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This paper is aimed at describing and analysing what school organisers express when they network to expand the access and application of digital technologies in educational systems. Digital technologies develop rapidly in society, creating challenges and opportunities in people’s lives. Schools have an important task: to prepare young people for a future permeated by digital technology.

Participant observations and semi-structured interviews were used to describe and analyse how school organisers describe digitalisation work in the educational system.

The findings show that school organisers describe digital competence and providing support to schools as being important for expanding the access and application of digital technologies in the educational system. They also talk about equality connected to digitalisation work, changes in organisations, the importance of a holistic perspective, and a gold thread. They furthermore explain that networks, a sharing culture, good relations, and good communication enable digitalisation work. In addition, they point out that the lack of time, attitudes towards digital technologies, the lack of digital competence, and resistance to change are some of the constraints for digital technologies in the educational system.

School organisers need to implement digitalisation policies, which can be problematic because they work strategically to support operational activities.

This paper contributes knowledge about school organisers’ work to expand the access and application of digital technologies in the educational system.

This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

The purpose of this paper is to present an analytical review of the educational innovation field in the USA. It outlines classification of innovations, discusses the hurdles to innovation, and offers ways to increase the scale and rate of innovation-based transformations in the education system.

The paper is based on a literature survey and author research.

US education badly needs effective innovations of scale that can help produce the needed high-quality learning outcomes across the system. The primary focus of educational innovations should be on teaching and learning theory and practice, as well as on the learner, parents, community, society, and its culture. Technology applications need a solid theoretical foundation based on purposeful, systemic research, and a sound pedagogy. One of the critical areas of research and innovation can be cost and time efficiency of the learning.

Several practical recommendations stem out of this paper: how to create a base for large-scale innovations and their implementation; how to increase effectiveness of technology innovations in education, particularly online learning; how to raise time and cost efficiency of education.

Innovations in education are regarded, along with the education system, within the context of a societal supersystem demonstrating their interrelations and interdependencies at all levels. Raising the quality and scale of innovations in education will positively affect education itself and benefit the whole society.

Originality is in the systemic approach to education and educational innovations, in offering a comprehensive classification of innovations; in exposing the hurdles to innovations, in new arguments about effectiveness of technology applications, and in time efficiency of education.

Flipped classroom approaches (FCA) are an educational innovation that could increase students' learning outcomes in, and their enjoyment of, mathematics or STEM education. To integrate FCA into education sustainably, professional teacher development (PTD) is a promising tool. The research aim is to explore which aspects should be considered when developing and implementing professional mathematics or STEM teacher development for flipped approaches.

A total of 20 expert interviews were conducted and analysed according to a synthesis of grounded theory approaches and qualitative interview study principles.

Evaluating the interview data indicates that the characteristics of different teacher types in PTD, learning activities in PTD and the DSE model derived in this study could be vital elements in professional mathematics or STEM teacher development for flipped approaches.

Evaluating the interview data indicates that the characteristics of different teacher types in PTD, learning activities in PTD and the DSE model derived in this study could be vital elements in professional mathematics or STEM teacher development for flipped approaches.

This article examines curatorial practices, both traditional and digital, in the Guizhou Provincial Museum’s ethnic exhibition to assess their effectiveness in representing ethnic minority cultures, fostering learning and inspiring curiosity about ethnic textiles and costumes and associated cultures. It also explores audience expectations concerning digital technology use in future exhibitions.

A mixed-methods approach was employed, where visitor data were collected through questionnaires, together with interviews with expert, museum professionals and ethnic minority textile practitioners. Their expertise proved instrumental in shaping the design of the study and enhancing the overall visitor experience, and thus fostering a deeper appreciation and understanding of ethnic minority cultures.

Visitors were generally satisfied with the exhibition, valuing their educational experience on ethnic textiles and cultures. There is a notable demand for more immersive digital technologies in museum exhibitions. The study underscores the importance of participatory design with stakeholders, especially ethnic minority groups, for genuine and compelling cultural representation.

This study delves into the potentials of digital technologies in the curation of ethnic minority textiles, particularly for enhancing education and cultural communication. Ethnic textiles and costumes provide rich sensory experience, and they carry deep cultural significance, especially during festive occasions. Our findings bridge this gap; they offer insights for museums aiming to deepen the visitor experiences and understanding of ethnic cultures through the use of digital technologies.

This paper explores the convergence of Education 4.0 and Industry 4.0 and presents a Twin Peaks model for their seamless integration.

A high-level literature review is conducted to identify and discuss the important challenges and opportunities offered by both Education 4.0 and Industry 4.0. A novel Twin Peaks model is devised for the convergence of these domains and to cope with the challenges effectively.

The proposed Twin Peak model for the convergence of Education 4.0 and Industry 4.0 suggests that the development of these two domains is interdependent. It emphasizes ethical considerations, inclusivity and understanding the concerns of stakeholders from both education and industry. We have also explained how continuous incremental adaptation within the proposed Twin Peaks model might assist in addressing concerns of one sector with the opportunities of the other.

First, Education 4.0 and Industry 4.0 are reviewed in terms of opportunities and challenges they present. Second, a novel Twin Peaks model for the convergence of Education 4.0 and Industry 4.0 is presented. The proposed discovers that the convergence is adaptive, iterative and must be ethically sound while considering the broader societal implications of the digital transformation. Third, this study also acts as a torch-bearer for the necessity for more research of this kind to guarantee that our educational ecosystem is adaptable and capable of producing the skills required for success in the era of IR4.0.

A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems.

The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system.

The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations.

The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.

The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.

This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.

This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.