Artificial intelligent based teaching and learning approaches: A comprehensive review

The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates

Artificial Intelligence in Education

Artificial Intelligence (AI) technologies have been researched in educational contexts for more than 30 years (Woolf 1988; Cumming and McDougall 2000; du Boulay 2016). More recently, commercial AI products have also entered the classroom. However, while many assume that Artificial Intelligence in Education (AIED) means students taught by robot teachers, the reality is more prosaic yet still has the potential to be transformative (Holmes et al. 2019). This chapter introduces AIED, an approach that has so far received little mainstream attention, both as a set of technologies and as a field of inquiry. It discusses AIED’s AI foundations, its use of models, its possible future, and the human context. It begins with some brief examples of AIED technologies

Preparing teachers for the application of AI-powered technologies in foreign language education

As any other area of human lives, current state of foreign language education has been greatly influenced by the latest developments in the modern information communication technologies. The paper focuses specifically on the incorporation of artificial intelligence (AI), which includes a wide range of technologies and methods, such as machine learning, adaptive learning, natural language processing, data mining, crowdsourcing, neural networks or an algorithm, into foreign language learning and teaching. First, the paper is concerned with changes brought to foreign language education specifically through the application of AI-powered tools and discusses ICALL (intelligent computer assisted language learning) as a subset of CALL. Second, it summarizes eight types of AI-powered tools for foreign language education and related results of the existing research, however scarce it is. Third, it discusses the frame for effective preparation of foreign language teachers in order to integrate AI-powered tools into their teaching to make it easier, less time-consuming and more effective. The author argues for reconsideration of the existing frames of requirements for CALL teachers.[KEGA 001TTU-4/2019

AI in Learning: Designing the Future

AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers

Application-driven visual computing towards industry 4.0 2018

245 p.La Tesis recoge contribuciones en tres campos: 1. Agentes Virtuales Interactivos: autónomos, modulares, escalables, ubicuos y atractivos para el usuario. Estos IVA pueden interactuar con los usuarios de manera natural.2. Entornos de RV/RA Inmersivos: RV en la planificación de la producción, el diseño de producto, la simulación de procesos, pruebas y verificación. El Operario Virtual muestra cómo la RV y los Co-bots pueden trabajar en un entorno seguro. En el Operario Aumentado la RA muestra información relevante al trabajador de una manera no intrusiva. 3. Gestión Interactiva de Modelos 3D: gestión online y visualización de modelos CAD multimedia, mediante conversión automática de modelos CAD a la Web. La tecnología Web3D permite la visualización e interacción de estos modelos en dispositivos móviles de baja potencia.Además, estas contribuciones han permitido analizar los desafíos presentados por Industry 4.0. La tesis ha contribuido a proporcionar una prueba de concepto para algunos de esos desafíos: en factores humanos, simulación, visualización e integración de modelos

Integrating Game Engines into the Mobile Cloud as Micro-services

Game engines have been widely adopted in fields other than games, such as data visualization and game-based education. As the number of mobile devices owned by each person increases, extra resources are available in personal device clouds, expanding typical learning space to outside of the classroom and increasing possibilities for teacher-student interactions. Owning multiple devices poses the problem of how to make use of idle resources on devices that are slightly dated or lack portability compared to newer models. Such resources include CPU power, display, and data storage. In order to solve this problem, an architecture is proposed for mobile applications to access these resources on various mobile devices. The main approach used here is to divide an application into several modules and distribute them over a personal device cloud (formed by same-user-owned devices) as micro-services. In this architecture, game engines will be incorporated as a render module to tap in its rendering capability. Additionally, modules will communicate using CoAP which has minimal overhead. To evaluate the feasibility of such architecture, a prototype is implemented and deployed over a mobile device, and tested in a modest context that is similar to real life settings

AI in Learning: Designing the Future

AI (Artificial Intelligence) is predicted to radically change teaching and learning in both schools and industry causing radical disruption of work. AI can support well-being initiatives and lifelong learning but educational institutions and companies need to take the changing technology into account. Moving towards AI supported by digital tools requires a dramatic shift in the concept of learning, expertise and the businesses built off of it. Based on the latest research on AI and how it is changing learning and education, this book will focus on the enormous opportunities to expand educational settings with AI for learning in and beyond the traditional classroom. This open access book also introduces ethical challenges related to learning and education, while connecting human learning and machine learning. This book will be of use to a variety of readers, including researchers, AI users, companies and policy makers

Online dispute resolution: an artificial intelligence perspective

Litigation in court is still the main dispute resolution mode. However, given the amount and characteristics of the new disputes, mostly arising out of electronic contracting, courts are becoming slower and outdated. Online Dispute Resolution (ODR) recently emerged as a set of tools and techniques, supported by technology, aimed at facilitating conflict resolution. In this paper we present a critical evaluation on the use of Artificial Intelligence (AI) based techniques in ODR. In order to fulfill this goal, we analyze a set of commercial providers (in this case twenty four) and some research projects (in this circumstance six). Supported by the results so far achieved, a new approach to deal with the problem of ODR is proposed, in which we take on some of the problems identified in the current state of the art in linking ODR and AI.The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009).Acknowledgments. The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006), which is a research project supported by FCT (Science & Technology Foundation), Portugal. The work of Davide Carneiro is also supported by a doctoral grant by FCT (SFRH/BD/64890/2009)

Implementation of business simulation games as learning tool: an example from University of Algarve

Game-based learning environments in education are a valuable asset, as well as their potential benefits are unquestionable (Guillén-Nieto & Aleson-Carbonell, 2012). Yet, recent studies concerning academic achievement have reported contradictory or ambiguous findings. It is also interesting that empirical studies devoted to Management courses are not abundant and focus on: single unit courses (e.g., Edelheim & Ueda, 2007), units with low levels of interdisciplinarity (e.g., Pasin & Giroux, 2011), non-longitudinal studies (e.g., Sørensen, 2011) or games usability (e.g., Blažič et al., 2012). Therefore, the leading Author produced the following research query: can GBL (Cesim Global Challenge) be a useful and productive tool to support Management students for effective learning towards complex contexts while enhances engagement? A case study approach will be used (University of Algarve)