Cognitive Computing in Technology-Enhanced Learning

Cognitive Computing in Technology-Enhanced Learning

Miltiadis D. Lytras (Deree – The American College of Greece, Greece & Effat University, Saudi Arabia), Naif Aljohani (King Abdulaziz University, Saudi Arabia), Linda Daniela (University of Latvia, Latvia) and Anna Visvizi (Deree – The American College of Greece, Greece & Effat University, Saudi Arabia)
Release Date: May, 2019|Copyright: © 2019 |Pages: 345
ISBN13: 9781522590316|ISBN10: 1522590315|EISBN13: 9781522590323|DOI: 10.4018/978-1-5225-9031-6


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.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Advanced Learning Systems
  • Augmented Reality
  • Blended Learning
  • Deep Learning
  • E-Research
  • Ethics
  • Learner Profiling
  • Machine Learning
  • Massive Open Online Course
  • Online Learning Environments
  • Predictive Modeling
  • Social Media

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Naif R. Aljohani is Assistant Professor and Head of Department of Information Systems at the Faculty of Computing and Information Technology in King Abdul Aziz University, Jeddah, Saudi Arabia. He holds a PhD in Computer Science from the University of Southampton, UK. He received the Bachelor’s degree in Computer Education from King Abdul Aziz University, 2005. In 2009, he received the Master degree in Computer Networks from La Trobe University, Australia. His research interests are in the areas of mobile and ubiquitous computing, mobile and ubiquitous learning, learning and knowledge analytics, semantic web, Web Science, technology enhanced learning and human computer interaction. He has more than 40 research publications.
Linda Daniela - Dr. Daniela is the professor and senior researcher at the University of Latvia; Chair of the Council for Promotion in Pedagogy of the University of Latvia; Head of the Scientific Institute of Pedagogy; Expert of Education at the Council of Sciences of the Republic of Latvia. Her research interests include virtual education, smart education, educational technologies for learning, educational robotics, educational processes and solutions for reducing social exclusion from the educational processes. Professor is an author and co-author of publications about processes in all dimensions of education. She has been involved in several projects, she is an editor and co-editor of several books and journals, and she is a scientific adviser for doctoral and master thesis.