Artificial Intelligence in Education
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In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine.
Matthew N. O. Sadiku
Matthew N. O. Sadiku is presently a Regents professor emeritus of electrical and computer engineering at Prairie View A&M University, Prairie View, TX. He is the author of over 1,450 professional papers and over 150 books. He is a Life Fellow of IEEE. His current research interests are in the areas of computational electromagnetic, computer science/networks, engineering education, and marriage counseling. He can be reached via email at [email protected]
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Artificial Intelligence in Education - Matthew N. O. Sadiku
Copyright © 2022 Matthew Sadiku.
All rights reserved. No part of this book may be used or reproduced by any means, graphic, electronic, or mechanical, including photocopying, recording, taping or by any information storage retrieval system without the written permission of the author except in the case of brief quotations embodied in critical articles and reviews.
iUniverse
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Because of the dynamic nature of the Internet, any web addresses or links contained in this book may have changed since publication and may no longer be valid. The views expressed in this work are solely those of the author and do not necessarily reflect the views of the publisher, and the publisher hereby disclaims any responsibility for them.
ISBN: 978-1-6632-3001-0 (sc)
ISBN: 978-1-6632-3434-6 (e)
Library of Congress Control Number: 2022900354
iUniverse rev. date: 01/26/2022
17475.pngContents
Chapter 1 INTRODUCTION
1.1 INTRODUCTION
1.2 COMPONENTS OF ARTIFICIAL INTELLIGENCE
1.3 APPLICATIONS
1.4 WEAK AND STRONG AI
1.5 GLOBAL ARTIFICIAL INTELLIGENCE
1.6 BENEFITS
1.7 CHALLENGES
1.8 CONCLUSION
REFERENCES
Chapter 2 AI IN EDUCATION
2.1 INTRODUCTION
2.2 REVIEW ON ARTIFICIAL INTELLIGENCE
2.3 POSSIBILITIES FOR AI IN EDUCATION
2.4 AI IN DIFFERENT LEVELS OF AI
2.5 APPLICATIONS OF AI IN EDUCATION
2.6 GLOBAL ADOPTION OF AI IN EDUCATION
2.7 BENEFITS
2.8 CHALLENGES
2.9 FUTURE OF AI EDUCATION
2.10 CONCLUSION
REFERENCES
Chapter 3 AI IN NATURAL SCIENCES
3.1 INTRODUCTION
3.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
3.3 WHAT ARE NATURAL SCIENCES?
3.4 APPLICATIONS OF AI IN NATURAL SCIENCES
3.5 BENEFITS
3.6 CHALLENGES
3.7 CONCLUSION
REFERENCES
Chapter 4 AI IN SOCIAL SCIENCES
4.1 INTRODUCTION
4.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
4.3 WHAT ARE THE SOCIAL SCIENCES?
4.4 APPLICATIONS OF AI IN SOCIAL SCIENCES
4.5 BENEFITS
4.6 CHALLENGES
4.7 GLOBAL AI MARKET
4.8 FUTURE OF SOCIAL SCIENCES
4.9 CONCLUSION
REFERENCES
Chapter 5 AI IN COMPUTER SCIENCE
5.1 INTRODUCTION
5.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
5.3 APPLICATIONS OF AI IN COMPUTER SCIENCE
5.4 ARTIFICIAL INTELLIGENCE AS LIBERAL ARTS
5.5 BENEFITS AND CHALLENGES
5.6 GLOBAL AI IN COMPUTER SCIENCE
5.7 CONCLUSION
REFERENCES
Chapter 6 AI IN ENGINEERNING
6.1 INTRODUCTION
6.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
6.3 AI AS A GENERAL-PURPOSE TECHNOLOGY
6.4 ARTIFICIAL INTELLIGENCE ENGINEERING
6.5 AI ENGINEERS
6.6 APPLICATIONS OF AI IN ENGINEERING
6.7 BENEFITS
6.8 CHALLENGES
6.9 GLOBAL AI ENGINEERING
6.10 CONCLUSION
REFERENCES
Chapter 7 AI IN BUSINESS
7.1 INTRODUCTION
7.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
7.3 ADOPTING AI IN YOUR BUSINESS
7.4 APPLICATIONS OF AI IN BUSINESS
7.5 BUSINESSES TRANSFORMED BY AI
7.6 BENEFITS
7.7 CHALLENGES
7.8 GLOBAL AI IN BUSINESS
7.9 CONCLUSION
REFERENCES
Chapter 8 AI IN MEDICINE
8.1 INTRODUCTION
8.2 OVERVIEW ON ARTIFICIAL INTELLIGENCE
8.3 APPLICATIONS OF AI IN MEDICINE
8.4 BENEFITS
8.5 CHALLENGES
8.6 GLOBAL AI IN MEDICINE
8.7 CONCLUSION
REFERENCES
Dedicated to our wives:
Janet, Lama, and Gloria
PREFACE
The quest for building an artificial brain developed in the fields of computer science and psychology. From ancient times, humans have been dreaming of creating a machine that can replicate the human brain. Such a machine is known as artificial intelligence (AI).
Artificial intelligence, sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. AI is an umbrella term John McCarthy, a computer scientist, coined in 1955 and defined as the science and engineering of intelligent machines.
AI is now the latest big game changer. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. AI is an interdisciplinary and comprehensive field covering numerous areas such as computer science, psychology, linguistics, philosophy, neurosciences, cognitive science, thinking science, information science, system science, and biological science. Today, AI is integrated into our daily lives in several forms, such as personal assistants, automated mass transportation, aviation, computer gaming, facial recognition at passport control, voice recognition on virtual assistants, driverless cars, companion robots, etc.
Although AI is a branch of computer science, there is hardly any field which is unaffected by this technology. Common areas of applications include agriculture, business, law enforcement, oil and gas, banking and finance, education, transportation, healthcare, engineering, automobiles, entertainment, manufacturing, speech and text recognition, facial analysis, telecommunications, and military. Artificial intelligence has endless potential to handle tasks commonly done by humans, including natural language processing, image recognition and data analytics, visual perception, decision-making, speech recognition, business process management, and even the diagnosis of disease, all of which normally require human intelligence.
Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) has become a field of scientific research for more than 30 years. AIED refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AIED has become a new trend in education. AI has become a top priority on the agenda of different countries around the world. Global adoption of AI technology in education is transforming the way we teach and learn. AI will impact the education field in the areas of administration, instruction, and personalized and individualized learning applications.
This book considers AIED in key areas in education and is divided into eight chapters. Besides chapter 1, each chapter covers a brief overview of AI to make it self-contained. Also, each chapter addresses that the global adoption of AI of the topic covered in the chapter.
Chapter 1 provides an overview on artificial intelligence. AI is not a single technology but a set of computational models and algorithms. Artificial intelligence has the following main branches: expert system, fuzzy logic, artificial neural network, machine learning, deep learning, natural language processing, and robotics.
Chapter 2 covers the positive impact of AI on educational applications. The field of education is a place where artificial intelligence is poised to make big changes. The implementation of AIED has several benefits for learners and educators. Educators may soon find themselves teaching in a digital classroom with AI at its heart.
Chapter 3 addresses the uses of AI in natural science, which is a branch of science concerned with the description, prediction, and understanding of natural phenomena. Essentially, natural science consists of physics, biology, and chemistry. AI has been applied in various sectors of the society with natural sciences as the frontrunner beneficiary. AI a powerful tool that can help scientists with their research, especially in modeling and prediction.
In chapter 4, the uses of AI in social sciences are discussed. The social sciences are all about how society works and how individuals interact with one another. They generally include economics, political science, sociology, cultural or social anthropology, social psychology, and social geography. Scholars of the social sciences seem to be losing touch with rapid advances in AI. It has now become clear that the concept of artificial intelligence can be revealed only through the convergence of natural sciences and social sciences.
Chapter 5 deals with various applications of AI in computer science. AI is a growing branch of computer science, which is the study of computers and computational systems. Computer science covers the theory, design, development, and application of computer software and systems. Due to the increasing demand for artificial intelligence, the demand for computer scientists is also increasing. As AI becomes more pervasive, relevant, and important, there is growing need for all students (including non-computer scientists) to learn how AI works and the potential ethical, legal, and societal issues associated with the use of AI.
Chapter 6 discusses various applications of AI in engineering. AI engineering is a discipline that combines the principles of systems engineering, software engineering, computer science, and human-centered design to create AI systems in accordance with human needs. AI is poised to fundamentally change the entire engineering profession and create many exciting job opportunities in the coming years. With the rapid deployment of AI in different industries, the demand for a trained, competent AI engineers is rising.
Chapter 7 deals with how AI is widely used in business. The business industry is in love with AI. Artificial intelligence in business is increasingly adopted into various companies for marketing, automation, raising revenue, streamlining operations, decreasing management expenditures, and engaging with customers. In today’s world, business operates in the era of data. Therefore, business owners must stay on top of trends, new techniques, and applications that are being developed to leverage artificial intelligence in business. Companies that implement AI throughout the organization will be at a great advantage.
Chapter 8 addresses artificial intelligence in medicine (AIM). Medicines are the common solution for the preventing and curing diseases. AIM refers to the application of AI technology in the diagnosis and treatment of patients. AI has started to revolutionize several areas in medicine and medical devices. Common AI medical applications include diagnosis, classification, therapy, and robotics. AI can be used to comb through mountains of health data (such as electronic health records [EHRs]), uncovering new insights and helping to predict disease risk. AI is poised to revolutionize the way in which medicine is practiced.
The second section of each chapter provides an overview of AI. This may seem repetitious, but it is intended to make the chapter self-contained. If it makes reading grievous, one might remember Zig Zigler’s quote, Repetition is the mother of learning, the father of action, which makes it the architect of accomplishment.
The book is a friendly introduction to various uses of AI in education. The presentation is clear, succinct, and informal, without proofs or rigorous definitions. The book provides researchers, students, and professionals a comprehensive introduction, applications, benefits, and challenges for each aspect of AIED. The author were motivated to write this book partly due to the lack of a single source of reference on these technologies. There are monographs on some of them, but there is none that combines different aspects of AIED. Hence, the book will help a beginner to have an introductory knowledge about these technologies. The main objective of the author is to provide a concise treatment that is easily digestible for AIED. It is hoped that the book will be useful to educators, students, practicing engineers, computer scientists, and information business managers.
We would like to thank those individuals who made this work possible. I am grateful to Dr. Pamela Obiomon, dean of the College of Engineering at Prairie View A&M University. We would like to thank Dr. Sudarshan Nelatury, Dr. Mahamadou Temberly, Dr. Emmanual Shadare, and Adedamola Omotoso for their contributions. Special thanks to our wives for ther support.
-Matthew N. O. Sadiku, S. M. Musa, and Uwakwe C. Chukwu
ABOUT THE AUTHOR
A. Matthew N. O. Sadiku received his B. Sc. degree in 1978 from Ahmadu Bello University, Zaria, Nigeria and his M.Sc. and Ph.D. degrees from Tennessee Technological University, Cookeville, TN in 1982 and 1984 respectively. From 1984 to 1988, he was an assistant professor at Florida Atlantic University, Boca Raton, FL, where he did graduate work in computer science. From 1988 to 2000, he was at Temple University, Philadelphia, PA, where he became a full professor. From 2000 to 2002, he was with Lucent/Avaya, Holmdel, NJ as a system engineer and with Boeing Satellite Systems, Los Angeles, CA as a senior scientist. He is presently a professor emeritus of electrical and computer engineering at Prairie View A&M University, Prairie View, TX.
He is the author of over 950 professional papers and over 90 books including Elements of Electromagnetics (Oxford University Press, 7th ed., 2018), Fundamentals of Electric Circuits (McGraw-Hill, 7th ed., 2021, with C. Alexander), Computational Electromagnetics with MATLAB (CRC Press, 4th ed., 2019), Principles of Modern Communication Systems (Cambridge University Press, 2017, with S. O. Agbo), and Emerging Internet-based Technologies (CRC Press, 2019). In addition to the engineering books, he has written Christian books including Secrets of Successful Marriages, How to Discover God’s Will for Your Life, and commentaries on all the books of the New Testament Bible. Some of his books have been translated into French, Korean, Chinese (and Chinese Long Form in Taiwan), Italian, Portuguese, and Spanish.
He was the recipient of the 2000 McGraw-Hill/Jacob Millman Award for outstanding contributions in the field of electrical engineering. He was also the recipient of Regents Professor award for 2012-2013 by the Texas A&M University System. He is a registered professional engineer and a fellow of the Institute of Electrical and Electronics Engineers (IEEE) for contributions to computational electromagnetics and engineering education.
He was the IEEE Region 2 Student Activities Committee Chairman. He was an associate editor for IEEE Transactions on Education. He is also a member of Association for Computing Machinery (ACM). His current research interests are in the areas of computational electromagnetic, computer networks, and engineering education. His works can be found in his autobiography, My Life and Work (Trafford Publishing, 2017) or his website: www.matthew-sadiku.com. He currently resides in Hockley, Texas. He can be reached via email at [email protected]
B. Sarhan M. Musa is a professor in Electrical and Computer Engineering Department at Prairie View A&M University. He holds a Ph.D. in Electrical Engineering from the City University of New York.