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Recent years have seen the rise of Artificial Intelligence (AI) powered generative chatbots, such as OpenAI's ChatGPT or Microsoft's Copilot. These tools have simultaneously positively surprised and taken aback people worldwide, raising the question of whether they can or should be used in education, as well as how to properly guide students and teachers on using them safely and ethically. To this end, this work provides (i) a brief overview of the current applications of AI in Higher Education (HE), (ii) a discussion of the ethical and societal concerns associated with the usage of AI models, (iii) the initial steps of the implementation of a chatbot used at the Technical University of Denmark (DTU) able to perform audits for Good Manufacturing Practice (GMP), and (iv) an investigation of the need and opportunities of AI in chemical engineering education. The latter is achieved through quantitative and qualitative analyses of the responses given by both Master's students and academia/industry practitioners on the introduction and use of AI in education. This paves the way for discussing current perceptions, expectations and concerns of AI models, as well as their limitations and the opportunities they could provide. • The potential of Large Language Models (LLMs) as virtual tutors in chemical engineering is highlighted. • Empirical results of surveys on the use of LLMs conducted among students and academics/industrial participants. • A discussion of the ethical and societal concerns on the deployment of LLMs is provided. • Initial investigation of a chatbot deployed in a Master's level course at the Technical University of Denmark. [ABSTRACT FROM AUTHOR]

New technology, through the IoT, Big Data and AI ecosystem, is the foundation on which tomorrow's solutions are created. Improved processes with better decision making are the actors that drive the evolution of tomorrow's services. This new technology has enabled innovations in several sectors including medical, manufacturing, automation, energy, education, and others. It should be noted that in recent years, Industry 4.0 and the COVID-19 sanitary crisis have forced some remarkable transformations and contributions to people's quality of life, safety, health and education. Currently, the education sector in all its levels (primary, secondary and university) re-quires the use of this technology and is moving more specifically towards a system known as "education 4.0" to meet the different demands of this sector. In this paper, we present a literature review of the use of Big Data analytics in the education sector in particular. We discuss the different technologies, architectures, and applications of Big Data analytics in this growing sector, and we propose a new architecture based on the new technology applied in education. [ABSTRACT FROM AUTHOR]

The process systems domain is undergoing the fourth industrial revolution, which is helping industries digitize and optimize their production techniques. Concurrently, the field of data-based modeling has been expanding, leading to the proposal of many fault detection models. However, the rapid expansion has created gaps in the field. For instance, Smart Manufacturing (SM) methodologies have yet to be incorporated into undergraduate chemical engineering education. Additionally, only a few developed fault detection models have been deployed for real-time usage and practical applications. This study takes a crucial step toward bridging the two mentioned gaps by enabling undergraduate students to learn SM techniques and developing a safe and controlled academic environment for deploying fault detection models. The demonstration is implemented on a shell and tube heat exchanger, taught in a senior year laboratory course, using the Smart Manufacturing Innovation Platform (SMIP). The implementation provides an easily customizable pipeline for SM applications involving human-in-the-loop decision-making on a real-life hardware system. Actual data from heat exchanger equipment is used to train and compare the performances of several state-of-the-art fault detection models, including fully connected, convolutional, and recurrent neural networks. Current work also presents tutorials on deploying models for practical real-time applications using the SMIP. The overall architecture is a plug-and-play package that will motivate students to learn about SM and catalyze their interest in developing and deploying fault detection models using real-world data. • Architecture to motivate undergraduate students to learn aspects of Smart Manufacturing. • The demonstration is implemented on a shell and tube heat exchanger using the Smart Manufacturing Innovation Platform (SMIP). • Fault detection models are deployed to test real-time applications, including fully connected, convolutional, and recurrent neural networks. • Students get first-hand experience of Human-in-the-Loop decision making similar to a control room. [ABSTRACT FROM AUTHOR]

Today's complex, dynamic, interconnected world presents the field of education ("Education 4.0") with significant challenges in developing competencies for reasoning for complexity. This article analyzes complex thinking as a macro-competency with sub-competencies of critical, systemic, scientific, and innovative thinking in educational environments. We worked with the systematic literature review method, selecting 35 articles in the Scopus and Web of Science databases using keywords words of interest and applying inclusion and exclusion criteria. Seven research questions guided the data analysis. The results highlighted that: (a) there are common characteristics of studies linking complex thinking, critical thinking, and creative thinking; (b) there is predominance of the qualitative method in the studies; (c) the critical thinking competency has been the most addressed in the research; (d) the predominant components of Education 4.0 are teaching methods and techniques; and (e) the three challenges that stand out for educational research are project feasibility, research opportunities, and required skills. This article is intended to be of value to academic and social communities and decision-makers interested in developing reasoning for complexity within the framework of Education 4.0. [ABSTRACT FROM AUTHOR]

Development in information technology has resulted in revolutionizing all aspects of life and this revolution has been realized as Industrial Revolution 4.0 (IR4.0). The IR4.0 will reduce the gap between digital and physical world. Keeping ultramodern developments in view, an amalgamation of physical and digital systems will prove to be revolutionary. To elevate from the current state universities are required to prepare curriculum, academicians and students alike. Thus academia should weigh their capabilities putting effort to equip our generations with latest knowledge and skills to face future realism. Universities are required to enhance their approach and methods of education. Latest technologies such as Big Data Analytics, Artificial Intelligence, Augmented Reality, and Internet of Things, Cloud Computing and other advancements need to be focused in order for students to learn its application. This paper is based on qualitative research along with a deductive approach focused towards redesigning curriculum and teaching practices in line with IR4.0 practices. The research is focused upon various emerging challenges related to fundamental elements and objectives in academia. Based on the qualitative research a curriculum matrix has been proposed, the suggested matrix will enable universities to enhance their current curriculum in line with the technological competencies required in the upcoming era of Industry 4.0. [ABSTRACT FROM AUTHOR]

Development in information technology has resulted in revolutionizing all aspects of life and this revolution has been realized as Industrial Revolution 4.0 (IR4.0). The IR4.0 will reduce the gap between digital and physical world. Keeping ultramodern developments in view, an amalgamation of physical and digital systems will prove to be revolutionary. To elevate from the current state universities are required to prepare curriculum, academicians and students alike. Thus academia should weigh their capabilities putting effort to equip our generations with latest knowledge and skills to face future realism. Universities are required to enhance their approach and methods of education. Latest technologies such as Big Data Analytics, Artificial Intelligence, Augmented Reality, and Internet of Things, Cloud Computing and other advancements need to be focused in order for students to learn its application. This paper is based on qualitative research along with a deductive approach focused towards redesigning curriculum and teaching practices in line with IR4.0 practices. The research is focused upon various emerging challenges related to fundamental elements and objectives in academia. Based on the qualitative research a curriculum matrix has been proposed, the suggested matrix will enable universities to enhance their current curriculum in line with the technological competencies required in the upcoming era of Industry 4.0. [ABSTRACT FROM AUTHOR]

Technological developments as part of Industry 4.0 are leading to significant changes in terms of new systems, approaches, and management systems with a multitude of implications for human life. Social evolution from an agricultural society to an industrial society, and from an information society to a knowledge society has not only transformed manufacturing systems, but also how societies deal with other fields, such as education, health, and the environment. Unlike memorization-oriented education approaches, Education 4.0 is a new experience-based education system that uses technology and meets the expectations of today's world within the framework of personalized education needs. Recent literature highlights the importance of digital transformation in education and the use of an array of specific digital technologies. However, Education 4.0 emerges as a relatively new topic in the literature. In this study, the concept of Education 4.0 is examined and possible changes in known education systems are highlighted. The aim of this paper is to determine current research topics, explore knowledge gaps, and propose future directions in this field by reviewing the published literature on Education 4.0. Two different searches were made in the Web of Science core collection database, where journals were scanned and studies determined. Both quantitative analysis and qualitative discussion were used to analyze the state of the art. The study contributes a structured overview of Education 4.0-related publications and reports on the existing state of literature, categorize publications, analyze and link trends, highlight gaps, and accordingly guides future research. • The education system is changing with the development of technology. • Education 4.0 represents both the change in context and technology for learning. • This article reviews the state-of-the-art of existing Education 4.0 literature. • It determines the most used approaches and examines recent trends in Education 4.0. • It identifies knowledge gaps and limitations in Education 4.0 for future developments. [ABSTRACT FROM AUTHOR]

Development of competencies for Open Innovation (OI) plays a very important role since new skills and abilities are required at all levels: to design and adapt products and processes, to develop new business models and to modify the organization of work and processes. This paper analyzes Education 4.0 features, main components, and characteristics; adaptation of teaching and learning practices to changed requirements of Industry 4.0 for the successful implementation of the Open Innovation model. This paper systematically reviews a total of 48 WoS and Scopus studies, ultimately allowing us to determine components of Education 4.0 used in the framework of the OI model in recent years. Four research questions have been directed to data analysis. The results showed that (a) there is little literature research on issues related to important aspects in the dynamics of open innovation (partnerships, critical thinking, self-assessment, leadership, friendships, and risk-taking); (b) the main literature focuses on a comprehensive study of knowledge and skill parameters, application of appropriate strategies for their development, there are gaps in character development and meta-learning; (c) there is a noticeable lack of research on the competence framework of OI aimed at schoolchildren and the use of learning and teaching strategies to strengthen open educational innovations in schools; and d) there is a lack of research on development of OI competencies using cloud resources. This paper is intended for researchers, education and open innovation experts interested in the possibilities of educational technologies for the further dynamic development of the OI model. [ABSTRACT FROM AUTHOR]

[Display omitted] • A learning design cooperative framework LDCF is set to boost 21st century education. • The LDCF transforms classic HE settings to those that foster 21st century learning. • The LDCF recreates a u–learning stage and instills domain & 21st century knowledge. • The LDCF foments 21st century learners to acquire and develop 21st century skills. • Albeit learners met cognitive load, gained higher & even learning than control team. At present 21st century education boosts situated teaching approaches, meaningful learning habits, and experiential use of new technology, all of which enable learners to acquire domain knowledge and develop skills during seamless scholar labors. In this sense, students are motivated to learn by actively engaging in educational experiences performed in renewed stages with trendy resources and praxis, where they are involved in hands–on activities similar to true work. Hence, traditional academic facilities, curricula, content, materials, and practices should be transformed according to the needs and trends of an evolving world society that requires the use of smart and advanced technologies that empower teaching and learning duties. With the aim of contributing to cope with such a demand, a learning design cooperative framework is proposed to harness suitable technologies that upgrade classic academic sceneries and toils to recreate 21st century education settings. Thus, the framework is tested during a real case, where it leads the conversion of a typical engineering lab to a ubiquitous engineering lab that enables undergraduates to access digital content and cooperate with peers to automatize equipment proper to an industrial cell. Albeit experimental pupils were not trained to adapt to a novel situation and dealt with higher cognitive load, they reached a more superior and balanced learning than their control mates. As a result, evidence shows how a suitable learning design reforms a conventional scholar scene to feature 21st century education and guides successful technology–driven learning processes. [ABSTRACT FROM AUTHOR]

• The concept and vision of Education 4.0 in higher education are presented. • Four core components are integrated to shape the proposed concept of Education 4.0: (i) Competencies, (ii) Learning Methods, (iii) Information and Communication Technologies, and (iv) Infrastructure. • The components of Education 4.0 can apply to different educational levels and non-formal and informal educational environments. • Three different case studies were presented to illustrate how current programs adopt the concept and vision of Education 4.0. Technological progress and its rapid evolution have positively affected the industrial sector and different productive/service sectors. One of the service-sectors that have benefited the most has been Education. In this sector, the implementation of current and emerging technologies combined with innovative pedagogical procedures and best practices is known as Education 4.0, which, in this paper, is described and mapped according to the well-known periods of the four industrial revolutions and related to higher education. Likewise, four core components of Education 4.0 to be used as a reference for the design of new projects in educational innovation are proposed (i) Competencies, (ii) Learning Methods, (iii) Information and Communication Technologies, and (iv) Infrastructure. Finally, three case studies applied to Engineering Education illustrate how the proposed components are considered in educational programs' designs. [Display omitted] [ABSTRACT FROM AUTHOR]