Computational Intelligence for Technology Enhanced Learning


Book Description

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.




AI Injected e-Learning


Book Description

This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.




Computational Intelligence for Technology Enhanced Learning


Book Description

E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners’ performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity.




Artificial Intelligence Supported Educational Technologies


Book Description

This book includes a collection of expanded papers from the 2019 Sino-German Symposium on AI-supported educational technologies, which was held in Wuhan, China, March, 2019. The contributors are distinguished researchers from computer science and learning science. The contributions are organized in four sections: (1) Overviews and systematic perspectives , (2) Example Systems, (3) Algorithms, and (4) Insights gained from empirical studies. For example, different data mining and machine learning methods to quantify different profiles of a learner in different learning situations (including interaction patterns, cognitive modes, knowledge skills, interests and emotions etc.) as well as connections to measurements in psychology and learning sciences are discussed in the chapters.




Methodologies and Intelligent Systems for Technology Enhanced Learning, 8th International Conference


Book Description

This book presents the outcomes of the 8th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning held in Toledo (Spain) hosted by the University of Castilla-La Mancha from 20 th to 22nd June 2018. Further expanding the topics of the previous editions, the conference provided an open forum for discussing intelligent systems for technology enhanced learning (TEL) and their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone and web-based solutions and maker spaces, and also fostering entrepreneurship and increasing business startup ideas. It brought together researchers and developers from industry, the education field and the academic world to report on the latest scientific research, technical advances and methodologies.




Technologies, Artificial Intelligence and the Future of Learning Post-COVID-19


Book Description

This book aims to assess the experience of education during COVID-19 pandemic and explore the future of application of technologies and artificial intelligence in education. Education delivery requires the support of new technologies such as artificial intelligence (AI), the Internet of Things (IoT), big data, and machine learning to fight and aspire to new diseases. The academic community and those interested in education agree that education after the corona pandemic will not be the same as before. The book also questions the role of accreditation bodies (e.g., AACSB, etc.) to ensure the effectiveness and efficiency of technology tools in achieving distinguished education in times of crisis.




Cognitive Computing in Technology-Enhanced Learning


Book Description

Various technologies and applications such as cognitive computing, artificial intelligence, and learning analytics have received increased attention in recent years. The growing demand behind their adoption and exploitation in different application contexts has captured the attention of learning technology specialists, computer engineers, and business researchers who are attempting to decipher the phenomenon of personalized e-learning, its relation to already conducted research, and its implications for new research opportunities that effect innovations in teaching. Cognitive Computing in Technology-Enhanced Learning is a critical resource publication that aims to demonstrate state-of-the-art approaches of advanced data mining systems in e-learning, such as MOOCs and other innovative technologies, to improve learning analytics, as well as to show how new and advanced user interaction designs, educational models, and adoptive strategies can expand sustainability in applied learning technologies. Highlighting a range of topics such as augmented reality, ethics, and online learning environments, this book is ideal for educators, instructional designers, higher education faculty, school administrators, academicians, researchers, and students.




Computational Intelligence for COVID-19 and Future Pandemics


Book Description

The book covers a wide topic collection starting from essentials of Computational Intelligence to advance, and possible application types against COVID-19 as well as its effects on the field of medical, social, and different data-oriented research scopes. Among these topics, the book also covers very recently, vital topics in terms of fighting against COVID-19 and solutions for future pandemics. The book includes the use of computational intelligence for especially medical diagnosis and treatment, and also data-oriented tracking-predictive solutions, which are key components currently for fighting against COVID-19. In this way, the book will be a key reference work for understanding how computational intelligence and the most recent technologies (i.e. Internet of Healthcare Thing, big data, and data science techniques) can be employed in solution phases and how they change the way of future solutions. The book also covers research works with negative results so that possible disadvantages of using computational intelligence solutions and/or experienced side-effects can be known widely for better future of medical solutions and use of intelligent systems against COVID-19 and pandemics. The book is considering both theoretical and applied views to enable readers to be informed about not only research works but also theoretical views about essentials/components of intelligent systems against COVID-19/pandemics, possible modeling scenarios with current and future perspective as well as solution strategies thought by researchers all over the world.




The New Development of Technology Enhanced Learning


Book Description

The book addresses the main issues concerned with the new development of learning processes, innovative pedagogical changes, the effects of new technologies on education, future learning content, which aims to gather the newest concepts, research and best practices on the frontiers of technology enhanced learning from the aspects of learning, pedagogies and technologies in learning in order to draw a picture of technology enhanced learning in the near future. Some issues like “e-learning ... m-learning ... u-learning – innovative approaches,” “the Framework and Method for Understanding the New Generation Students,” “Context-aware Mobile Role Playing Game for Learning,” “ Pedagogical issues in content creation and use: IT literacy through Spoken Tutorials,” “Supporting collaborative knowledge construction and discourse in the classroom,” “Digital Systems for Hierarchical Open Access to Education,” “ Using Annotated Patient Records to Teach Clinical Reasoning to Undergraduate Students of Medicine,” “ Utilizing Cognitive Skills Ontology for Designing Personalized Learning Environments” and “Using Interactive Mobile Technologies to Develop Operating Room Technologies Competency” are discussed in separate chapters.




Methodologies and Intelligent Systems for Technology Enhanced Learning


Book Description

This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of ebuTEL 2013 conference which took place in Trento, Italy, on September, 16th 2013 and of mis4TEL 2014 conference, which took take place in Salamanca, Spain, on September, 4th-6th 2014. This conference series are an open forum for discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for its design or evaluation.