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Cognitive Computing in Technology-Enhanced Learning, 1st Edition

  • Miltiadis D. Lytras
  • Naif Aljohani
  • Linda Daniela
  • Published By:
  • ISBN-10: 1522590323
  • ISBN-13: 9781522590323
  • DDC: 371.33
  • 345 Pages | eBook
  • Original Copyright 2019 | Published/Released August 2020
  • This publication's content originally published in print form: 2019

  • Price:  Sign in for price

About

Overview

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.

Table of Contents

Front Cover.
Title Page.
Cpoyright Page.
Advances in Educational Technologies and Instructional Design (AETID) Book Series.
Titles in This Series.
Dedication.
Table of Contents.
Detailed Table of Contents.
Preface.
Foundations of Cognitive Computing and Learning Analytics.
1: Understanding Student Learning Behavior and Predicting Their Performance.
2: Enhancing the Credibility of the Decision-Making Journey Through Serious Games Learning Analytics.
3: Fostering Online Interactions Between Learners.
4: Principal Component Analysis on the Students' Perception of a Cognitive Assistant for Content Reinforcement in Higher Education.
Applications and Approaches of Cognitive Computing and Learning Analytics.
5: Managing the Learner Model With Multi-Entity Bayesian Networks in Adaptive Hypermedia Systems.
6: Virtual and Augmented Reality in Medical Education and Training: Innovative Ways for Transforming Medical Education in the 21st Century.
7: Eye Tracking Applications for E-Learning Purposes: An Overview and Perspectives.
8: The Exploration of Automated Image Processing Techniques in the Study of Scientific Argumentation.
9: Evaluation of Mobile Apps for Chinese Language Learning.
10: Modern Health Management With Cognitive Computing and Big Data Analytics.
11: Smart MM: Smart Movie Management System.
12: Virtual Reality in Visual Analytics of Large Datasets.
Glossary.
Compilation of References.
Related References.
About the Contributors.
Index.