleagues. The monitoring and evaluation activity performed in Riconnessioni aims at processing information on implementation and results, following three lines. First, it regularly evaluates project activities from a reporting standpoint. Second, it verifies the plan consistency against implementation achievements. Third, it identifies changes produced and focuses on teachers’ and students’ skills to evaluate the effects of the project. The assessment framework is also discussed in this work, reporting on results regarding feedback, follow-up, and effects gathered from the field. The evaluation highlighted that labs were indeed able to improve teachers’ competence and underlined the added value of cascade training which spread digital domain knowledge and awareness into the group of involved schools.

… Education is also in the early stages of a fundamental reconfiguration. This chapter considers how digital environments will likely shape the content, scope, and practice of education. …

… of the challenges and possibilities in educational digital transformation. Firstly, “A qualitative exploration of university students' perspectives on distance education in Jordan” (Al-…

Industry 4.0 and Society 5.0 are reshaping the way organizations function and interact with the communities they serve. The massive penetration of computer and network applications forces organizations to digitalize their processes and provide innovative products, services, and business models. The education market is suffering changes as well, but universities seem slow to react. This paper proposes the application of an integrated digital transformation model to assess the maturity level that educational institutions have in their digital transformation processes and compares them to other industries. Particular considerations to address when using the model for higher-education institutions are discussed. Our results show that universities fall behind other sectors, probably due to a lack of effective leadership and changes in culture. This is complemented negatively by an insufficient degree of innovation and financial support.

Digital transformation (DT) is raising new challenges. This article seeks to understand how DT has changed business strategies, requiring a new profile of professionals, analyzing the most sought-after skills and identifying opportunities for future professionals. Also, it studies whether universities have incorporated in their training the new skills required by the labor market impacted by DT. To these ends, a systematic literature review dealing with digital transformation, competence, and education was conducted. The existing literature was categorized into seven main areas of investigation: digital literacy; skills identification; use of digital technologies in teaching; learning models; workforce qualification or re-skilling; digital technologies in the labor market; and undergraduate course analysis. This structuring then lays the groundwork for capturing gaps in the literature and proposing future research.

… in education and industry by the digital transformation to … resources for the digital transformation and the challenges of … AI under the constructs of the new educational model? (3) What …

… changes in the educational ecosystems studied by Zhao and Frank. Teachers remained the most influential ‘species’ within educational ecosystems and they were not replaced by ICT. …

… Digital technology has restructured the spatial configuration and power relations of the educational field, propelling the educational ecosystem towards a transformation characterized …

The comprehensive intervention of Generative Artificial Intelligence (GenAI) into the educational ecosystem represents far more than a mere technological iteration; it marks a discontinuous mutation in the history of curriculum design, comparable in profundity to the advent of the printing press or the internet. We are currently witnessing a fundamental reset of the "value" assigned to cognitive tasks. As the marginal cost of content generation approaches zero, the premium in education is shifting drastically from the retrieval and accumulation of information to its evaluation, curation, and synthesis. This report, based on an exhaustive review of global educational frontiers—including empirical cases from Singapore, China, and Western higher education institutions—provides an in-depth analysis of the educational landscape in the Post-GPT era. The analysis indicates that traditional capabilities centered on rote memorization and linear execution are depreciating at an accelerated rate. Conversely, skills emphasizing high agency, evaluative judgment, and human-machine collaboration are rapidly climbing the value chain. Future curriculum design must achieve a paradigm shift from "AI as Oracle," where students passively receive answers, to "AI as Partner" or "Cognitive Mirror," where students actively critique and refine outputs. This transition is essential to address the increasingly severe risks of cognitive offloading and skill atrophy.

Driven by the digital transformation of territorial spatial governance, traditional urban planning is irreversibly shifting towards a data-driven empirical paradigm. However, constrained by mimetic isomorphism and path dependence, many geography-based regional universities remain trapped in an educational dilemma: they overemphasize morphological representation while marginalizing quantitative decision-making, fostering a structural mismatch between graduate competencies and industry demands. To explore a systematic pathway out of this dilemma, this study chronicles a three-year pedagogical intervention utilizing a mixed-methods design with a historical control cohort (N = 275) within the urban planning program of Gansu Agricultural University—a regional institution situated in a less-developed frontier where territorial renewal demands macro-spatial synthesis over aesthetic forms. The intervention strategically redefined the graduate competency profile as “spatial data analysts”, constructing a pedagogical model comprising foundational algorithmic training, cross-disciplinary faculty collaboration, and real-world Project-Based Learning (PBL), coupled with a restructured, evidence-based evaluation system. Longitudinal tracking and quantitative analyses indicate a structural alignment with elevated educational efficacy. At the macro level of employment trajectories, the proportion of graduates securing knowledge-intensive data positions experienced a structural shift, rising from a baseline of 14.5% to 42.5%, reflecting an enhanced capacity to capitalize on expanding societal demands. At the meso level of practical competence, the award rate in high-level professional competitions increased by 35.4%. At the micro cognitive level, the new evaluation mechanism is associated with a successful redirection of students’ cognitive resources toward algorithmic logic and policy translation (p < 0.001) while highly significantly enhancing their self-efficacy in tackling complex, wicked engineering problems (p < 0.001). Rather than isolating pure causal mechanics, this study interprets these systemic gains as a contextual realignment of academic supply. It provides a context-sensitive, reproducible methodological reference for cultivating professional distinctiveness and reshaping the spatial planning education system in the digital era.

… best be described as educational ecosystems that are just as … the ecosystem and the entire sys tem vibrates. That, quite simply, is why reforms that take aim at only one part of education …

Purpose The purpose of this research article is to explore the strategies and frameworks employed for Industry 4.0 integration, study the effects of Industry 4.0 integration on student …

… Digitalization being big evolutionary step, will reshape the entire education system in future. … a new paradigmatic shift in learning from frontal education system to online digital learning, …

… criteria in paradigm shift in higher education is … the paradigm shift has been there in the higher education, still it is not in the unfulfilled state. Poland’s higher education sector is digitally …

Flipped learning is rapidly transforming education by shifting from traditional teacher-centered instruction to student-driven learning. This pedagogical approach enhances critical thinking, collaboration, and engagement by encouraging students to engage with content outside the classroom and apply their knowledge through interactive activities, such as discussions and problem-solving, within class time. While the benefits of flipped learning are clear, its successful implementation faces challenges such as the digital divide, limited teacher training, and the need for strong technological infrastructure. E-learning plays a vital role in enhancing academic performance and developing digital skills, but its effectiveness is influenced by factors like instructional design, student autonomy, and the ability of instructors to adapt to the digital environment. For flipped and blended learning models to reach their full potential, continuous investment in technology, innovative teaching strategies, and professional development for educators are essential. Despite these challenges, these hybrid models offer a promising approach to creating more inclusive, engaging, and future-ready educational environments. By addressing existing barriers, flipped learning can help prepare students for the demands of the modern world, equipping them with the skills and critical thinking abilities necessary for success in an increasingly digital and collaborative society.

The digital transformation of universities is a strategic choice to deepen educational and teaching reforms and strengthen talent cultivation. Leveraging the information and communication technology (ICT) strengths of Xidian University and the theoretical and practical achievements of educational informatization, we explored and practised methods for digital transformation to drive profound reforms in higher education. First, with the ideas of “data-driven, AI-empowered” as the core, we addressed systemic issues in educational and teaching reforms by establishing the intelligent education brain and the “intelligent teaching platform.” This facilitated data-driven process of reengineering, forming the five-duals nurturing model or Xidian model, harnesses digital transformation to drive educational reforms. Second, in response to the precise and personalized demands of talent cultivation, we constructed a resource provision model and a cobuilt sharing system based on human–technology collaboration. This generated a precise and personalized teaching model that was comprehensive and data-driven. Finally, to address the major formative issues in educational and teaching assessment, we built a data-driven evaluation system for the entire process. We have persistently pursued the integration of ICT with education and teaching, upholding the human–technology collaboration model for talent cultivation and development. Our approach has reshaped a first-class undergraduate education system in the era of the digital economy, establishing a benchmark university for “artificial intelligence + education” and creating a comprehensive solution that is replicable and adaptable.

In the light of technology-driven social change that creates new challenges for universities, this paper considers the potential of mobile learning as a subset of e-learning to effect a paradigm shift in higher education. Universities face exponential growth in demand for higher education, significant decreases in government funding for education, a changing in understanding of the nature of knowledge, changing student demographics and expectations, and global competition. At the same time untethered mobile telephony is connecting large numbers of potential learners to communications networks. A review of some empirical literature on the current status of mobile learning that explores alternatives to help universities fulfil core functions of storage, processing, and disseminating knowledge that can be applied to real life problems, is followed by an examination of the strengths and weaknesses of increased connectivity to mobile communications networks to support constructivist, self-directed quality interactive learning for increasingly mobile learners. This paper also examines whether mobile learning can align the developing technology with changing student expectations and the implications of such an alignment for teaching and institutional strategies. Technologies considered include mobile computing and technology, wireless laptop, hand-held PDAs, and mobile telephony.

This chapter reviews salient features of the recent widespread adoption of digital educational resources by Higher Education. Although change is ongoing, there are some obvious lessons to learn. First, there is no single blueprint on how digital learning should best be done. A flexible mixture of pedagogy, technology, face-to-face and online contact will be different for individual subjects, students, levels of education, and institutions. Choices of the delivery format are often based upon decisions by an institution or lecturer who may be very knowledgeable about the subject matter but poorly aware of the full range of effective digital opportunities available. Despite greater awareness of digital educational activities, new applications are barely realised. Sustainable, large-scale implementation of digital learning environments will require customised training for students and staff in the use and rationale of digital educational technology. The cultural aspects of learning and acquisition of technical competency may be more difficult for staff than simply changing the application of technology.

… The pandemic has pulled the actors in higher education to … education before COVID would no longer be the same as the one after. This research aims at investigating the primary digital …

… paradigm and the paradigm shift in education; also, to identify the deterministic foundations of the paradigmatic shift, … potential of riskiness in modern education. An approach to bringing …

… In our discussion of digitalization in education, distinguishing between these different types is helpful, especially when considering challenges for integrating educational technology …

The paper presents the results of systematic review of modern scientific publications devoted to the digitalization of education. A review of Russian and foreign studies allows us to conclude that there is a relationship between high academic performance of students and the use of digital technologies. Other advantages of digitalization are: expanding the boundaries of "self-directed learning", developing leadership in the pedagogical environment, creating conditions for the formation of individual educational trajectories of students, modernizing tools for assessing student knowledge, and also differentiating forms and methods for teaching. Based on a critical analysis of publications on this topic, the possible destructive consequences of digitalization of education are determined: ousting experienced teachers with insufficient digital competence from the educational space; information overload; an increase in cognitive distortions; a decrease in the effectiveness of training regarding the formation of interpersonal communication skills of students; the deepening of digital divide; the formalization and dehumanization of education. Compensators of educational space digitalization dysfunctions are distinguished: improving the teacher training and motivating system, digital content quality control, taking into account the regional specifics of educational systems, a combination of traditional and digital pedagogy, group collaboration, and digital trust. The paper substantiates the conclusion that digital technology is a necessary, but at the same time, insufficient condition for improving the quality of educational work and morale building activities. Based on the analysis of scientific publications, the authors determine the principles of digitalization of education: the formation of institutional conditions for supporting digital innovations, the consideration of situational factors, the resource support of educational organizations, and the priority of personal interests (subject-centered approach).

The article describes the changes in the modern socio-economic environment, which affect the digitalization of society, including the socio-educational sphere. On the basis of the authors’ proposals for the development of the concept of “information-educational systems”, mathematical models for their description and mechanisms for analysing their essential characteristics determined by modern processes of development and digitalization of society are indicated. Through the example of using elements of the theory of dynamic deductive databases and the theory of neural networks, the article describes mathematical models that adequately reflect strategies for the development of people and stable small groups, as well as large dynamic human communities, on the basis of which recommendations are proposed for developing such strategies. The results can be used in the pedagogical design of various models of educational activities and information and educational systems for various purposes, including education management and direct training. It also seems that the mechanisms and features of information and educational systems described in the article will allow us to establish an evidence-based educational policy at various levels in the context of digitalization

. The paper examines the possible effects of information and communication technologies (ICT) on educational institutions (four directions of impacts and four axes of measuring changes— pedagogy, technology, organization, and economics). The authors propose to use four classes of models to describe all forms of technology-based education and possible transformations of educational institutions under the influence of ICT to analyze the modern experience of digital transformation: a value chain model describing the primary and secondary activities of an educational institution; a diagram of added quality chains describing the sequence of actions carried out by an educational institution; a model of the routine loop of a teacher (employee) of an educational institution, describing his/her daily activities, taking into account the use of software products and computer and communication technology, displayed at the appropriate place in the value chain; the event chain of the process, detailing the description of the routine loops of teachers (employees) and trainees, describing the logic of their actions, incoming and outgoing information, information systems used, and all types of interactions in the educational process between a trainees and a teacher, a trainee and training material, and a trainee and his own himself. As a result, a tool has been created to describe and research all modern forms of technological education and their digital transformation.

The fourth industrial revolution, the digitization of industry, is driving business landscape and associated skills development, including tertiary education. Universities and institutions of higher learning have evolved into technological hubs, developing and delivering skills for the future. The operations and systems together with workflows of delivery at a tertiary institution should be modified to deliver services and a product that is 4IR savvy, more importantly, the systems and processes must be 4IR enabled so as to deliver a seamless, efficient, smart digital experience. This paper reviews tertiary institutional operations and provides an architecture to deliver digitization at institutional level. This research adopts a functional and architectural view of the system and systems of systems. A Digital Education Evaluation Model (DEEM) is proposed for evaluation of traditional and digitized practices, for identification of digitized technologies for adoption. The DEEM is demonstrated by comparatively analyzing traditional and virtual classrooms.

Based on the results of the study, it was concluded that Anwaha's mission of digitizing education was realized by visualizing, futuristic thinking, showing foresight, proactive planning, creative thinking, taking risks, process alignment, coalition building, continuous learning, and embracing change so as to be able to adapt to digitalization of administration and teaching. Develop a model for digitizing the publication of school activities.

The article substantiates the need for a transition from an eclectic postmodern education paradigm to a humanistic one, rooted in the foundation of Russian culture and suggesting the development of a person and increasing his personal potential. The educational process immanently contains moments that are not reducible to technology and require direct subject-subject communication and interaction between teacher and student. Education issues are mainly related to student motivation, not digital literacy. In this regard, the authors believe that the priority direction of state policy in the field of education should be the training of highly qualified teachers, improving the level and quality of their life, as well as increasing the prestige of teacher work.

Artificial Intelligence (AI) has the potential to revolutionize various aspects of education due to its rapid expansion in educational technology by introducing personalized and efficient learning experiences. Several artificial intelligence (AI) tools are being integrated into this research project such as “Coursera Coach powered by Generative AI” which incorporates adaptive learning, “AI- assisted course building powered by Generative AI” which incorporates intelligent tutoring elements and “Turnitin” offers tools for grading and providing feedback to revolutionize teaching, learning, and assessment practices in higher education. Researchers evaluate the effectiveness of AI tools in enhancing student engagement, personalizing learning experiences, and optimizing assessment processes based on a variety of quantitative metrics. A comparison is made between experimental groups that follow AI-integrated teaching methods and control groups that follow a traditional approach to instruction. As part of the study, scores of pre- and post-assessment questions were collected, learning progression patterns were analyzed, and instructors and students provided qualitative feedback. As a result of the experimental data, it has been possible to discern which AI tools have strengths and limitations within the context of higher education. A variety of adaptive learning platforms are evaluated for their ability to adjust content to individual learning styles, while intelligent tutoring systems are assessed for their impact on comprehension, retention, and problem-solving skills. Automated grading tools are tested for their efficiency gains in assessment processes and their ability to improve feedback promptness and quality. A substantial amount of empirical evidence is provided by the findings of this study to the ongoing discourse on AI integration in higher education. This study provides a wealth of actionable insights for academic staff, technicians, and administrators seeking evidence-based strategies for implementing AI technologies in their educational frameworks.

… roles of GAI (LLMs) for collaborative learning and proposal of AI readiness actions by various stakeholders to form an ecosystem conducive to harnessing GAI (LLMs) for collaborative …

Industry 5.0 challenges higher education to adopt human-centred and sustainable uses of artificial intelligence, yet many current deployments still treat generative AI as a stand-alone tool, neurophysiological sensing as largely laboratory-bound, and governance as an external add-on rather than a design constraint. This article introduces Nested Learning as a neuro-adaptive ecosystem design in which generative-AI agents, IoT infrastructures and multimodal deep learning orchestrate instructional support while preserving student agency and a “pedagogy of hope”. We report an exploratory two-phase mixed-methods study as an initial empirical illustration. First, a neuro-experimental calibration with 18 undergraduate students used mobile EEG while they interacted with ChatGPT in problem-solving tasks structured as challenge–support–reflection micro-cycles. Second, a field implementation at a university in Madrid involved 380 participants (300 students and 80 lecturers), embedding the Nested Learning ecosystem into regular courses. Data sources included EEG (P300) signals, interaction logs, self-report measures of engagement, self-regulated learning and cognitive safety (with strong internal consistency; α/ω≥0.82), and open-ended responses capturing emotional experience and ethical concerns. In Phase 1, P300 dynamics aligned with key instructional micro-events, providing feasibility evidence that low-cost neuro-adaptive pipelines can be sensitive to pedagogical flow in ecologically relevant tasks. In Phase 2, participants reported high levels of perceived nested support and cognitive safety, and observed associations between perceived Nested Learning, perceived neuro-adaptive adjustments, engagement and self-regulation were moderate to strong (r=0.41–0.63, p<0.001). Qualitative data converged on themes of clarity, adaptive support and non-punitive error culture, alongside recurring concerns about privacy and cognitive sovereignty. We argue that, under robust ethical, data-protection and sustainability-by-design constraints, Nested Learning can strengthen academic resilience, learner autonomy and human-centred uses of AI in higher education.

As Generative Artificial Intelligence (GenAI) becomes more common in higher education, integrative methods will be needed to navigate the changing landscape. This paper proposes a holistic model for transforming the academic landscape that relies on AI tools and systems rather than simplistic ones, within the GAIA-EDU (Generative Artificial Intelligence for Academic Instruction and Advancement) framework. GAIA-EDU is all about using AI across all parts of higher education, including improving the academy's AI-infused ecosystems, teaching and learning, research and knowledge creation, assessment and feedback, academic administration, and the institution's decision-making processes. GAIA-EDU aims to address problems with integrating customizable generative AI tools and the changing roles and skills of knowledge workers. GAIA-EDU, like other higher education institution frameworks, aligns with the latest trends in educational frameworks and generative AI tools. GAIA-EDU, therefore, aims to facilitate the incorporation of functional generative AI tools for pedagogical purposes in higher education. This paper offers a thorough conceptual framework for researchers, educators, and policymakers aiming to develop, evaluate, and deploy generative AI-enhanced teaching and learning systems in higher education.

… how AI is influencing teaching and learning at different levels of the educational ecosystem. … tools have provided new opportunities for dynamic dialogue through generative AI. We also …

The potential of generative artificial intelligence (GenAI) to transform education has become a key area of focus, particularly in its integration with pedagogical strategies such as flipped learning. Flipped learning, which encourages students to engage with content prior to class, has been shown to promote deeper learning. However, its implementation often presents challenges. This paper proposes a novel framework that combines flipped learning with GenAI, offering a comprehensive approach that spans micro, meso, and macro levels. At the micro level, the framework focuses on optimizing in-class experiences by leveraging GenAI to facilitate real-time feedback, collaborative learning, and personalized support. On the meso level, it examines how GenAI tools can assist in workload management and facilitate personalized pre-class preparation, ensuring alignment with diverse learning styles and needs. At the macro level, the paper addresses the paucity of theoretical guidance regarding the flipped approach and discusses how the framework can guide curriculum redesign by employing theoretical frameworks such as constructivism and connectivism theory to inform the structure of in-class activities and foster more effective knowledge construction and critical thinking. By addressing systemic challenges at multiple levels, the proposed GenAI-enabled flipped learning framework aims to enhance the overall learning experience, providing a more engaging and efficient approach to flipped classrooms. The paper concludes by suggesting areas for future research and calling for empirical studies to assess the impact of this integrated approach across various educational contexts.

… of AI’s affordances can be discovered through another tool borrowed from ecological studies – ecosystem … of introducing something to the ecosystem— such as generative AI tools in a …

The deep integration of Generative Artificial Intelligence (GAI) and education is reshaping smart learning environments (SLEs). This study constructs and validates a GAI-enhanced SLE framework that integrates technological principles, personalized learning, real-time feedback, and ecosystem collaboration. We propose a “cognitive-behavioral-emotional” three-dimensional analytical model and implement a personalized content generation algorithm based on conditional random fields. In addition, a multi-agent collaborative ecosystem is introduced to optimize interactions within the learning environment. A 12-week mixed-methods study involving 300 participants shows that the GAI-enhanced SLE significantly outperforms traditional environments across multiple dimensions, including knowledge mastery (85.3% vs. 72.1%, $\mathbf{p}<0.001$) and student engagement (42.3 hours vs. 31.4 hours, $\mathrm{p}<0.001$). Importantly, this study systematically quantifies potential negative impacts of GAI for the first time in comparable empirical research, such as the significant increase in cognitive load in high-intervention groups (NASA Task Load Index: 68.2 vs. 52.4, $\mathrm{p}<0.01$), revealing the complex dual effects of the technology. The empirical application of the three-dimensional analytical framework (e.g., learner clustering based on state vectors) effectively bridges theory and practice. The findings confirm the effectiveness of the proposed framework in enhancing personalization, feedback efficiency, and overall system intelligence, while highlighting the limitations of a 12-week short-term study and outlining future research directions for long-term impact tracking, differentiated intervention strategies, and the construction of ethical safeguards.

… Generative AI (GenAI) is transforming creative design education through the development of a Dynamic Learning Ecosystem. … teaching approaches affect learning outcomes, challenges …

The integration of Generative Artificial Intelligence (Gen-AI) in the Society 5.0 era has brought significant disruption to the global education landscape. At the elementary school level, institutional leaders often face gaps in official regulations that trigger restrictive rather than enabling policies. This study aims to analyze the role and digital leadership strategies of elementary school principals, identify systemic challenges and emerging supporting factors, and develop a conceptual framework for developing a safe, ethical, and innovative Gen-AI-based learning ecosystem. Using a descriptive qualitative approach with a single case study design, data collection was conducted at BINUS SCHOOL Semarang through triangulation techniques that included in-depth interviews with eight key informants (consisting of the principal, technology coordinator, four class teachers, and two parent representatives), passive participant observation, and analysis of formal school documents. The study results indicate that the digital leadership implemented in this school displays an adaptive profile (Enabling Leadership) through synchronization of the institution's vision, provision of ICT infrastructure based on content filtering, facilitation of digital pedagogical competency training, and regular updates to academic honesty guidelines. Furthermore, interactions within this ecosystem have resulted in the "BINUS Digital-Pedagogical Framework" model, which seeks to balance strategic alignment, streamline teacher administrative workloads (professional co-piloting), and limit the use of AI during the initial ideation stage (cognitive encapsulation) to protect students' original critical thinking. These findings are contextual to the characteristics of the schools studied. As a practical recommendation, elementary school principals can gradually adapt the principles of this framework through redesigning conceptual assessment tasks (AI-Resistant Tasks) and developing local SOPs with school committees to build a relevant and ethical digital citizenship curriculum.

… transformational practice, and (v) educational ecosystem architects. Each stage reflects on recognition activities, unlearning levels, and key actions to realize generative AI’s integration. …

This theoretical research paper explores Generative Artificial Intelligence (AI) as a transformative force in sustainable education within the digital era. Through a comprehensive literature review of peer-reviewed articles, conference proceedings, and policy documents in sustainable education, AI in education, and learning theories, we propose a novel conceptual framework: Generative AI-Enabled Sustainable Education (GAISE). This framework synthesises principles from sustainable education theories, AI in education, constructivism, connectivism, and transformative learning. The GAISE model elucidates how Generative AI's capabilities in content generation, personalisation, adaptive learning, and natural language processing can enhance sustainability literacy and promote transformative learning experiences. Our analysis reveals the framework's potential to integrate Generative AI into curriculum design, teaching methodologies, assessment strategies, and teacher professional development for sustainable education. Critical ethical considerations include data privacy, equity, and human-AI collaboration in educational contexts. The paper identifies key challenges in implementing Generative AI for sustainable education and proposes future empirical research directions and policy recommendations. This work contributes to the intersection of AI and sustainable education, offering theoretical insights and practical pathways for educators and policymakers to leverage Generative AI in promoting sustainability competencies in education.

A nation’s progress toward Sustainable Development Goal 4 (Quality Education) depends in part on the long-term health of its educational research system, yet systematic, longitudinal assessments of such research ecosystems remain scarce. This study applies a generative artificial intelligence–based framework to evaluate the sustainable development of China’s empirical educational research ecosystem from 2004 to 2023. We compiled a dataset of 2,145 empirical studies published in leading Chinese education journals and used GPT-4o to score each paper on 31 quality indicators covering research problem, theoretical framing, design, data collection, analysis, and reporting, using a 1–10 analytic rating scale. Based on the resulting score distributions, we constructed a fuzzy relation matrix and applied a fuzzy comprehensive evaluation method to derive annual and overall sustainability indices, while the Criteria Importance Through Intercriteria Correlation (CRITIC) method was used to determine objective indicator weights. The overall sustainability index of China’s empirical educational research ecosystem over the 20-year period is 75.77 on a 100-point scale, with membership degrees concentrated at quality levels 7 (0.328) and 8 (0.435), indicating a generally robust and maturing system. Longitudinal trends reveal three stages of evolution—fluctuating development, rapid growth, and continuous improvement—corresponding to a shift toward more stable high-quality output. At the micro level, the ecosystem shows strong responsiveness to real-world educational problems, with high average scores for the relevance (8.45) and social significance (8.23) of research questions, as well as generally solid research design and data analysis practices. However, relatively lower scores for transparency of data analysis (7.08) and accessibility of raw data (6.46) highlight persistent challenges for reproducibility, open science, and methodological innovation. We conclude that China’s empirical educational research ecosystem has reached a relatively high and stable level of performance but faces critical tasks in strengthening data openness, methodological renewal, and AI-augmented governance. The proposed generative AI–based evaluation framework may offer a scalable tool for continuous monitoring and governance of national research ecosystems, while its results should be interpreted as an auxiliary input rather than a substitute for expert peer assessment.

In recent years, the epidemic of communicable diseases has boosted the prevalence of online teaching activities. But how to make smart evaluation towards teaching effect has always been a technical barrier. As consequence, this paper utilizes fuzzy comprehensive analysis to deal with this problem from the perspective of big data mining. In particular, it proposes a data-driven smart evaluation framework for teaching effect based on fuzzy comprehensive analysis. Firstly, business data is timely collected from online courses as the basis, including teacher performance, teaching contents, student feedback, etc. Specifically, the initial data is encoded into structured format, from which characteristics of students behaviors can be analyzed. Then, the fuzzy comprehensive analysis is utilized to calculate evaluation results of teaching effect. Some simulation experiments are conducted based on the computer programming design, in which the proposal technical framework is implemented on a developed Web platform. The experiments reflect that the proposal can well realize evaluation of teaching effect.

… We consider a smart university as a self-learning organization functioning on the basis of a … mechanism of adapting promptly to contemporary economic conditions. This mechanism …

… the competency map proposed in this paper. In particular, for the construction of the competency map… This approach allowed the proposed competency map not only to cover courses for …

This paper features a methodology for embedding and assessing a competency in an academic curriculum using competency maps. This methodology enables embedding and assessment of any competency in any curriculum, regardless of the educational level, as long as the competency is correctly described by means of a competency map. As an example of the application of this methodology, a proposal for embedding and assessing sustainability in engineering degrees is presented. A competency map embodies the set of learning outcomes of the competency that students should have acquired upon completion of their studies. This information allows the designers of the curriculum to determine the learning outcomes that should be developed in the degree and to distribute them appropriately among the subjects. The presence map can be constructed from the competency map. It contains information regarding the extent to which each learning outcome of the competency map is being developed in the degree. This paper proposes the construction of a presence map in two steps: (1) perform a survey and (2) conduct a semi-structured interview with professors. The interview, which is conducted by one or several experts in the competency, allows the different criteria used by the professors when filling out the questionnaire to be unified, whereas the presence map shows whether a particular competency is correctly embedded in the curriculum and the aspects that could be improved. Finally, to validate that the students are achieving the learning outcomes of the competency map, we propose a survey to measure the students’ perception about their own learning in the competency. These results can be compared with the presence map to help determine whether, from the students’ point of view, the expected learning outcomes are being achieved in the corresponding subjects. The aim of this process is to provide the information necessary to indicate any changes in the curriculum that may improve the embedding of the competency.

Despite the importance of competency modeling for both individuals and organizations, there is a lack of a comprehensive literature review and a cartography for it. This paper aims to provide an in-depth overview of different approaches to competency modeling reported in the field of technology-enhanced com petency-based learning. This literature review is complemented by an additional overview of related initiatives toward modeling intended learning outcomes, learning opportunities, achieved learning outcome profiles of learners and competency maps. In addition, a cartography illustrating the relationships between some important models is proposed. The main purpose of this work is to provide researchers with a comprehensive review of the current status in this field as well as to highlight ongoing issues and challenges that need to be addressed.

Despite the plethora of studies reported during the last decade in relation to educational innovation in teaching and assessment of competencies, a consensus is seemingly lacking on a definition that establishes the scope and boundaries competency assessment. This research gap motivated a systematic review of the literature published on the topics of “educational innovation in teaching” and “assessment of competencies” in upper secondary and higher education during the period from January 2016 to March 2021. The main objective of the study was to define and evaluate educational innovation in teaching and assessment of competencies in upper secondary and higher education following PRISMA guidelines for a systematic literature review (SLR) on a curated corpus of 320 articles. We intended to answer the following questions: (1) What do “educational innovation in teaching” and “assessment of competencies” represent for upper secondary and higher education? (2) How are they evaluated? Lastly, (3) are efforts exerted toward the standardization of transversal competencies? The SLR seeks answers to these questions by examining nine research sub-queries. The result indicated that the greatest effort toward educational innovation in competencies was made at the higher education level and targeted students. Competencies were revised through associations with the Sustainable Development Goals of the 2030 Agenda. In addition, the methodologies used for teaching and evaluation of competencies were reviewed. Finally, the study discussed which technologies were used to develop the proficiencies of students.

Due to the development of deep learning technology, its application in education has received increasing attention from researchers. Intelligent agents based on deep learning technology can perform higher order intellectual tasks than ever. However, the high deployment cost of deep learning models has hindered their widespread application in education. In addition, there needs to be more research on applying deep learning technology in education. In this article, we develop an intelligent agent using a performer-based encoder–decoder neural model to classify object-oriented programming (OOP) errors in student code and generate hint feedback in natural language to help students correct the code. This study investigates the feasibility of deploying this agent in an educational setting to support the learning of OOP. This study first examines the low-speed inference problem of the deep learning model. A fast inference algorithm is proposed for the model, which achieves a speedup of eighty times. This study further explores integrating a human–machine collaborative learning process with the deep learning agent. Students were surveyed about their perceptions of the agent in supporting learning. Student responses are interpreted within the learning partnerships model (LPM) framework to show how the agent's technical automation and autonomy features support student-agent learning partnerships. Finally, implications and suggestions for educational application and research of deep learning technology are presented.

Human-machine collaboration is the future trend of the human social learning. The new data generation capability of the Generative AI has been proven on similar pre-trained models such as ChatGPT. MOOC is an important engine to drive the digital transformation of the higher education in the world. The innovative and practical researches of the human-machine collaborative MOOC learning interaction can offer useful references to build the digital learning ecology with high quality. Guided by the interaction theory and the curriculum theory, this study sorted out the general process of the human-machine collaborative MOOC learning. Then, based on the Human in the Loop (HITL), this study deconstructed the mechanism of the human-machine collaborative MOOC learning interaction, and clarified the empowerment function of the Generative AI. After that, the pattern of the human-machine collaborative MOOC learning interaction empowered by the Generative AI, which constituted with “self-content-society”, was constructed, and it was applied through a national open online course with high quality from the iCourse. Finally, the results of the quantity and quality analysis of the social interactions in the MOOC discussion forum showed that the interaction patterns mentioned above could effectively improve learners’ interactive validity and learning quality.

In the era of digital intelligence, the integration of artificial intelligence (AI) into educational practices has the potential to transform traditional teaching methods. Human-machine collaborative teaching (HMCT) is a new paradigm that leverages the strengths of both human educators and AI tools to enhance learning outcomes. This study investigates the effectiveness of three human-machine collaborative teaching strategies—directive, guided, and collaborative-implemented in a university—level software engineering course. The experiment involved 99 third-year students and aimed to evaluate the impact of these teaching strategies on creativity and academic performance. The results show that the collaborative teaching method, enhanced by generative AI tools, led to the highest performance in final exams and overall academic achievement, as well as increased participation in extracurricular innovation activities in homework. While directive teaching produced consistent results, it did not foster the same level of engagement or creativity. Guided teaching demonstrated moderate success, but the greatest benefits were observed in the collaborative approach, where students took an active role in their learning. This study suggests that integrating AI into collaborative learning environments can enhance both academic outcomes and student creativity, and recommends expanding the use of AI-supported strategies in higher education. Future research should explore the scalability of these findings across disciplines and investigate long-term impacts on student development and career readiness.

… This study employed a meta-analysis to examine the overall effect of human-machine collaborative learning based on EVEs on knowledge retention in science learning. The study …

… acquisition and human-machine collaborative learning, this … learning, explained the human-machine collaboration … for designing human-machine collaborative learning activities to …