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The emergence of new technologies has developed a new industrial need for engineering graduate students. This modern industry needs a modern educational framework to support further development. This research revolves around developing the learning methodological approach for university courses that aligns with Education 4.0 and can fulfill the essential knowledge requirements for future engineers in Industry 4.0. We used a constructive approach as a baseline methodology already proven in the field of engineering education. On the other hand, we modified this approach by implementing Industry 4.0 standards, such as Agile methodology, DevOps tools, and Artificial intelligence chatbots. In this way, we managed to establish one more step in the digital transformation of education as one of the paramount cornerstones of Industry 4.0. As a result, during the course, Agile methodology and DevOps tools created a learning environment very similar to the real software development environment in companies. The efficiency of the delivery of the learning material also increased by implementation and integration of AI chatbots. This was tracked by the number of projects developed during course implementation. The study showed that in the field of education, the implementation of novel approaches developed in the industry to increase efficiency can be implemented in the educational environment. It also showed that the implementation of those methodologies does not hinder but improves the efficiency of the educational cycle. [ABSTRACT FROM AUTHOR]

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]

Copyright of Revista Gênero e Interdisciplinaridade is the property of Instituto de Ensino e Pesquisa Periodicojs and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Personalized learning, a pedagogical approach tailored to individual needs and capacities, has garnered considerable attention in the era of artificial intelligence (AI) and the fourth industrial revolution. This systematic literature review aims to identify key drivers of personalized learning and critically assess the role of AI in reinforcing these drivers. Following PRISMA guidelines, a thorough search was conducted across major peer-reviewed journal databases, resulting in the inclusion of 102 relevant studies published between 2013 and 2022. A combination of qualitative and quantitative analyses, employing categorization and frequency analysis techniques, was performed to discern patterns and insights from the literature. The findings of this review highlight several critical drivers that contribute to the effectiveness of personalized learning, both from a broad view of education and in the specific context of e-learning. Firstly, recognizing and accounting for individual student characteristics is foundational to tailoring educational experiences. Secondly, personalizing content delivery and instructional methods ensures that learning materials resonate with learners' preferences and aptitudes. Thirdly, customizing assessment and feedback mechanisms enables educators to provide timely and relevant guidance to learners. Additionally, tailoring user interfaces and learning environments fosters engagement and accessibility, catering to diverse learning styles and needs. Moreover, the integration of AI presents significant opportunities to enhance personalized learning. AI-driven solutions offer capabilities such as automated learner profiling, adaptive content recommendation, realtime assessment, and the development of intelligent user interfaces, thereby augmenting the personalization of learning experiences. However, the successful adoption of AI in personalized learning requires addressing various challenges, including the need to develop educators' competencies, refine theoretical frameworks, and navigate ethical considerations surrounding data privacy and bias. By providing a comprehensive understanding of the drivers and implications of AI-driven personalized learning, this review offers valuable insights for educators, researchers, and policymakers in the Education 4.0 era. Leveraging the transformative potential of AI while upholding robust pedagogical principles, personalized learning holds the promise of unlocking tailored educational experiences that maximize individual potential and relevance in the digital economy. [ABSTRACT FROM AUTHOR]

This study investigates the demand for digital learning and the application of Quality 4.0 for future education in higher education institutes (HEIs). Quality 4.0 leads to digital transformation for innovation, excellence, and performance. Over the past decade, the educational landscape has undergone a revolution due to digitalization and enhancing academic development. The present study, through a systematic review of the literature published from 2017 to 2023, aims to highlight how digital advancements have played a critical role in improving the people and operations of higher education institutes to meet the growing challenges in the education sector. The implementation of Quality 4.0 and the application of its practices in HEIs can drive innovation through technological advancements in the Internet of Things (IOT), blended learning, and artificial intelligence (AI) to meet the increasing demand for digital learning. The findings suggest that digital learning through various technologies brings about significant changes in employment, skill development, and the educational environment. However, these advancements do not come without challenges, including the imperative of faculty development, the establishment of robust technological infrastructure, ethical considerations in AI implementation, and quality management. More research is needed to address the gap in understanding the applicability of Quality 4.0 and the demand for digital learning in higher education institutes. [ABSTRACT FROM AUTHOR]

The digital transformation has profoundly affected every facet of human life, with technological advancements potentially reshaping the economy, society, and our daily living and working modalities. Artificial Intelligence (AI), particularly Generative AI (GAI), has emerged as a pivotal disruption in education, showcasing the capability to produce diverse and context-relevant content. Generative Artificial Intelligence (GAI) has revolutionized natural language processing, computer vision, and creative arts. Large language models (LLMs) like GPT-4 and Open Assistant and tools like DALL-E and Midjourney for the visual and creative domain are increasingly used for various tasks by students and others with critical information needs. AI presents novel avenues for crafting effective learning activities and developing enhanced technology-driven learning applications in the educational sector. However, integrating AI with a pedagogical focus pose challenge. Education 4.0, which integrates emerging technologies and innovative strategies, aims to prepare new generations for a technologically fluid world. This systematic literature review aims to analyze the use of LLMs in higher education within the context of Education 4.0's pedagogical approaches, identifying trends and challenges from a selection of 83 relevant articles out of an initial set of 841 papers. The findings underscore the significant potential of LLMs to enrich higher education, aligning with Education 4.0 by fostering more autonomous, collaborative, and interactive learning. It highlights the necessity for human oversight to ensure the quality and accuracy of AI-generated content. It addresses ethical and legal challenges to ensure equitable implementation, suggesting an exploration of LLM integration that complements human interaction while maintaining academic integrity and pedagogical foundation. [ABSTRACT FROM AUTHOR]

This review explores how artificial intelligence (AI henceforth) can reshape education through insights from situated learning literature. The objective was to critically examine opportunities and challenges of situated learning, and how AI could augment strengths while overcoming obstacles. A systematic review using the PRISMA method analyzed 60 articles from peer-reviewed journals over three decades. Key concepts associated with situated learning were extracted and analyzed qualitatively and quantitatively. Findings identified major obstacles: the traditional school system's one-way passive learning; the predominant educational approach fixated on predefined outcomes; and teachers' lack of contextual knowledge. AI presents solutions including adaptive systems tailored to students' evolving needs; intelligent tutoring situated in authentic scenarios; automation of administrative tasks; and data-driven teacher support. When implemented thoughtfully, AI has the potential to enhance situated learning through increased personalization, interactivity, and realworld connections. This promises a better effective, adaptive education - but human guidance remains essential for ethical grounding. This review offers teachers, researchers, and policymakers valuable insights on integrating both AI and situated learning to keep education relevant in an interconnected world. [ABSTRACT FROM AUTHOR]

Purpose: The article's primary goal is to analyze artificial intelligence's (AI) development in the educational system. Design/methodology/approach: In the article, deep analysis of the consequences of technological progress For process teaching, identifying challenges and opportunities related to dynamic AI development. Underlined the necessity of facing changes in education appearances the AI and valuable looking at the implications for ways driving lessons, content teaching, and self-education. Findings: AI is a new way of solving problems, especially during crises. The new technologies determine the way and the speed of problem-solving. The new era of education requires modern methods concerning AI. Research limitations/implications: The surveys discussed in this article may contribute to further empirical studies, including but not limited to initiating works to improve innovation in artificial intelligence. Practical implications: Education in the age of AI demands a holistic approach, connecting modern technologies with traditional teaching methods and considering the ethical and social aspects of technological development. Originality/value: Originality work is about a consistent approach based on research literature, which can be a basis for further empirical research regarding the impact of AI on education and modification of learning methods. [ABSTRACT FROM AUTHOR]

The emerging generative artificial intelligence (AI) chatbots, such as Chat Generative Pre-Trained Transformer (ChatGPT), have recently taken different disciplines by surprise. Very few scholarly papers show the collaborative effort by researchers on the impact of generative AI in higher education (HE) and its implication on HE disciplines and activities. This paper uses citation network analysis by deep searching the different research articles using Scopus databases. A bibliographic analysis tool is used to reveal patterns of application of generative AI chatbots in HE, collaboration of generative AI research, and generative AI in HE among different countries of the world. Furthermore, it investigates the thematic topics that generative AI in HE researchers are studying. Research papers from Scopus databases were sampled. The sampling timeframe is from January 2022 to September 2023. This paper presents the preliminary findings of the work that was conducted for a doctoral thesis in computer science and information technology. The preliminary findings show that Spain, the United States of America (USA), and Australia are countries that collaborate more often on the development of generative AI chatbots. In the study, generative AI chatbots were most likely to cover plagiarism and essay inclusion, but very few covered research for postgraduate enterprises. The study concludes that Chatbots are an important part of teaching technology that should be embraced by higher education. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Education Research (1680-6360) is the property of Angle Publishing Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Iskolakultúra is the property of University of Szeged, Faculty of Arts & Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Now a days with the rapidly increasing development of technology and communication system, the implementation of blockchain is continuously increasing in various sectors. With the increase in massive data in educational sectors there arise a requirement of handling such enormous data. This can be easily and securely handled by blockchain technology due to its scalability, robustness, and resilience characteristics. In this paper, a methodology is presented for systematic meta-analysis of the blockchain applications, technologies, and integration of next-gen technologies for the deployment of education 4.0. The bibliometric analysis, the methodology is divided into three steps: selection strategy, inclusion strategy, and meta-analysis of research contributions are provided based on PRISMA-P. In the selection strategy, different research sources are searched. Selection and sorting of contributing research articles are performed in the inclusion strategy and finally, in a meta-analysis, the critical assessment of the educational management system and security aspects with blockchain deployment is performed. It was observed that most of the research contributions are theoretical concept based without any practical validations. From the results, it was also observed that the blockchain designs presented mainly focus on confidentiality, integrity, and availability. But apart from these, other security concerns such as scalability, flexibility, authorization, mutual authentication, attack resistant, etc. are not explored most. Further, the paper presented a critical analysis of next-gen technologies with blockchain for future education 4.0. This paper is focused to analyze the growing demand of the educational blockchain paradigm (EBP). For this paper presented a meta-analysis of existing research contributions concerning the application area, technology used, real-world examples, and next-gen technologies in education 4.0. Therefore, this paper will enlighten the focus of researchers for future research innovations. [ABSTRACT FROM AUTHOR]

Digital Language Teaching 5.0, a new language teaching paradigm that applies the digital pedagogies and technologies of the fifth Industrial Revolution (Industry 5.0), is expected to transform the English language teaching and learning landscape soon, as the world continuously seeks innovative solutions to the educational challenges brought by the COVID-19 pandemic. As a new concept, it draws inquiries and discussions on how it will influence language curriculum, instruction and assessment in the post-pandemic digital age, what technologies and practices will be adopted in schools to align with its purposes, and what competencies pre-service and in-service language teachers will need to be able to actualize it in their own contexts. This paper aims to address the foregoing issues by discussing relevant concepts, trends and practices. It begins by providing a brief background about Education 4.0, its key features, technologies and trends as applied in English language teaching. It then proceeds to the discussion of Education 5.0 and Digital Language Teaching 5.0 with their distinct features, purposes, technologies and practices. Lastly, it explores the skills and competencies under Digital Language Teaching 5.0 and discusses how pre-service and in-service language teachers can develop and enhance such competencies through various formal and alternative language teacher development activities. It concludes with insights on some issues raised and recommendations for successful implementation. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the 'Carol I' National Defence University / Buletinul Universitatii Nationale de Aparare 'Carol I' is the property of Carol I National Defence University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article explores the connection between artificial intelligence (AI) and language learning in the context of Education 4.0, highlighting how the former revolutionizes the latter with the introduction of emerging technologies and innovations in education. The article discusses how AI improves the processes of language learning through personalized learning experiences, interactive practice, and automated assessment. AI can be used to create diverse learning materials and immersive experiences that align with the principles of Education 4.0. When used correctly, AI can bring numerous benefits to language learning, such as increased efficiency, greater student engagement in the teaching-learning process, and the accessibility of content from anywhere and on any device. Additionally, it emphasizes the need to adopt Education 4.0 accompanied by the development of content that equips students with the necessary skills in the digital age. The article also highlights the importance of integrating AI and Education 4.0 in language learning to promote critical thinking, problem-solving skills, and digital literacy

RationaleThe development of the complex thinking meta-competency in the education of university students potentially promotes high capacities, where artificial intelligence (AI) might work as a supporting structure.ObjectiveThis proof-of-concept study of an AI-based platform aimed to integrate a sequence of activities into the design of an online platform to assess the development of complex thinking competency in higher education students.MethodThe Transition Design method was used within an Ideathon event supported by an AI platform to provide students with a sharing economy challenge. A total of 31 university students from five university campuses in Mexico synchronously participated. An instrument was applied in the pre-test and post-test phases to explore the complex thinking meta-competency and its sub-competencies of critical, innovative, scientific, and systemic thinking.ResultsTwo hypotheses were tested, both of which turned out to be true: (a) the functioning of the constructed learning situation and (b) the model of the learning situation.ConclusionThese findings may be of value to scientific and academic communities, as well as social and business organizations interested in developing high capacities of complex thinking and educational innovations using digital platforms.

Copyright of Journal of Technology & Information Education is the property of Palacky University in Olomouc and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purpose of this paper is to shows the required educational system which drives to the societal needs. In higher education programs, the quality edification continues to deteriorate irrespective of paying supplementary attention. There are many factors which influenced the education system and at each steps our perception is changed and developed. The problem is arisen when industry 4.0 of the twenty-first century is came with emerged technologies, which takes one step ahead with automation technologies like IoT, Artificial Intelligence, Machine Learning in all manufacturing technologies and making smart industries. The motive of education is to realize the truth of current scenario of industries, society and country. The main challenge and constraint of education required changes in educators' attitude, textbooks, curriculum, education technologies, pedagogies, innovation, research, reforms and policies of education 4.0. The education 5.0 is more about people than technologies. All these challenging parts can be overcome by creating values to identify the creative potential of human beings by enhancing education system known as education 5.0. The answer of all societal problems is continuously overcome by problems solving attitude through rehumanizing values among students as well as in educators. In this regard, to know the all-education philosophy and update learning practices to implement education 5.0 has been discussed. [ABSTRACT FROM AUTHOR]

With the developments experienced in recent years, the current period, called Industry 4.0, which includes concepts such as the internet of objects, artificial intelligence, dark factories, and embedded systems, has influenced many areas. One of the areas most affected by these developments is education. The knowledge level of pre-service teachers about these concepts is very important in this study, the purpose was to determine the pre-service science teachers' levels of awareness of Industry 4.0 concepts. "Industry 4.0 Conceptual Awareness Scale" prepared by Dogan and Baloglu (2020) was used as a data collection tool. The findings obtained in the study revealed that the preservice teachers' levels of awareness of Industry 4.0 concepts differed significantly concerning the variables of gender, academic average grade, mother and father's education levels, family income, following scientific journals and websites, and knowing the technological concepts prominent in education. Consequently, it was seen that the pre-service science teachers' awareness of Industry 4.0 concepts was generally at a level below the average, except for certain concepts. [ABSTRACT FROM AUTHOR]

This article presents a model for the implementation of cell phones as a functional component of educational robotics. With this, a massification of the educational practices of robotics can be achieved, and an approach to innovative solutions with the use of everyday components. The above constitutes an easily adaptable model to develop specific skills of students in STEM areas with a low investment. As a result, it was evidenced that robotics facilitates the possibility of introducing technology in the teaching and learning processes through these kits that have sensors, mechanisms, parts and characteristics that can be coupled and integrated with a cell phone to assemble a functional robot. Through an online questionnaire on the integration of educational robotics and cell phones, the interest of engineering students and teachers was verified, so that their higher education institutions include robotics in their training processes, thus contributing to the preparation to face the challenges of the Education 4.0 line within the context of Industry 4.0. [ABSTRACT FROM AUTHOR]

To meet expectations of stakeholders in Education 4.0, the inclination towards acceptance, testing, and implementation of Voice Assistants has increased at a faster pace in western universities. This study has been done to understand the present level of performance and capability of voice assistants in answering the basic queries of users from Indian Higher education sector. Three voice assistants namely Amazon Alexa, Microsoft Cortana, and Google Assistant have been considered for a survey in which 100 students participated and tested the performance of these three voice assistants by asking basic questions related to admission and examination. A set of total 14 questions has been selected to be asked by user in both the categories. Category 1 related to Admissions contained 7 little complex questions while category 2 related to Examination had 7 direct and simpler questions. Responses of the users were noted down and after careful analysis, the explanations have been deduced about performance of these voice assistants in factors considered: understanding of voice and language of user, understanding of basic meaning of the question, request to repeat the question, whether the answer was given by voice assistants and quality of the answer received. As per the results, various observations have been noted that may further help Artificial Intelligence developers and programmers to understand the success and failure of voice assistants and accordingly bring improvements in their performance level. This study also helps in knowing about huge applications, contributions and benefits these voice assistants offer to the stakeholders. Once the improvements are incorporated by the developers, marketing professionals can boost the absorption and use of voice assistants in massive higher education sector of India by convincing the important stakeholders that also paves a way to tap into more undiscovered possibilities about use of Artificial Intelligence in higher education system at global level. [ABSTRACT FROM AUTHOR]

Copyright of Journal Computer Technology is the property of ECORFAN-Mexico S.C. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The current paper aims to take a glimpse at the potential of the advanced technologies present today such as the Internet of Things (IoT), Augmented Reality (AR), Virtual Reality (VR), Artificial Intelligence (AI), Cloud Technologies, Mobile Internet, etc. that have the potential to improve everyday life with new, interactive experiences that can change the way we perceive many of our daily activities. These technologies are pushing the society towards the development of Industry 4.0 and implicitly, Education 4.0. In the context of the COVID-19 pandemic, the pressing need for a digitized society and education was felt, where technology plays a key role in the teachinglearning process. Thus, the concepts of Smart learning, Smart city, Digital campus, E-education and many such notions are starting to take shape more and more, aiming to adopt the trend of smart...everything. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Social Sciences Institute / Sosyal Bilimler Enstitüsü Dergisi is the property of Bingol University / Rectorate and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. As a consequence, there is a growing demand for educational material that introduces science and engineering students to technologies, such as Artificial Intelligence (AI) and Brain–Computer Interfaces (BCI). Thus, our contribution towards the development of this material is to create a test bench for BCI given the basis and analysis on how they can be discriminated against. This is shown using different AI methods: Fisher Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), Restricted Boltzmann Machines (RBM) and Self-Organizing Maps (SOM), allowing students to see how input changes alter their performance. These tests were done against a two-class Motor Image database. First, using a large frequency band and no filtering eye movement. Secondly, the band was reduced and the eye movement was filtered. The accuracy was analyzed obtaining values around 70∼80% for all methods, excluding SVM and SOM mapping. Accuracy and mapping differentiability increased for some subjects for the second scenario 70∼85%, meaning either their band with the most significant information is on that limited space or the contamination because of eye movement was better mitigated by the regression method. This can be translated to saying that these methods work better under limited spaces. The outcome of this work is useful to show future scientists and engineers how BCI experiments are conducted while teaching them the basics of some AI techniques that can be used in this and other several experiments that can be carried on the framework of Education 4.0.

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]

Education 4.0 is looking to prepare future scientists and engineers not only by granting them with knowledge and skills but also by giving them the ability to apply them to solve real life problems through the implementation of disruptive technologies. As a consequence, there is a growing demand for educational material that introduces science and engineering students to technologies, such as Artificial Intelligence (AI) and Brain–Computer Interfaces (BCI). Thus, our contribution towards the development of this material is to create a test bench for BCI given the basis and analysis on how they can be discriminated against. This is shown using different AI methods: Fisher Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), Restricted Boltzmann Machines (RBM) and Self-Organizing Maps (SOM), allowing students to see how input changes alter their performance. These tests were done against a two-class Motor Image database. First, using a large frequency band and no filtering eye movement. Secondly, the band was reduced and the eye movement was filtered. The accuracy was analyzed obtaining values around 70∼80% for all methods, excluding SVM and SOM mapping. Accuracy and mapping differentiability increased for some subjects for the second scenario 70∼85%, meaning either their band with the most significant information is on that limited space or the contamination because of eye movement was better mitigated by the regression method. This can be translated to saying that these methods work better under limited spaces. The outcome of this work is useful to show future scientists and engineers how BCI experiments are conducted while teaching them the basics of some AI techniques that can be used in this and other several experiments that can be carried on the framework of Education 4.0. [ABSTRACT FROM AUTHOR]

Small and medium-sized enterprises (SMEs) in Europe risk their competitiveness if they fail to embrace digitalization. Indeed, SMEs are aware of the need to digitalize—more than one in two SMEs are concerned that they may lose competitiveness if they do not adopt new digital technologies. However, a key obstacle is related with decision-makers' lack of awareness concerning digital technologies potential and implications. Some decision-makers renounce digital transition simply because they do not understand how it can be incorporated into the business. Take into account this common reality, especially among SMEs, this research project intends to identify the skills and subjects that need to be addressed and suggests the educational methodology and implementation strategy capable of maximizing its success. Therefore, and supported by a focused group research methodology, an innovative training program, oriented to decision-makers, was designed and implemented. The program was conceived based on a self-directed learning methodology, combining both asynchronous lecture/expositive and active training methodologies, strongly based on state-of-the-art knowledge and supported by reference cases and real applications. It is intended that the trainees/participants become familiar with a comprehensive set of concepts, principles, methodologies, and tools, capable of significantly enhancing decision-making capability at both strategic and tactical level. The proposed programme with a multidisciplinary scope explores different thematic chapters (self-contained) as well as cross-cutting thematic disciplines, oriented to the Industry 4.0 and digital transformation paradigm. Topics related with Digital Maturity Assessment, Smart Factories and Flexible Production Systems, Big Data, and Artificial Intelligence for Smarter Decision-Making in Industry and Smart Materials and Products, as well as new production processes for new business models. Each thematic chapter in turn is structured around a variable set of elementary modules and includes examples and case studies to illustrate the selected topics. A teaching-learning methodology centered on an online platform is proposed, having as a central element, a collection of videos complemented by a set of handouts that organize the set of key messages and take-ways associated with each module. In this paper, we present the design and practice of this training course specifically oriented to decision-makers in SME. [ABSTRACT FROM AUTHOR]

Education is facing challenges to keep pace with the widespread introduction of robots and digital technologies in industry and everyday life. These challenges necessitate new approaches to impart students at all levels of education with the knowledge of smart connected robot systems. This paper presents the high-school enrichment program Intelligent Robotics and Smart Transportation, which implements an approach to teaching the concepts and skills of robot connectivity, collaborative sensing, and artificial intelligence, through practice with multi-robot systems. The students used a simple control language to program Bioloid wheeled robots and utilized Phyton and Robot Operating System (ROS) to program Tello drones and TurtleBots in a Linux environment. In their projects, the students implemented multi-robot tasks in which the robots exchanged sensory data via the internet. Our educational study evaluated the contribution of the program to students' learning of connectivity and collaborative sensing of robot systems and their interest in modern robotics. The students' responses indicated that the program had a high positive contribution to their knowledge and skills and fostered their interest in the learned subjects. The study revealed the value of learning of internet of things and collaborative sensing for enhancing this contribution. [ABSTRACT FROM AUTHOR]