Reprint

AI in Education

Edited by
June 2022
114 pages
  • ISBN978-3-0365-4341-3 (Hardback)
  • ISBN978-3-0365-4342-0 (PDF)

This book is a reprint of the Special Issue AI in Education that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

Artificial intelligence (AI) is changing the world as we know it. Recent advances are enabling people, companies, and governments to envision and experiment with new methods of interacting with computers and modifying how virtual and physical processes are carried out. One of the fields in which this transformation is taking place is education. After years of witnessing the incorporation of technological innovations into learning/teaching processes, we can currently observe many new research works involving AI. Moreover, there has been increasing interest in this research area after the COVID-19 pandemic, driven toward fostering digital education.

Among recent research in this field, AI applications have been applied to enhance educational experiences, studies have considered the interaction between AI and humans while learning, analyses of educational data have been conducted, including using machine learning techniques, and proposals have been presented for new paradigms mediated by intelligent agents.

This book, entitled “AI in Education”, aims to highlight recent research in the field of AI and education. The included works discuss new advances in methods, applications, and procedures to enhance educational processes via artificial intelligence and its subfields (machine learning, neural networks, deep learning, cognitive computing, natural language processing, computer vision, etc.).

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
performance measurement; key performance indicators; educational data mining; institutes performance; governance; educational mining; machine learning; artificial intelligence; decision support systems; systematic literature review; learning styles; machine learning; hybrid university teaching; e-behaviour; big five personality; student performance; plagiarism; ethics; academic dishonesty; online education; higher education; AS&P model; Pakistan