Teaching And Learning In The Digital Era Issues And Studies Jun Xu

Teaching And Learning In The Digital Era Issues
And Studies Jun Xu download
https://ebookbell.com/product/teaching-and-learning-in-the-
digital-era-issues-and-studies-jun-xu-56773440
Explore and download more ebooks at ebookbell.com

Here are some recommended products that we believe you will be
interested in. You can click the link to download.
Education In The Postcovid19 Era Opportunities And Challenges
Proceeding Of 2022 International Conference On Learning And Teaching
In The Digital World Saida Affouneh
https://ebookbell.com/product/education-in-the-postcovid19-era-
opportunities-and-challenges-proceeding-of-2022-international-
conference-on-learning-and-teaching-in-the-digital-world-saida-
affouneh-56793194
The Digital Era Of Learning Novel Educational Strategies And
Challenges For Teaching Students In The 21st Century Christopher S
Keator
https://ebookbell.com/product/the-digital-era-of-learning-novel-
educational-strategies-and-challenges-for-teaching-students-in-
the-21st-century-christopher-s-keator-33613646
Developing Writers Teaching And Learning In The Digital Age 1st
Edition Richard Andrews
https://ebookbell.com/product/developing-writers-teaching-and-
learning-in-the-digital-age-1st-edition-richard-andrews-2348228
Understanding The Digital Generation Teaching And Learning In The New
Digital Landscape 1st Edition Ian Jukes Ted Mccain Lee
Watanabecrockett
https://ebookbell.com/product/understanding-the-digital-generation-
teaching-and-learning-in-the-new-digital-landscape-1st-edition-ian-
jukes-ted-mccain-lee-watanabecrockett-51330812

Teaching And Learning English In The Digital Age 1st Edition Inez De
Floriohansen
https://ebookbell.com/product/teaching-and-learning-english-in-the-
digital-age-1st-edition-inez-de-floriohansen-43257086
Literacy In A Digital World Teaching And Learning In The Age Of
Information Tyner
https://ebookbell.com/product/literacy-in-a-digital-world-teaching-
and-learning-in-the-age-of-information-tyner-10812802
Learning And Teaching Mathematics In The Global Village Math Education
In The Digital Age 1st Edition Marcel Danesi Auth
https://ebookbell.com/product/learning-and-teaching-mathematics-in-
the-global-village-math-education-in-the-digital-age-1st-edition-
marcel-danesi-auth-10303734
Crayons And Ipads Learning And Teaching Of Young Children In The
Digital World 1st Edition Debra Harwood Debra Harwood
https://ebookbell.com/product/crayons-and-ipads-learning-and-teaching-
of-young-children-in-the-digital-world-1st-edition-debra-harwood-
debra-harwood-51609596
Teaching And Learning In A Digital World Proceedings Of The 20th
International Conference On Interactive Collaborative Learning Volume
2 1st Edition Michael E Auer
https://ebookbell.com/product/teaching-and-learning-in-a-digital-
world-proceedings-of-the-20th-international-conference-on-interactive-
collaborative-learning-volume-2-1st-edition-michael-e-auer-6989666

Teaching and
Learning
in the
Digital Era
Issues and Studies

This page intentionally left blank

NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TAIPEI • CHENNAI • TOKYO
World Scientific
Teaching and
Learning
in the
Digital Era
Issues and Studies
Editor
Jun Xu
King’s Own Institute, Australia

Published by
World Scientific Publishing Co. Pte. Ltd.
5 Toh Tuck Link, Singapore 596224
USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601
UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE
Library of Congress Cataloging-in-Publication Data
Names: Xu, Jun, 1970- editor.
Title: Teaching and learning in the digital era : issues and studies /
editor, Jun Xu, King's Own Institute, Australia.
Description: Singapore ; Hackensack, NJ : World scientific, 2024. |
Includes bibliographical references and index.
Identifiers: LCCN 2023053684 | ISBN 9789811285615 (hardcover) |
ISBN 9789811285622 (ebook) | ISBN 9789811285639 (ebook other)
Subjects: LCSH: Education--Effect of technological innovations on. |
Educational innovations. | Internet in education. | Web-based instruction. |
Computer-assisted instruction.
Classification: LCC LB1028.3 .T3747 2024 | DDC 371.33/4--dc23/eng/20231212
LC record available at https://lccn.loc.gov/2023053684
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library.
Copyright © 2024 by World Scientific Publishing Co. Pte. Ltd.
All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means,
electronic or mechanical, including photocopying, recording or any information storage and retrieval
system now known or to be invented, without written permission from the publisher.
For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance
Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy
is not required from the publisher.
For any available supplementary material, please visit
https://www.worldscientific.com/worldscibooks/10.1142/13658#t=suppl
Desk Editors: Balasubramanian Shanmugam/Steven Patt
Typeset by Stallion Press
Email: enquiries@stallionpress.com
Printed in Singapore

v
© 2024 World Scientific Publishing Company
https://doi.org/10.1142/9789811285622_fmatter
Preface
Digital technologies have brought disruptions to the education sector,
including new market opportunities, learners being able to assemble
their learning paths and learning content, an unlimited supply of content
and flexible delivery, new value propositions, large-scale platforms, and
reimagined systems. Meanwhile, some tough decisions education organi-
zations have to make are delivery model (e.g., online, hybrid, and face-to-
face teaching arrangements), revenue model, targeted student cohorts,
growing academic integrity issues arising from ChatGPT and other artifi-
cial intelligence applications, teacher shortages, the relevance of educa-
tion to the practice, return of capital and asset investment, student success,
the long-lasting impact of COVID-19, automation/digitization issues,
demand for better learning experience, security and privacy concerns, and
others. This book entitled Teaching and Learning in the Digital Era:
Issues and Studies, looks at current status and practices of teaching and
learning facilitated/enabled by digital technologies, reviews challenges/
issues associated with classroom teaching, online teaching and hybrid-
learning, and discusses success factors and future directions of teaching
and learning in the digital era. On top of high-level discussion of current
status, challenges and issues, emerging trends and technology, and future
directions of teaching and learning in the digital era, this book will also
provide a number of studies looking at different perspectives of using
digital technologies for teaching and learning. This book can be used as a
good reference book for education organizations (especially higher
education providers) to review their current approaches and practices of
technology-assisted/enabled teaching and learning and develop their

vi Teaching and Learning in the Digital Era: Issues and Studies
future plans for teaching and learning in the digital era. This book also can
serve as a good reference book for teaching staff or administrators at edu-
cation institutions, who are looking at updating their professional knowl-
edge & skills.
This book has 14 chapters and is divided into two parts. Part 1 focuses
on key issues associated with technology-assisted/enabled teaching and
learning and includes seven chapters (Chapters 1–7) and Part 2 presents
studies on digital technologies for teaching and learning and consists of
seven chapters (Chapters 8–14). Chapter 1, by Jun Xu, discusses the
impacts of digital technologies on society and the education sector,
reviews e-learning and hybrid learning, looks at learning and training in
the organization, highlights the recent development of artificial intelli-
gence (especially ChatGPT) and its impact on education, and comments
on the role of the government and teacher in the education in the digital
era. Chapter 2, by Sanjay Jha, Meena Jha, and Jun Xu, provides an over-
view of teaching and learning in the digital era, describes the definition,
types, and elements of teaching and learning in the digital era, explains the
opportunities, and challenges of teaching and learning, and points out
emerging patterns and provides insight into future trajectories how the use
of digital technologies while providing the required support to enhance
teaching and learning activities. Chapter 3, by Jun Xu, Graeme Salter, and
Yuxi Lan, presents the background of ChatGPT, discusses the benefits it
can provide to higher education, points out its limitations, concerns, and
issues, and looks at strategies and success factors for successful imple-
mentation of ChatGPT in the higher education organization. Chapter 4, by
Sweta Thakur, Farzaneh Mayabadi, Fariza Sabrina, and Shaleeza Sohail,
provides an overview of the emerging trends in online education and
elaborates on educational tools and how they can be used to enhance the
quality of education. Chapter 5, by Smitha Shivshankar, explores the sig-
nificance of assessment integrity and security and emphasizes their
imperative role in preserving the value of academic qualification and
genuine knowledge acquisition. It also sheds light on the strategies
and digital tools for addressing the challenges and discusses concerns and
issues associated with the digital tools. Chapter 6, by Shima Forughi,
delves into the realm of online assessments, shedding light on their advan-
tages, prerequisites, and the critical role of student perspectives. It empha-
sizes the pivotal influence of student attitudes, motivations, and emotions
on the outcomes of online assessments and provides a scope to the online
evaluation by looking into assessment types, consideration of academic

Preface vii
integrity, alternative ways of the learners’evaluation, and different aspects
of online examinations. Chapter 7, by Yuxi Lan, Nora Bhangi, and Jun
Xu, starts with a brief illustration of academic integrity and online assess-
ment arrangements, including exams. It then proceeds to explore the fac-
tors associated with academic misconduct, followed by a discussion on
various measures and digital tools that can be utilized to cope with aca-
demic integrity. This chapter also provides examples of current practices
for deterring academic misconduct at King’s Own Institute (KOI),
Australia.
Chapter 8, by Graeme Salter, examines the benefits and challenges of
creating engaging lessons in an online learning environment. Suggestions
for increasing student engagement online are provided. The importance of
gaining attention, demonstrating relevance, and providing state changes
during a lesson are highlighted. Chapter 9, by Mubashir Hussain, explores
the potential of “Game-Based Learning” (GBL) and gamification as an
alternative pedagogy to improve learner’s engagement, problem-solving
skills and learning skills. It provides insights on GBL and its application
in programming education, which enables instructors to make better deci-
sions in their teaching practices for programming courses and improve
students’ learning experience. Chapter 10, by Behnaz Rezaie Ortakand,
discusses predictive models for student engagement and retention issues
(e.g., identifying students at risk of attrition during the early phases) and
looks at using learning management system as data sources for such mod-
els. Chapter 11, by Mehrdad Razmjoo, discusses different machine learn-
ing algorithms and dives into the importance of student engagement, the
challenges involved, and the utilization of learning analytics in the educa-
tional process. The findings highlight the potential of machine learning in
identifying at-risk students and optimizing educational outcomes in online
learning environments. Chapter 12, by Farzaneh Mayabadi, Sweta
Thakur, Shaleeza Sohail, and Fariza Sabrina, sheds light on how big data
can be used in curriculum development to ensure that the skills and com-
petencies students learn at educational institutions align with those
required in the current and future job market. By exploring three case
studies in which big data has been utilized to revise and update curricula
in different fields, this chapter suggests that big data allows curriculum
designers to make data-driven decisions which leads to a higher rate of
employability and satisfaction among students. It also discusses the limi-
tations and challenges of using big data in education. Chapter 13, by Xin
Gu, Fareed Ud Din, and Robert M.X. Wu, compiles and examines 51 ICT

viii Teaching and Learning in the Digital Era: Issues and Studies
programs and 1,251 associated ICT courses from 11 universities in
China’s Shanxi province. This case study discovers that the most sought-
after ICT programs primarily center around Information and Computing
Science, as well as Computer Science and Technology. Mathematics and
Programming-related courses lay the foundation for ICT programs, while
Programming is the most frequently offered course in ICT programs at
Shanxi Universities. Chapter 14, by Gazi Farid Hossain, Deb Case, and
Caitlin Smith, looks at different technology-centric feedback collection
and analysis tools for collected survey data. It also suggests some factors
for making the students’ feedback and survey more successful.
We would like to express our sincere gratitude to the CEO and
President of King’s Own Institute, Professor Doug Hinchliffe for his great
support, and thank Dr Nicky Antonius and Dr Daniel O’Sheedy, for their
suggestions and assistance. Finally, we would like to thank World
Scientific for the opportunity to work on the book, and thank Editor
Steven Patt and his colleagues, at World Scientific, for overseeing the
publishing process of the book, for their great assistance, and for giving
us such a wonderful publishing experience.

ix
About the Editor
Jun Xu currently works with King’s Own Institute,
Sydney, Australia, as Vice President (Academic).
He earned his Bachelor of Engineering (1992) from
China University of Petroleum and received his
MBA (1999) and PhD (2003) degrees from Curtin
University, Australia. On top of his significant
experience of working with Australian and Chinese
governments and businesses across various indus-
tries, and his good experience of working with
major international oil & gas companies in
Singapore and China, he also possesses good experience of working with
e-business and digital technology start-ups in Australia and China, good
experience of higher education management, sound experience of prop-
erty management & development, and extensive teaching, research, and
doctoral research project supervision experience in the areas of informa-
tion management/knowledge management and e-business/digital enter-
prise.Hehaspublishedeightbooksone-business,knowledgemanagement,
information systems, digital enterprise, and teaching & learning, and he is
the Foundation Editor-in-Chief of the journal The International Technology
Management Review.

xi
Contents
Prefacev
About the Editorix
Part 1 Issues 1
Chapter 1 Overview of Teaching and Learning in the Digital Era 3
Jun Xu
Chapter 2 Teaching and Learning in the Digital Era:
Opportunities and Challenges 51
Sanjay Jha, Meena Jha, and Jun Xu
Chapter 3 ChatGPT and Higher Education 87
Jun Xu, Graeme Salter, and Yuxi Lan
Chapter 4 Online Education: Challenges, Tools, and
Emerging Trends 121
Sweta Thakur, Farzaneh Mayabadi, Fariza Sabrina,
and Shaleeza Sohail
Chapter 5 Assessment Integrity and Assessment Security
in the Digital Era 137
Smitha Shivshankar
Chapter 6 Designing Effective Online Assessment 165
Shima Forughi

xii Teaching and Learning in the Digital Era: Issues and Studies
Chapter 7 Academic Integrity and Online Teaching
and Learning 193
Yuxi Lan, Nora Bhangi, and Jun Xu
Part 2 Studies 213
Chapter 8 Creating Engaging Online Lessons 215
Graeme Salter
Chapter 9 Effectiveness of Game-Based Learning for
Programming Courses 235
Mubashir Hussain
Chapter 10 Monitor and Predict Student Engagement and
Retention Using Learning Management
System (LMS) 259
Behnaz Rezaie Ortakand
Chapter 11 Enhancing Student Engagement by Using
Machine Learning Algorithms 279
Mehrdad Razmjoo
Chapter 12 Application of Big Data in Curriculum
Development291
Farzaneh Mayabadi, Sweta Thakur,
Shaleeza Sohail, and Fariza Sabrina
Chapter 13 ICT Programs in China: A Case Study of Shanxi
Universities303
Xin Gu, Fareed Ud Din, and Robert M.X. Wu
Chapter 14 Technologies and Student Feedback Collection
and Analysis 327
Gazi Farid Hossain, Deb Case, and Caitlin Smith
Index343

3
https://doi.org/10.1142/9789811285622_0001
Chapter 1
Overview of Teaching and Learning
in the Digital Era
Jun Xu
King’s Own Institute, Australia
Abstract
This chapter discusses the impacts of digital technologies on society and
on the education sector, reviews e-learning and hybrid learning, looks at
learning and training in the organization, highlights the recent develop-
ment of artificial intelligence (especially ChatGPT) and its impact on
education, and comments on the role of the government and teacher in
the education in the digital era.
Keywords: Digital technology, E-learning, Online learning, Remote
learning, Hybrid learning, Future skills, Artificial intelligence (AI),
ChatGPT.
1. Impacts of Digital Technologies
Digital technologies such as Advanced connectivity (e.g., optical fiber,
LPWA network, Wi-Fi 6, 5G/6G Cellular, LEO satellite constellations),
Applied artificial intelligence (e.g., computer vision, natural-language pro-
cessing, deep reinforcement learning, knowledge graphs), Cloud Edge
Computing (e.g., device edge, remote edge, branch edge, enterprise edge,

4 Teaching and Learning in the Digital Era: Issues and Studies
telecom/MEC edge, cloud), Immersive reality technologies (e.g., spatial
computing, mixed reality, augmented reality, virtual reality, metaverse),
Industrializing machine learning (e.g., tooling optimizing ML workflows,
automated data management, structure and collaborative development,
controlled production release decisions, automated continuous integration
and continuous development (CI/CD) for test and validation of all
releases), Next generation software development (e.g., greater participa-
tion of citizen developers, automated configuration and monitoring,
AI-based pair programmers, fully automated CI/CD pipelines), Quantum
technologies (e.g., Quantum computing, Quantum communication,
Quantum sensing), Trust architecture and digital identity (e.g., zero-trust
architecture, digital identity, privacy engineering, and explainable artificial
intelligence), Web 3 (e.g., digital assets and tokens, smart contracts, block-
chain), Future of Bio-engineering (e.g., viral-vector gene therapy, mRNA
therapy, Cultivated meat, Drop-in, Bio-replacements, Biobetter), Future of
clean energy (e.g., Solar photovoltaics, On-and offshore wind generations,
nuclear vision, Electrolyzers), Future of mobility (e.g., Radar and cameras,
HD maps, Infotainment, Digital twin, Hybrid propulsion, nanomaterials,
green primary materials), Future of space technologies (e.g., Laser com-
munication, Edge computing AI, Nuclear propulsion, In-orbit servic-
ing), and Future of sustainable consumption (e.g., CCUS, Carbon removal,
Green construction, Natural capital ad nature, Alternative protein and sus-
tainable agriculture, Circular technologies), have great impacts on the way
we do things, the way we live, and the way we teach and learn (Chui et al.,
2022b: 5, 34, 41, 46, 74, 95, 111, 140, 153, 160, 180; the author’s own
knowledge). Among all the technology trends, it can be said that artificial
intelligence has the greatest potential, especially in terms of innovation
(Chui et al., 2022b, 3, 21).
Some of the most significant shifts for organizations, which could be
enabled by rapidly evolving digital technologies discussed in the last para-
graph are as follows (Bort, 2023; Simon et al., 2023; the author’s own
knowledge):
• More resilience and faster speed are required (e.g., through re-organization
for faster responses, empowering people, and encouraging and facili-
tating continuous learning in the organization).
• A hybrid work model balancing in-person and remote working is
needed (e.g., having a supporting structure, business processes, and
performance management mechanism).

Overview of Teaching and Learning in the Digital Era 5
• Artificial intelligence should be used for building better organizations
(e.g., improving business processes, creating talent pipelines, hiring
and developing AI-savvy leaders, fostering data-driving decision-
making, and being actively aware of the limitations, risks, and ethical
concerns associated with artificial intelligence).
• New rules of attracting, developing, and retaining talent need to be
developed (e.g., providing individuals with tailored value proposi-
tions by adopting a multidimensional approach including salary,
work-life balance, professional development, and purpose).
• Digital capabilities need to be built up in the organization (e.g., suf-
ficient training, resources, commitment to digitization initiatives,
development of required digital skills including digital analytics,
software development, customer insights, data science, product
development, and digital marketing).
• Organizations need to focus on finding and retaining high performers
who can be up to 800% more productive than average performers in
the same role (e.g., finding talent for critical roles, marching talent for
the highest-value roles, developing and looking after talent and keep-
ing talent in the organization).
• Leaders have to be capable and inspiring (e.g., having the ability to
lead and inspire others, having equipped themselves with advanced
digital intelligence and other digital skills, and having the skills to
influence others and win friends in the digital era).
• Organizations need to make meaningful progress on diversity, equity,
and inclusion (e.g., identifying and working on both internal opportu-
nities and external community issues, making diversity, equity, and
inclusion part of its strategic goals, investing in people’s knowledge
and skills of diversity, equity, and inclusion).
• Organizations have to be more serious about people’s mental health
and well-being issues (e.g., taking a more systematic approach,
addressing the root causes, and allocating dedicated resources).
• Better efficiency/productivity and effectiveness needs to be achieved
(e.g., deploying resources more effectively, achieving better and faster
decision-making, establishing appropriate delegation mechanism and
arrangements, actively monitoring technological advancements and
applying new technologies to improve its operations, enhance exter-
nal relations, and develop or sustain competitive advantages).
• Information security and privacy protection measures need to be con-
stantly reviewed and updated (e.g., given the rapid development of

digital technologies, widely available networks, and global adoption
of computing equipment (especially mobile devices), more and more
data can be collected, stored, and processed. Consequently, how to
protect personal information and prevent unethical uses of personal
information becomes a paramount issue.
2. Impacts of Digital Technologies on Education
Digital technologies have brought disruptions to the education sector
(Moore Martinotti, 2016; the author’s own knowledge), such as:
• New market opportunities (e.g., market opportunities arising
from new digital capabilities, remote learning/e-learning opportuni-
ties, hybrid/blended learning opportunities, personalized learning
opportunities).
• Allowing learners to assemble their own learning pathways and con-
tent rather than relying on traditionally bundled degrees (e.g., micro-
credentials and badges).
• Unlimited supply of content and flexible delivery (e.g., open educa-
tional resources, crowdsourcing, virtual delivery, blended delivery,
co-working spaces/innovation labs).
• New value propositions (e.g., student-centered approach and tailored
learning options, competency-based learning, and outcome-based
funding model, global learning platforms, global digital degrees, and
global access to learning material facilitated by digital ID).
• Large-scale platforms (e.g., online education platforms integrating
learning resources from various sources and having Amazon-type
learning portals with Google-type search function, and ChatGPT-type
assistance).
• Reimagined systems (e.g., mobile/online courses (such as MOOCs)
with a mix of curriculum and project-based learning, experiential/
immersive learning with augmented, reality, virtual reality, and mixed
reality, classes delivered by human teachers and virtual assistants).
Some particular changes and challenges that education organizations
(particularly higher education providers) are facing include (Barber
Mourshed, 2007; Boggs et al., 2021; Brassey et al., 2019; Bryant et al.,
2020, 2022; Chen et al., 2019; Diaz-Infante et al., 2022; Dorn et al., 2019;

Ferrari and Phan, 2018; Fuller Kirkland, 2018; Gallagher, 2023; Hall
et al., 2022, 2023; Hancock et al., 2022; Heitz et al., 2020; Khan
Kirland, 2019; LinkedIn Learning, 2023; Microsoft, 2023; Pandit et al.,
2012; the author’s own knowledge; UNESCO, 2023b; University of
Queensland, 2023; Welch, 2023):
• Deciding learning/delivery models: The hybrid/blended delivery
model, which combines face-to-face and online delivery approaches,
arguably would be the suitable model for many education providers.
• Financial viability issues: Education providers need to look for mul-
tiple avenues for generating revenue (e.g., new courses, extension of
existing courses (e.g., adding in new specializations into existing
courses), double degrees, micro-credentials, online courses, short
vocational courses, adult learning, new student markets and cohorts,
better student retention strategies, more targeted outreach, improving
efficiencies of current investments (e.g., via innovative teaching
delivery), improving internal efficiency via streamlining business
processes and digital transformation).
• Changing student demographics and unstable student enrolment:
More targeted approach and more individualized value propositions
as well as diversification in markets and products should be
implemented.
• Increasing academic integrity issues arising from ChatGPT and other
artificial intelligence applications and systems: AI applications such
as ChatGPT have made academic cheating easier and detection of
academic cheating more challenging. Such challenges have to be dealt
with combined forces of humans and technology.
• Teacher shortages around the world: The government has to put more
investment and resources into training and developing teachers and
provide them with good benefits. More social recognition is needed
for those human’s social engineers. Compared to medical doctors,
who are viewed as human’s body engineers, the significance of teach-
ers should be more and better publicized by the government and
society. On a related note, while there are various issues associated
with AI and other digital technologies, we should explore ways that
they can assist teachers in teaching students (e.g., facilitating self-
learning, personalized learning).
• Relevance of education (especially higher education) to the real
world: More practice-oriented courses, more practice-based projects,

more industry-based projects, more work-integrated learning projects,
and internship programs should be adopted. And more engagement
with the industry (e.g., co-designing the courses, internship with
industrial partners) should be pursued by education providers as well.
• Fast-growing operating costs: Operational efficiencies in areas such
as faculty staff/teachers, academic support services, student support
services, facilities, and administrative services should be looked at
closely, and ways to streamline processes and speed up the decision-
making (e.g., adopting data-driven decision-making approach, learn-
ing analytics) as well as strategies for more effectively allocating
organizational resources (e.g., adopting the value-chain model for
value creation in each internal and external activity) should be
explored.
• Pressure on securing research funding: In many countries, the govern-
ment is reducing research funding for education providers (especially
universities). Education providers need to be innovative in securing
research funding (e.g., working more closely with businesses,
co-developing and funding research projects with the industry,
encouraging entrepreneurship among faculty members, seeking dona-
tions, establishing closer relations with alumni, enhancing internal
capabilities of commercializing research results).
• Pressure on return of capital and asset investment: Education organi-
zations may need to look at the “light company model” (or “the agile
company model”) if possible (but you need to have sufficient
resources for sustainability and future growth, and in different growth
stages of the firm, the resource requirements will differ), examine
underutilized assets and facilities as well as underperforming courses,
and digitize business processes and activities as many as possible.
• Pressure on student success: Education organizations need to focus on
getting the right people into suitable teaching positions, developing
them into effective teachers, working on a system to deliver the best
possible teaching to every student, and providing excellent student
support.
• The long-lasting impact of COVID-19: The remote learning (also
e-leaning, online learning, digital learning) adopted during COVID-
19 period will stay even after COVID-19. Education providers need
to strategically integrate remote learning into the teaching and learn-
ing plan and make it more individual/personalized and adaptive.

• Dealing with automation/digitization issues: Teachers need to take on
reskilling and adopt the learning philosophy of lifelong learning, and
they should use technologies to help them with some routine tasks
such as quiz grading and attendance marking so they can focus on
more value-added tasks such as coaching and one-to-one tutoring.
Education providers should think carefully about the possible losses
of social connection and human interaction and caring in the process
of automation/digitization.
• Getting the online learning right: The online education market (in
terms of rapidly increasing student number, influx of investing and
rising standard of online education quality and assurance) is growing
dramatically. Online education providers need to design courses
meeting students’ needs, integrate degree and no-degree offers, offer
students with courses and skills aligning with students’ career plan-
ning, provide more personalized learning experiences, establish
closer partnership with employers, adopting a student-centered
approach, engaging students through multiple channels and touch
points, investing heavily in marketing and management, and choos-
ing a suitable operation model (e.g., looking at options of having an
online program manager for online programs (both in-house and
outsourced programs), working with an independent contractor,
partnering with large existing providers, in-housing operations with
separate entity), and having clear accountability for online learning
organization/entity.
• Demand for better learning experiences: Education providers need to
offer good learning experience (e.g., seamless journey, engaging
teaching approach, caring network/support, seamless connections,
captivating experiences, real-world skills, and strong community),
and learning experiences should be supported by factors such as
access to high-quality and relevant content, well-trained teachers,
personalized approach, good and frequent evaluation and feedback
and good data analytics and benchmarking.
• Exploring additional education market: Education organizations need
to understand the reasons for additional education and take appropri-
ate actions. Some reasons that people pursue additional education
include: career setbacks, important life events, community building,
influences from family members or friends, having problems requir-
ing more learning to resolve, seeing promotion and advertisement, not

engaging at work, overlooked for a promotion opportunity, and New
Year’s resolution.
• Focusing on access and equity: Given the economic and digital divide
for different regions and countries, education providers have to work
on providing computing equipment and educational resources to the
students who need them.
• Competence-based learning vs. traditional classroom learning:
Opportunities for both mastering competence (not time-based) and
learning academic knowledge (normally within fixed timeframe)
should be provided to students/learners, and it could be done via
collaborating with independent learning providers (such as Khan
Academy, Udemy). On a related note, the significance of lifelong
learning should be highlighted again here since competence-based
learning is closely related to lifelong learning (e.g., continually update
your competence and skills after you have got formal education from
colleges and universities).
• Different skills needed: Skills-focused training for higher education
students can be greatly facilitated by digital technologies. On the
other hand, curriculum-focused teaching is more for younger students
that needs intensive human interaction to progress.
• Important skills thought by teachers vs. Important skills perceived by
students: While teachers believe skills such as literacy, critical think-
ing, social awareness, communication, self-awareness and collabora-
tion are important, students think skills important to them are such
skills as digital skills, creativity, relationship skills, intercultural
understanding, ethical understanding, self-management. Another part
of this discussion is Teacher-led learning vs. Student-led learning.
• The impacts of digital technologies on education: Education organiza-
tions need to be well prepared for the impacts (both positive and nega-
tive impacts) of digital technologies (especially artificial intelligence)
on the education systems. Stanford University’s AIRE (Artificial
Intelligence, Robotics and Education) is a good example of such
initiative (refer to https://aire.stanford.edu/). It is dedicated to “find
the best approach to redesigning our education systems to accommo-
date the coming area of robotics and artificial intelligence” by bring-
ing together knowledge and experiences from various areas such as
Design thinking, Robotics, Artificial Intelligence, Neurology and
Education.

• Competition for talent: Education providers need to make their
human resources (HR) function stronger, more agile and smarter (e.g.,
aligning HR strategy with business strategy, taking a more agile and
collaborative HR approach, continually investing in HR staff devel-
opment and HR technology, working with universities on recruiting
and developing talent (such as via work-integrated learning projects,
internship programs)). HR department could be called talent depart-
ment and the head of the HR could be called Chief Talent Officer.
• The external environment issues: In many countries, lack of teachers
and administrators and lack of funding are serious issues. On top of
the local government’s efforts, international communities have to lend
their helping hands. Technologies and technology firms could play
important roles (e.g., supporting e-learning, m-learning, personalized
learning).
• Security and privacy issues: Education providers need to continuously
invest in security and privacy measures to ensure the continuity of
teaching and learning and provide a safe learning environment.
3. E-Learning and Hybrid Learning
3.1. E-Learning
E-learning (also called Remote Learning or Online Learning) has been
widely adopted by both educational and non-educational organizations.
For example, it is reported that more than 25% of college students have
taken at least one (1) online course, and about 71% of academic leaders
believe that online learning could achieve same or similar learning out-
comes as the traditional approach (Chen et al., 2019; Xu Gao, 2021:
110). E-learning could be provided at the traditional schools, colleges, and
universities, workplaces (e.g., via corporate universities and training cent-
ers, doing on the job-tasks), communities and training and development
agencies, online learning portals/platforms (e.g., Coursera, Udacity,
Udemy, edX), and it also self-paced (McKinsey, 2017; the author’s own
knowledge; Xu Gao, 2021: 110–111).
E-learning offers many benefits (such as convenience, flexibility, self-
paced learning, individualized/personalized learning, 24/7 availability,
access to much more learning material, more course and unit options,
cost-efficiency, capacity of teaching large number of students without the

constraint of space limitation, being cheaper and easier to update and store
content, access to global expertise, democratization of knowledge, contri-
bution to education equality via providing people in the less developed
regions with access to global teaching and learning resources), but it also
has a number of challenges and drawbacks (Xu 2014, p. 99).
3.1.1. Barriers/Challenges/Issues of E-Learning
Some barriers/challenges/issues of E-learning include (Brasca et al.,
2022; Child et al., 2022; Cusumano et al., 2013; Gallagher, 2023; Hall
et al., 2023; Keppell, 2023; Maiolo, 2014; McKinsey, 2017; the author’s
own knowledge; Turban et al., 2012: 243; Xu, 2014: 100–101; Xu Gao,
2021: 110–112):
• Security and privacy issues (e.g., learners’ online safety and privacy
issues, security of online testing and assessment, difficulties in ensur-
ing who actually have completed the online tasks).
• Online content, assessment and curriculum development (e.g., digital
teaching and learning has different pedagogical perspectives and issues,
simply digitizing student materials and using the same traditional teach-
ing approach will not work. In addition, there are challenges associated
with digital assessments (including online essays, online quizzes,
online group work, forums, online presentations, online exam, online
projects, online reflective journal, online self-assessment, e-portfolio,
online peer assessment, online tutorials) in the perspectives of assess-
ment validity, reliability, fairness, variability and efficiency).
• Different teaching and support expertise required (e.g., professional
development of teaching and admin and other support staff for online
teaching and learning is required).
• Lack of common standards for e-learning platforms (e.g., difficulties
in integrating different learning platforms).
• Failing to engage with students (e.g., not providing timely and ade-
quate feedback, not providing enough opportunities for team/group
work).
• Mobile learning challenges (e.g., limitations arising from the mobile
devices and networks).
• Lack of required infrastructure and access equality issues (e.g.,
required Internet and Wi-Fi access and computing equipment in some
countries and regions are not available).

• Lack of internal capabilities to deploy E-learning (e.g., there is a lack
of required strategy, leadership, capacity, skills and resources for
learning initiatives).
• Perceived difficulties in developing higher-level cognitive skills (e.g.,
it could be really challenging to develop students’ cognitive skills by
watching online sessions, doing online activities with human connec-
tion and social interaction).
• Issues of intellectual property protection (e.g., difficulties in control-
ling the transmission of copyrighted works downloaded from the
e-learning sites/platforms).
• Believing e-learning has little or no impact on learning and online
programs are not motivating enough.
• Getting more distracted when studying online and Lacking the disci-
pline to do online programs, which have significant impact on learn-
ing experiences and learning outcomes.
• Believing that online programs don’t offer the same extracurricular
options and online programs don’t offer the opportunity to interact
with other students.
• Lack of face-to-face in-person social interaction and campus life.
• Under-estimating the cost of e-learning, especially when the student
number is not sufficient to justify the capital investment and high-
fixed cost associated with e-learning.
• Over-estimating the achievement of e-learning: e-learning has its
limitation and may only be suitable for certain student cohorts (e.g.,
students who have full-time employment or live far away from the
campus), especially in the early stage.
• Overlooking the difficulties of self-study: some people are not capa-
ble of doing or are not willing to do self-study.
• Treating content/study material as commodity could lead to a lack of
attention to quality and learning experience.
• Having too much emphasis on technology or not fully utilizing avail-
able tools: A balanced approach should be adopted.
• Assuming learned knowledge will be applied: Learned knowledge
needs to be applied in real-life actions or work-integrated projects,
which could be difficult in the digital learning environment.
• Confusing with adoption and diffusion issues: even people have
adopted e-learning systems, they may not use them or use them prop-
erly. The assumption of once e-learning system is developed, people
will use it, is not true.

3.1.2. Success Factors of E-Learning
Some success factors of E-learning include (Brasca et al., 2022; Child
et al., 2021; Child et al., 2023; Cusumano et al., 2014; Epignosis LCC,
2014; Gilbert et al., 2018; Hall et al., 2023; Henry et al., 2014; Pandit
et al., 2012; the author’s own knowledge; Xu, 2014: 99–102):
• Designing online journey carefully.
• Having clear understanding of the needs of the students and pros and
cons of the current programs being offered.
• Deciding a clear vision/strategic direction for your online learning.
• Planning your transformation journey properly (e.g., online program
structure, structured course maps, online assessment and integrity
issues, online course design).
• Addressing key teaching and learning activities (e.g., content, deliv-
ery, evaluation and assessment, engagement and learning, and learn-
ing outcomes).
• Providing students with seamless journey via developing clear educa-
tion road map and offering seamless connections and access to stu-
dent portals and learning resources.
• Allocating sufficient resources and making necessary adjustments to
organizational culture and structure to facilitate the implementation of
e-learning strategy.
• Providing sufficient training to teachers (including online teaching
pedagogy, effective use of digital technologies for teaching, develop-
ing high-quality digital content, and hybrid/blended teaching and
learning approach).
• Keeping on monitoring students’ e-learning experience and making
necessary adjustments.
• Having clear expectations and communicate them effectively to stu-
dents in every possible opportunity.
• Developing quality content and maintaining its currency.
• Adopting technology platforms, which have the interoperability and
integration flexibility, and providing students with easy digital experi-
ences via multiple channels and touch points (e.g., through offering
omnichannel experience).
• Ensuring learning platforms are both useful and user friendly (e.g.,
even a e-learning system has many functions, if it is difficult to use,
students will not use it).

• Ensuring engaging teaching via providing range of learning formats
(e.g., asynchronous classes, asynchronous classes, peer-to-peer learn-
ing), captivating delivery and experiences (e.g., updated content, rele-
vant faculty, content in various formats), opportunities of applying
learned knowledge to real-world cases/situations, and tailored learning.
• Ensuring that e-learning is designed to help to personalize learning,
provide access to resources/instructors, improve ability to learn, make
learning more efficient, and make learning more entertaining.
• Putting caring network and strong community (student led or teacher-
led) in place to assist students timely and adequately (including aca-
demic support, non-academic support, coaching, career support and
IT support).
• Providing reliable and responsive support to students (including
actively participating online discussions with students and providing
feedback to their inquiries in a timely manner).
• Listening to students and seeking their input for improvement (e.g.,
via direct observations, student surveys).
• Using data analytics for better understanding thus more informed
decision making and continuous improvement.
• Providing opportunities and channels for face-to-face interactions
(e.g., contact offices, meeting places, service hubs).
• Making both explicit knowledge (e.g., study material and digital con-
tent) and tacit knowledge (e.g., professors’ expertise) available to
students.
• On top of offering online courses to existing markets, using online
channels to tap into new segments and domestic and international
markets (e.g., domestic and international students) are not able to
attend on-campus studies) should be explored (e.g., such approach
would improve the operation of online programs an cause less disrup-
tions to existing operations, especially in the early stage).
• Establishing distinctive unit/entity for managing online programs
only when necessary.
• Taking into consideration other relevant factors associated with online
programs (including scale of growth, customization level, required
talent, speed to market, legal constraints and budget and financial
constraints).
According to UNESCO (2020b), in certain countries, there are signifi-
cant issues/challenges in establishing remote learning/e-learning systems:

• Student perspectives: For example, in Sub-Saharan Africa, only
11% households have computers and only 18% of households have
Internet connections.
• Teacher and Curriculum perspectives: For example, in Sub-Saharan
Africa, there is a shortage of 17 million qualified primary and second-
ary school teachers.
• Technology solution perspectives: For example, the total size of
e-learning in Sub-Saharan Africa is smaller than 2% of the global
total.
• School system perspectives: most educations in low and middle-
income countries are underfunded.
UNESCO (2020b) further points out that remote learning/e-learning
strategy should include elements such as assignment and information
(e.g., how to communicate new assignment and information), methods
for teaching (e.g., how to teach remotely), methods for student practices
(e.g., how students can practice remotely), and formative feedback and
coaching (e.g., how teachers can provide formative feedback and coach
remotely). In addition, in countries and regions with poor educational
resources, very often there are challenges in securing some common
tools and resources for learning, including paper textbook, physical
notes, TV/radio program, recorded videos, adaptive software programs,
live video-conference, online platforms, email messages and text mes-
sages, and discussion boards.
3.2. Hybrid Learning
Hybrid Learning (also called Blended Learning) includes combinations of
online and offline learning, synchronous and asynchronous learning,
classroom learning and real-life learning, and in-person learning and
online learning (or e-learning or remote learning), student-led learning
and teacher-led learning, and self-paced learning and instructed learning
(Keppell, 2023; the author’s own knowledge). The combined teaching and
learning approach of the hybrid delivery is very critical to the knowledge-
intensive business (e.g., education). The creation and sharing of our tacit
knowledge (e.g., the teacher’s experience and expertise) and the emo-
tional/caring side of the teaching cannot be done by the technology itself
even though it may provide some facilitating roles (e.g., connecting

people who need knowledge (such as students) with people have the
required knowledge and experience (such as teachers). Hybrid learning
approach is a balanced approach, which could deliver benefits of both
traditional classroom teaching and the online education. In addition, the
results of a federal study in the U.S. suggested blended learning models
can producing learning outcomes that are equal to or better than face-to-
face or pure online learning (Henry et al., 2014; Xu, 2014: 102).
Hybrid learning could also address the concerns in both remote learn-
ing (e.g., difficulties in achieving the same learning outcomes as in person
learning, digital divide issues) and in-person learning (e.g., staffing issues,
the physical premise requirements), and it can follow a three-stage process:
assessing the needs and capabilities and current practices (including guid-
ing principles for learning, students’ needs for remote and in-person learn-
ing, accessibility and effectiveness of current remote learning outcomes,
teacher’s ability, availability of physical space, availability and flexibility
of support), determining suitable learning model (e.g., looking at such
perspectives as distributing capacity evenly or prioritizing certain seg-
ments, assessing online learning and in-person learning, and following on
support to vulnerable groups in various options and student number projec-
tions and required learning resources), and operationalizing hybrid learn-
ing method (e.g., reviewing subjects for remote learning and in-person
learning, learning activities for remote learning and in-person learning,
optimal distribution of hybrid model, teacher allocation model, capability
model) (UNESCO, 2020).
Hybrid learning could bring many benefits to educational organiza-
tions, especially higher education providers (such as providing students
with more choices and more flexibility in dealing with their busy schedule
of study, part-time work and personal activities; allowing the teachers to
deliver live classes to and interact with students at different locations;
improving teaching efficiency and productivity, bettering teaching and
learning resources and environments, applying latest technology to teach-
ing and learning, updating teachers’ knowledge and skills of using tech-
nology for teaching, and enhancing students’ learning interest and class
participation) (Hall et al., 2023; the author’s own knowledge).
Hybrid classroom has become popular in recent years, it typically
includes tracking cameras, wireless microphones, interactive white
boards, and smart screens. Figures 1 and 2 show the hybrid classroom

set-up at King’s Own Institute, Australia, and the hybrid classroom equip-
ment include: BenQ Interactive Whiteboards, AVER DL30 Tracking

Figure 1: KOI’s Hybrid Classroom 1.
Source: King’s Own Institute 2023.
Figure 2: KOI’s Hybrid Classroom 2.
Source: King’s Own Institute 2023.

Cameras, Smart Screens, Computers and Screens for the Teacher as well
as overhead projector and pull down screen. Meanwhile students can join
the activities on the BENQ Interactive Whiteboards from their smart-
phones and mobile devices.
What are the (negative) impacts of digital technologies on humanity
and society? Should we care about such impacts (especially when focus-
ing on such impacts could mean sacrificing certain benefits of digital
technologies)? It can be said that people have different answers on those
questions. One of the impacts is the concern of that we become less
human (for example, We are more and more recognized by user names,
passwords, mobile phone numbers and represented only by a series of the
number of 0 and the number of 1?; Have we lost our ability of thinking,
writing and research by over-relying on search engines, spell check and
grammar software, and Wikipedia-type applications?; How about the ini-
tiatives of hybrid human and technology being pursued? (such as
Neuralink’s brain implants and mind reading technology researched by
Facebook, MIT, and University of California) (Xu 2019: 19; the authors’
own knowledge).
Cyberbullying, abusive language, and predation targeting vulnerable
people (especially children), online pornography, online cigarettes and
drugs sales, and online gambling are having dramatic damages on families
and society (Laudon Traver, 2018: 604). While it is critical for govern-
ment to establish appropriate regulations (e.g., The Children’s Internet
Protection Act and Federal State laws on regulating online cigarettes
and drug sales and online gaming) and it is necessary to use technologies
(e.g., filtering software) to deal with such issues, it is essential all the
stakeholders (e.g., government agencies (including police), parents, chil-
dren, teachers and schools, communities, technology firms, businesses) to
work together to win the battle (Laudon Traver, 2018: 617; the authors’
own knowledge).
Automation, AI and Robotics will have huge impact on employment
and job safety in the future (Heltzel, 2017; Manyika, 2017; the authors’
own knowledge). It is predicted nearly half of all jobs in the U.S. could be
automated by 2050 (Bhalla et al., 2017: 4) even though discussions such as
what can be automated, costs and benefits of replacing human, and how
new jobs will be created in the process of automation, are still going on
(Rotman, 2018). It is fair to say that automation will not only result in job
losses, but also lead to creating new jobs (e.g., via increased spending and
investment on technology development and deployment) as well as

changing existing jobs (e.g., changing occupations, requiring different
skills, changing workplace) (Manyika et al., 2018). However, people are
really worried about their job security and next generation’s employment
prospects. On top of the employment concerns, digital technologies (espe-
cially AI and robotics) could impose us to such threats as: Privacy and
surveillance concerns; Manipulation of behavior (e.g., algorithms devel-
oped by collected data could be used to influence certain individuals or
groups into believing and doing things based on analyzing the collected
data); Bias and opacity concerns (e.g., predictive analytics without due pro-
cess, accountability, community engagement, and auditing); Uncertainties
and difficulties in ensuring effective and accurate communication and
interaction between human and robots, autonomous systems concerns (e.g.,
Who is in control? Who is responsible?); Robotizing humanity and thus
destroying human’s heart and soul, compassion, creativity, empathy, and
stewardship; Responsibilities and rights of robots; and Technological sin-
gularity and superintelligence concerns (e.g., AI systems have higher level
of intelligence than human, can develop AI systems themselves, and
become uncontrollable) (Müller, 2020; Schwab, 2016).
So what should we do? Simply complaining and panicking won’t be
helpful?! We need to have a thorough understanding of the issues and
prepare for the future (Brynjofsson McAfee, 2012; Dickson, 2017,
2018; Frank et al., 2017; Goodwin, 2018; Heywood et al., 2014: 7;
Manyika et al., 2018; Ted, 2018; Trieu, 2016; Xu, 2019: 26; Xu, 2019: 27;
the authors’ own knowledge):
• Even though machines are getting better, more powerful and smarter,
they are still not good at many things requiring intuition, judgment,
experience, and insight (e.g., computers can’t decide what analyses to
carry out and how to interpret the results), can’t do negotiation and
group dynamics, can’t produce good writing, can’t frame problems
and solve open-ended problems, and can’t do persuasion and human
interaction and nurturing).
• While repetitive (e.g., tele-sales, customer support), routine (e.g.,
truck driver, security guards), or optimizing (radiologist and reporter)
types of job will be gradually replaced by machines, some jobs that
are complex and creative and need human compassion, intuition, and
judgment should be still in demand in the future (e.g., social workers,
scientists, artists, economists, professors, senior executives).

• Even though some jobs (e.g., very labor-intensive and dangerous jobs,
jobs requiring very low human compassion, intuition and judgment)
will be replaced by machines, human can coexist with AI and other
advanced technologies, and can work together (e.g., AI can be a use-
ful tool for human, AI can assist human to become more creative, and
AI can partner with human).
• While it is essential to acknowledge and accept that the robots are
here already not coming, it is also true that people still need to have
face-to-face contact and social (physical) interactions, which can’t be
digitized or automated or done by robots.
• Human has gone through three industry revolutions (e.g., steam tur-
bine representing first industry revolution, electricity symbolizing
second industry revolution, and personal computer reflecting third
industry revolution), each time human faced the same issues of the
impacts of the new machines on human conditions and opportunities,
and each time human survived and found new uses for labor. We are
now in the period of 4th industry revolution (arguably typified by 5G
and AI), based our experiences of past three industry revolutions, we
should be confident that we (human) can grow together with new
technologies (e.g., AI) and work with them to create better tomorrow
for humankind.
• Maybe AI (artificial intelligence) should be called Augmented
Intelligence (term coined by former IBM CEO Ginni Romett), which
views technological intelligence is to complement human intelligence
not to replace human intelligence, focuses on the partnership between
technology and human, and looks at using technology to make human
faster and smarter at what they do and building better machines to
enable human to achieve higher performance.
• Ethics and social impacts should be educated and scrutinized closely
all the time and should be on the mind of all the stakeholders and
should be part of the culture (i.e., the way we do things).
• We should pay more attention to responsible computing, including
developing and deploying systems, applications and networks respon-
sibly, dealing with data responsibly, ensuring ethical and safe use of
AI and other computing technologies, sharing best practices of
responsibly using and deploying AI and other computing technolo-
gies, and keeping on innovating the way of responsibly using and
deploying AI and other computing technologies.

• While certain advanced technologies (such as Neuralink’s brain
implants) could have medical benefits, the associated ethical concerns
should be examined closely at the same time. Can we argue that the
natural human body and the natural systems in the human body
should not be interfered and changed by external stuff (such as com-
puter chips)? Having said that, we have already put such things as
Artificial Heart and Artificial Ear into our body to replace or enhance
human organs.
4. Learning/Training in the Organization
In 2016 organizations spent $359 billion on training, meanwhile the
majority of training is not effective and have flaws in purpose, timing and
content of training (Glaveski, 2019). It is also reported that:
• 90% of corporations adopt e-learning (Edgepoint learning cited in
RWS, 2022).
• 67% of organizations embark on mobile learning (eLearning industry
cited in RWS, 2022).
• 72% of organizations suggest that e-learning give them competitive
advantages (Certifyme.net cited in RWS, 2022).
• The corporate e-learning is set to reach $50 billion by 2026
(TalentLMS, 2023).
• E-learning could increase retention rates by up to 60% and link to
higher revenue and faster growth for 42% US organizations
(TalentLMS, 2023).
According to a survey done by McKinsey (reported in Glaveski,
2019): 75% of surveyed managers are not happy with the training in the
organization, 70% of employees report that they don’t have the required
skills for the job, 88% of employees are not able to apply their new skills
they gained via training in the organization, and 75% of survey respond-
ents believe that the training in the organization had impact on their per-
formance. Meanwhile a study conducted in 2021 by LinkedIn (reported in
Brainier, 2023) unveiled that 62% of participating CEOs viewed upskill-
ing as a priority for the organization and investing in upskilling and
reskilling the global workforce will grow GPD by 30% by 2030.

Accenture (cited in Das et al., 2023) suggests that 94% of workers would
stay with their firms longer if their firms invested in their career develop-
ment. Learning and Training could be provided internally by the organiza-
tion itself, alternatively organizations could use external training providers,
such as: Afya Educational, Eruditue, Unacademy, Udemy, BYJUS,
BetterUp, MasterClass, 360Learing, Go1, upGrad, Degreed, Guild and
CoachHub (Sanghvi Westhoff, 2022).
Some suggestions for effectively learning/training in the organization
include (360Learning, 2023; Brainier, 2023; Das et al., 2023; Glaveski,
2019; Wentworth, 2023):
• Aligning learning with learner’s performance and business
objectives.
• Making learning relevant to people’s needs and embarking on a
learner-centred approach.
• Adopting lean learning in the organization (e.g., focusing on core
knowledge first) and offering short-bite sized learning and micro
courses.
• Applying learning to real-world issues quickly.
• Improving training based on the feedback.
• Repeating the cycle of learning, applying and receiving feedback and
improving.
• Encouraging peer-learning/collaborative learning.
• Establishing mentoring relationships.
• Emphasizing and promoting internal experts to keep them and their
knowledge.
• Empowering people to learn.
• Offering ongoing support.
• Creating conducive learning environments (e.g., organizing lunch
events for knowledge sharing and encouraging internal
collaboration).
• Encouraging and facilitating both formal and informal learning.
• Concentration on learning outcomes (rather than credits and number
of people completing the training.
• Setting realistic training expectations.
• Using learning analytics to analyze people’s learning patterns and
assess the impact of training.

Table 1: Future trends and opportunities in the teaching and learning areas.
Business
Process
Trends and
Opportunities
Technologies for Addressing the
Identified Trends/Opportunities
Teaching and
Learning
Activities
· Enhancing
Classroom
Learning
Experiences
· Tools for Classroom interactions (e.g., polls,
chats, breakout rooms) and systems for Classroom
exercises (e.g., learning games, badges, rewards)
could enhance classroom learning experiences.
· Personalized
Learning
· Applications/systems such as Applications/
systems for assessment and factor checking (e.g.,
ChatGPT, Grammarly, Microsoft Word Spelling
and Grammar Checker, Turnitin) could support
personalized learning.
· Intelligent Tutoring Systems that provide
immediate and customized instruction feedback to
learners according to their characteristics and
needs (typically based on the assessment based on
their responses to assigned tasks and questions),
very often without requiring intervention from a
human teacher (e.g., Algebra Tutor, Cognitive
Tutor, SQL Tutor, ITSS, Dragon 2, PCAR, Mouse
Work, Living Letters, SARA, Nanotutors, DME,
ALEKS, ASSISTments, CTAT, HINTS,
SKOPE-IT, My Science Tutor, GraphicGame
Rime) could also assist personalized learning.
5. Future Skills, Future Trends, and Opportunities
5.1. Opportunities in the Teaching and Learning Areas
For educational organizations (e.g., schools, colleges and universities),
opportunities could be found in teaching and learning areas (their main
activities) and supporting areas of teaching and learning. Table 1 presents
opportunities in the teaching and learning areas and the roles of digital
technologies in addressing identified opportunities.
5.2.
Opportunities in the Supporting Areas of Teaching
and Learning
Table 2 shows opportunities in the supporting areas of teaching and learn-
ing and the roles of digital technologies.

Business
Process
Trends and
Opportunities
· Adaptive
Learning
· Adaptive Learning Systems, which automatically
adapts teaching process (i.e., delivering
customized resources and learning activities) and
can arguably be viewed as a type of Intelligent
Tutoring Systems, include applications such as
ELAN, Reading Plus, Dutch Education System,
FB-TS, Adaptive Mobile Learning Systems,
Personalized Adaptive Learning Dashboard, AL,
Adaptemy, EdApp, Cogbooks, Knewton,
Realizeit, Pearson Interactive Labs, Adaptive
Learning, Design Digitally, Impelsys Scholar
ALS.
· Self-Learning · Virtual Classroom (e.g., digital avatars, engaging
interfaces, virtual reality, augmented reality and
mixed reality tools, gamified learning systems),
One-to-one online tutorial between the teacher
and the student, and Learning management
systems serving as a gateway or central hub for
learning (e.g., Blackboard, Canvas, Moodle),
could assist self-paced learning.
· Self-paced technology-assisted learning (either
synchronous or asynchronous) (e.g., attending
online learning activities and reviewed online
learning materials (including online content,
recordings, videos, discussion forums, learning
communities, collaborative platforms and classes)
and Technologies for self-evaluation (e.g.,
Turnitin, Speedgrader, GradeScope) could
facilitate self-paced learning as well.
• Active Learning • Active learning could be enabled by tools such as
In-class Polling Systems, Google Slide Decks,
Zoom Breakout Rooms, Classroom Response
Systems; Group Decision Support Applications.
• Peer Learning/
Collaborative
Learning
• Peer learning/Collaborative learning could be
facilitated by technologies such as social media
platforms, video conferencing tools, and virtual
collaboration and learning management systems.
Table 1: (Continued)
(Continued)

Business
Process
Trends and
Opportunities
• Collaborative learning could be supported by
technologies such as Wikis, Smart Panels,
Concept Mapping, Real-time Collaborative
Editing tools (such as Google Doc, Google
Shared Drive), Virtual Whiteboards, Online
meeting/conferencing tools (such as Zoom,
Microsoft Team, Google Meet), Instant
Messaging, Project Management Tools,
Discussion Boards/Forums, Blogs, Emails,
Social Media, Online Communities.
· Visualized
Learning
· Information visualization tools (e.g., Geographic
information systems, Gapminder.com, JMOL,
Google Earth) could help student understand and
present complex data.
· Game-based
Learning/
Gamification
· Gaming tools and platforms (e.g., Duolingo,
Kahoot, Goold Read-Along App, Quizlet) could
assist game-based learning.
· Immersive
Learning/
Situation
Learning/
Scenario
Learning
· Virtual reality (VR), Augmented reality (AR),
Mixed reality, Spatial computing, Metaverse-
based content learning experience platforms,
gamification and scenario-based learning,
story-based learning, and branch simulations for
developing immersive learning environments,
could enable immersive, situational, and scenario
learning.
• Mobile Learning • Mobile learning platforms (e.g., Mobile version of
Learning Management Systems; Mobile apps)
could enable mobile learning.
• Hybrid Learning • Classroom technologies for Hybrid Class (e.g.,
Tracking cameras, Wireless microphones, Smart
Panels, Online Video Conferencing Tools such as
Zoom).
• Online Learning • Online learning (or e-learning) has been and will
be supported by various technologies (e.g., High
speed Internet, Wi-Fi, Learning Management
Systems, Online learning portals, Video
Conferencing tools, Online video sites).

Business
Process
Trends and
Opportunities
· Open Learning · Open educational resources (e.g., Open Source
Software, Open Access, Open Data and
Crowdsourcing Platforms) could support open
learning.
· Online
Academic
Integrity
· Tools such as Zoom, Webcams, Moodle
Proctoring, Canvas’s Respondus Lockdown
Browser and Monitor, could assist in ensuring
online academic integrity.
· Remote
Learning
continuing after
COVID-19
(Remote
learning will
stay after
COVID-19)
· Remote learning facilitating tools (e.g., Video
conferencing systems such as Zoom, Google
Meet, Microsoft Team) could support remote
learning/e-learning.
· Experiential
Learning
· Tools such as Simulations, AR/VR and Gaming
for hands-on experience could support
experiential learning.
· Lifelong
Learning
· Self-learning or teaching assistant platforms (such
as Khan Academy, Udemy, Coursera, Edx,
Udacity., MOCC) and open source platforms
(e.g., Open edX, Sakai) could assist students/
learners’ lifelong learning and competence-based
learning. Virtual assistant could assist in
answering routine questions while machine
learning and predictive modeling could assist in
marking.
· Competence-
based Learning
· Self-learning or teaching assistant platforms (such
as Khan Academy, Udemy, Coursera, Edx,
Udacity., MOCC) and open source platforms
(e.g., Open edX, Sakai) could assist lifelong
learning and competence-based learning. Virtual
assistant could assist in answering routine
questions and follow-ups while machine learning
and predictive modelling could assist in marking.
(Continued)

Business
Process
Trends and
Opportunities
· Micro-Learning · Microlearning caters learners’ specific needs and
interests and allows them to choose their own
learning content and format, and it is a type of
personalised learning. It can be delivered via
learning management systems, mobile apps and
social media platforms.
· Video Learning · Video learning could be facilitated by videos and
interactive videos.
· Informal
Learning
· Tools such as short message services (SMS) and
Social media chats could facilitate informal and
social learning.
· Social Learning · Tools such as SMS and Social media chats could
facilitate informal and social learning.
· Metaverse
Learning
· Virtual universe (the Metaverse) enabled by
technologies such as 5G, VR, AR, and 3D could
provide learners with more advanced level
immersive and interactive learning.
· Decentralized
Learning
(Learning
anytime and
anywhere
and moving
around tools
seamlessly)
· Technologies such as Web3 could provide
decentralized learning to learners, which will be
more personalized, more interactive and more
immersive.
· Micro-Learning · Tools (such as text, images, videos, audios, tests
and quizzes, and games) could facilitate micro-
learning (bite-sized learning (normally 3–5
minutes learning)).
· Nudge Learning · Nudge Learning could be facilitated by
personalized messages and task-oriented
nudges (e.g., auto-reminders and push
notifications).

Business
Process
Trends and
Opportunities
Evaluation of
Teaching
and
Learning
· Real-time
Student
Feedback
· Learning
(Analytics for
better
understanding
students’ needs
and learning
performance and
thus enhancing
teaching quality)
· Tools such as Real-time survey tools, Real-time
applications for capturing and analyzing facial
expressions of students, could support collecting
students’ feedback.
· Tools for analyzing learning trends and behavior
include: Visual data mining, Tree learning
methods, Text mining, Support vector machines,
Smooth inverse frequency algorithm, Sequential
pattern mining, Recurrent neural networks,
Probabilistic learning methods, Parallel practice
swarm optimization, Outliner detection, Neural
networks, Generic algorithm, Deep Q-learning
algorithm, Native bayes algorithm, Fizzy logic,
K-nearest neighbor, Differential sequence mining,
Decision trees, Correlation mining, Content based
filtering techniques, Collaborative filtering
techniques, Clustering, Classifications, Bayesian
networks, Bayesian knowledge tracing,
Association rules mining, Ant colony
optimization, Data visualization, Maximum
likelihood analysis, Semantic similarity analysis,
and Natural learning process as well as tools for
presenting results of learning analytics including
Learning analytics dashboard for advisers,
Learning dashboard for insights and support,
SmartKlass, Acrobatiq, Signals and Klassdata.
Sources: 360Learning (2023); Baig et al. (2023); Brasca et al. (2022); Brussels et al. (2017); Bujan
(2021); Chui et al. (2022c); Chui et al. (2022b); CMU (2023a, 2023b: 46); Das (2023); Das et al.
(2023); Deveau et al. (2023); Hall et al. (2023); Hancock et al. (2022); Hancock et al. (2023);
Harbinger Group (2023); Hatami et al. (2023); Hyler (2006); Kabudi et al. (2021); Keppell
(2023); Khan and Kirland (2019); Laverdiere et al. (2023); McKinsey (2017); McKinsey Explainers
(2023); Microsoft (2020); Monash University (2023); Mougiakou et al. (2023); Moore and
Martinotti (2016); Pandit et al. (2012); Pappas (2020: 29–32); Pappas (2023: 20–23); Pappas (2023b);
Polito and Temperini (2021); Sanghvi and Westhoff, (2022); Small (2022); Spice (2020); Tauscher
and Kietzmann (2017); the author’s own knowledge); Torbet, (2022); UNESCO (2019); UNESCO
(n.d.); Wang et al. (2022: Wikipedia (2023a, 2023b, 2023c); Xu (2019: 103–104); Xu and Gao
(2021: 110–112).

Table 2: Future trends and opportunities in the supporting areas.
Business
Process
Trends and
Opportunities
Technologies for Addressing the Identified
Trends/Opportunities
Student
Recruitment
· Developing
Marketing Materials
· Dealing with
Inquiries and
Provide 24/7
Personalized
Services
· Promoting products
· Analyzing Collected
Information and
Providing
Forecasting
· AI tools (such as ChatGPT) could assist in
developing the content of marketing
documents.
· AI tools (such as Chatbots, Virtual
Assistants, Intelligent Agent, Generative AI
applications for generating personalized
emails/messages) could answer questions in
real-time and provide 24/7 personalized
customer services.
· Applications (such as Collaborative filters
recommendation systems) could make
personal recommendations to customers.
· Applications (such as Google Analytics,
Dynamic audience targeting and segmentation
tools, Predictive models) could help analyze
the online traffic and make forecasts.
IT Support/
Services
· Integrating artificial
intelligence (AI)
into technical
infrastructure
· Integrating learners’
own devices into
learning platforms
· Integrating generative AI model at key
customer touchpoints to facilitate a tailored
customer journey (e.g.,
customerCustomer facing interaction
applicationsGenerative AI
modelBackend applicationsData
sourceInfrastructure and Compute).
· Bring your own devices (BYOD has been
becoming the norm. Learners typically have
multiple devices (e.g., smart phone, laptop,
game console, i-pad, i-watch), their devices
should be allowed to integrate into the
learning provider’s networks and access the
learning content seamlessly.
Teaching Staff
and
Professional
Staff
Recruitment
and Other
HR Matters
· AI tools for
identifying suitable
candidates
· Online portals
for HR related
matters
· AI-enabled software could assist in
matching candidates with job descriptions.
· Online portals could provide many self-
services of HR matters (e.g., leave
application, travel requests, travel expense
reconciliation, training and development
activities).

Business
Process
Trends and
Opportunities
· AI tools for writing
job requirements
and providing
services to
candidates.
· AI tools for developing job requirements
and position descriptions.
· AI tools for providing personalized services
to candidates.
Student
Experience,
Services and
Information
Management
· Platforms and
Systems for
centrally managing
student information
· Connectivity and
Community
Building
· Student progress
monitoring and
at-risk alerts
· Cloud-based ERP systems (e.g., TechOne
and SAP) could help manage student
information.
· AI enabled student management system
could help monitor student learning
activities.
· Virtual collaboration and social media tools
can assist in connectivity and community
building.
· Student management systems, learning
management systems and AI applications
could help track the student’s progress.
Business
Strategy
· Using digital
technology to
facilitate learners’
lifelong learning
journey
· Partnership
development
· Working on factors
shaping future
digital education
· Best of breed of formal and informal digital
content could support lifelong learning.
· Digital learning credentials, digital
identification, and talent analytics across
systems could support end to end (E2E)
personalized lifelong learning.
· Extranet/Portals/Hubs for partnerships
between e-learning platforms and
corporations, training and development
agencies, traditional educational institutions,
are emerging. Another trend is recruitment
and human resources service firms are
entering the e-learning arena. For example,
the leading recruitment site in Australia and
New Zealand Seek.com and offers online
courses (in areas of Business, Information
Technology, Healthcare, Logistics and
Transport) via its Seeklearning site and has
partnership with universities and industry
collaborators. Recruitment firms such as
(Continued)

Business
Process
Trends and
Opportunities
Seek could have more updated and
comprehensive understanding of the job
market, required skills, and business
expectations than traditional training
providers (e.g., universities and colleges).
· Leveraging opportunities from factors
shaping future digital education, including
Common accreditation for digital curriculum
and credentials, Transparency around
outcomes, Data privacy regulations and IP
rights, Building and strengthening digital
capabilities at all levels, Integration of
real-world application of skills, Investing in
building communities and networks, and
Efficient setup and deployment of secure IT
infrastructure and devices.
Governance
and
Organization
· Creating learning
experiences and
resources
· Dedicated platforms and open ecosystems as
well as outcome-based/skills-based
educational approach with predictive
analytics and feedback systems could assist
in developing governance and managing
organization for creating learning resources
and environments.
Leadership,
Talent and
Culture
· Focusing on internal
capabilities and
needs
· Building centres of excellence, sharing
capabilities, internal virtual corporate
universities/training centres, and digital
talent management tools could facilitate
efforts of developing internal capabilities of
leadership, talent and culture.
Technology
and
Operations
· Concentrating on
technological
infrastructure and
standards
deployment
· Adoption of scalable cloud solutions with
open API (application programming
interface) and LTI (learning tools
interoperability) standards and integration of
platforms and systems based on common
standards could assist in technology
infrastructure and standards.
Sources: Refer to Table 1.

5.3.
Opportunities Arising from Future Skills and
Future Trends
Hall et al. (2023) report that the impact of automation and digitization on the
workforce will be seen at least next 10–15 years, and almost 50% of all work
activities could be potentially automated, and 1 in 16 workers might have to
change occupations by 2030. Manyika et al. (2017) further suggest that by
2030 75 million to 375 million workers (i.e., 3%–14% of the global work
force) will need to change occupation and upgrade skills due to automation.
According to a recent survey conducted by Sweetrush (reported in
Soto et al. 2023: 10), some identified top skills in demand in the organiza-
tion are (in the order): Agility and adaptability, Analytics and reporting,
Collaboration, Diversity, equity, inclusion, and belongings, Coaching
mindset, Emotional intelligence, Leadership, Strategic thinking, Critical
thinking, and Innovation. In the same survey, some top learning chal-
lenges in the organizations are: Future-proofing the organization to
address skill gaps, Establishing a culture of learning, Providing engaging
learning experiences, Elevating the strategic position of learning and
development, Developing learning programs in an uncertain economic
environment, Keeping up with the needs of the business, Aligning learn-
ing needs with business objectives, Offering people with learning and
growth opportunities, Using data for learning improvement, and Properly
designing learning delivery models (e.g., remote learning/e-learning and
hybrid/blended learning) (Soto et al., 2023: 26). To be successful with
their learning and development, organizations need to: embrace technol-
ogy, have a culture of continuous learning, measure the outcomes, and
make learning a strategic priority (Soto et al., 2023: 30–31).
Craig (2021) argues that digital platforms skills (e.g., skills required
for SaaS (software as a service) platforms) and other demanded digital
transformation skills have not been addressed by universities. Meanwhile
According to LinkedIn Learning (2023), Some highly demanded skills by
companies are (in the order): Management, Communication, Customer
Service, Leadership, Sales, Project Management, Research, Analytical
Skills, Marketing, and Teamwork. Table 3 presents some highly demanded
skills by business function.
Bughin et al. (2016) suggest that if firms adopted currently available
technology for their digitization initiatives, approximately 70% of the
activities of some 20% of all occupations could be automated. They fur-
ther point out that the following future changes in the occupation:

• Unbundling and rebundling the jobs/tasks enabled by digital
technologies.
• Shifting to project-based work (rather than function-based) supported
by digital technology-enabled workflows.
• Changing from salaried job to independent work that gives people
great autonomy and control over their time and it is made possible by
the Internet and digital tools.
• Focusing more on skills (including both technical and soft skills) than
formal educational credentials and degrees (such change could be
facilitated by digital tools such as online work platforms, online rating
systems).
Table 3: Highly demanded skills by business function.
Business Function Highly Demanded Skills (in the Order)
Business Management, Communication, Customer service,
Leadership, Sales, Marketing, Project Management,
Finance, Analytics skills, and Teamwork.
Finance/
Accounting
Management, Analytical skills, Customer Service,
Communication, Leadership, Financial Analysis, Sales,
Teamwork, Research, and Financial Planning.
Engineering JavaScript, Java, SQL, Python programming language,
Cascading style sheets, HTML, Management, Cloud
Computing, Git, and C++.
Information
Technology
Management, SQL, Microsoft Office, Project management,
Analytics skills, Communication, Customer service,
Leadership, Cloud computing, and Python programming
language.
Marketing Social media, Management, Digital marketing,
Communication, Strategy, Marketing strategy, Leadership,
Project management, Advertising, and Customer service.
Project and
Program
Management
Management, Leadership, Communication, Engineering,
Analytical skills, Customer service, Strategy, Team
leadership, Marketing, and Research.
Sales Customer service, Management, Communication,
Marketing, Leadership, Account management, Sales
management, Microsoft Office, Business development,
and Business.
Source: LinkedIn Learning 2023.

• Using online communities more than other employee associations
(e.g., unions) to gain peer support and present employees’ joint forces
directly to the firm and the government.
• Instead of using digitization and automation to replace human labor,
firms need to invest in human labor to equip them with both digital
literacy/skills (e.g., literacy/skills for cloud computing, data analytics)
and business skills otherwise the collected large volume data and the
manufactured large number of robots will not achieve their intended
effects.
• Changing employment from companies to platforms and ecosystems
(e.g., freelancer Youtubers and people making a living on social
media platforms).
On a related note, 93% of organizations are worried about employee
retention, and many organizations believe that providing learning oppor-
tunities is the most effective way to improve retention (Soto et al. 2023:
28). In other words, if organizations could provide people with training
for the demanded skills discussed in the previous sections, then people
will be more likely to stay and make greater contribution. The digital
technologies and applications discussed in the beginning of this chapter
and in the Sections 5.1 and 5.2 of this chapter could definitely enable or
facilitate learning and training activities pursued by organizations.
6. Focusing on Artificial Intelligence (AI)
It is forecasted that the economic value from AI (including both genera-
tive AI and non-generative AI) is $13.6–22.1 trillion (i.e., $11–17 trillion
for non-generative AI and $2.6–4.4 trillion for generative AI) (reported in
Chui et al., 2022b: 23; Chui et al., 2023). The differences between genera-
tive AI (e.g., ChatGTP, Virtual Assistants, Virtual Experts, Virtual
Collaborators, Automatic Content and Document Creation Applications)
and non-generative (traditional) AI are: the former could generate similar
data based on training data and generate content/responses based on users’
prompts while the latter has been typically used for analysis, predication
and pattern identification enabled by technologies such as advanced ana-
lytics, traditional machine learning and deep learning.
Some widely used AI capabilities in the organization include: Robotic
process automation, Computer vision, Natural-language text understand-
ing, Virtual agents or conversational interfaces, Deep learning, Knowledge

graphs, Recommender systems, Digital twins, Natural-language speech
understanding, Physical robotics, Reinforcement learning, Facial recogni-
tion, Natural-language generation, Transfer learning, Generative adver-
sarial networks, and Transformers. Meanwhile AI capabilities have been
used for functional activities such as: Service operations optimization,
Creation of new AI-based products, Customer service analytics, Customer
segmentation, New AI-based enhancement of products, Customer acquisi-
tion and lead generation, Contact-center automation, Product feature
optimization, Risk modeling and analytics, and Predictive service and
intervention (Chui et al., 2022). Meanwhile some AI-related positions in
the organization include: Software engineers, Data engineers, AI data
scientists, Machine learning engineers, AO product owners/managers,
Design specialists, Data visualization specialists, and Translators (Chui
et al., 2022).
The adoption of AI around the world has increased rapidly due to fac-
tors such as faster global expansion (e.g., 56% of participants of a recent
McKinsey global survey are embarking on AI), easier and more afforda-
ble AI implementation (e.g., 94.4% improvement in training speed for AI
training models since 2018), fast-growing innovation (e.g., compound
annual growth rate of filed patents for the period of 2015–2021 is 76.9%),
and significant investment growth (e.g., private investment in AI-related
companies increased 100% to $93.5 billion for the period of 2020 to
2021) (Chui et al., 2022b: 22). On the other hand, adoption of AI could
be a challenging task. For example, in a recent McKinsey global survey,
72% of participating organizations have not successfully adopted or
scaled their AI initiatives, and some reported reasons are: difficulties in
transition from pilots to products, model failure in production, stalling
team productivity and limitations in protection against potential risks
from unknown variables (Chui et al., 2022b: 61). Forth et al. (2023) indi-
cate that implementation challenges and data sensitivity issues are key AI
adoption barriers, and they suggest a number of success factors, including
aligning AI strategy with organizational strategy and goals, leaders’ com-
mitment, access to high caliber talent, agile governance, measuring and
monitoring outcomes, and developing business-led modular technology
and data platforms. Pappas (2023b) further point out that factors such as
insufficient or low-quality data, outdated infrastructure, issues of integrat-
ing with existing issues, lack of AI talent, overestimating the capabilities
of AI system, cost concerns, discrepancies in AI availability in different
places, and legal and ethical concerns surrounding AI (e.g., recent iTutor

Group case in the U.S. (Wiessner, 2023)), could make AI adoption more
difficult. He also suggests that when organizations are embarking on AI,
they should:
• Conducting thorough research.
• Clearly defining your problems and goals.
• Putting together a good AI team and training the team properly.
• Effectively evaluating your tools.
• Starting small.
• Preparing your organization for AI.
• Having good understanding of your data.
• Properly training your AI models with good-quality data.
• Determining suitable use cases.
• Measuring and monitoring the results.
Chui et al. (2022) suggest successful AI implementation could be
looked at the following four perspectives:
• Strategy (e.g., Clear road map, Senior management’s support, Clearly
defined AI vision and strategy, Alignment between AI strategy and
business strategy, Creditable AI leaders, Well-defined KPIs to meas-
ure AI impacts, Clear frameworks for AI governance).
• Data (e.g., Integration of data from various sources into AI models,
Process of preparing data for AI models).
• Models, tools and technologies (e.g., Models for small data, Refreshing
AI models regularly, Development of modular components,
Automating the full cycle for AI model development).
• Talent and ways of working (e.g., life cycle approach to developing
and deploying AI models, integration of AI technologies with busi-
ness processes, AI working teams, well-defined capability-building
programs, Training of non-technical employees to use AI, AI develop-
ment teams following standards and protocols).
Artificial intelligence (AI) applications (include ChatGPT-type AI
applications) could only be good if they have been trained properly with
good data and AI engines (software/algorithm developed by human
experts), and even “the most advanced AI models can make significant
mistakes or fabricate information altogether” (Huddleston Jr., 2023). It
also can be argued that even though AI could be capable of processing

Random documents with unrelated
content Scribd suggests to you:

DRESSED-TURKEY GRADES
Grading systems for dressed turkeys differ somewhat in different
markets but, in general, are similar. Greatest uniformity is provided
where the United States grades are used. The United States grading
system is more comprehensive than other systems and is intended
to satisfy the demands of the consumers more fully and to promote
more uniform grading.
The United States Government grading system was developed
and is sponsored by the Bureau of Agricultural Economics, United
States Department of Agriculture. Under this system as now used
there are four grades: U. S. Special or U. S. grade AA; U. S. Prime or
U. S. grade A; U. S. Choice or U. S. grade B; and U. S. Commercial
or U. S. grade C. Each grade is subdivided into four classes
according to the age and sex of the birds.
These classes are: Young hen, young tom, old hen, and old tom.
The quality specifications for individual birds apply to each class with
due allowance for fleshing condition characteristic of its sex and age.
Detailed descriptions are provided for each grade. For the U. S.
Special grade it is required that turkeys have broad, full-fleshed
breasts and that the carcasses be fully covered with fat. The birds
must also have been well bled, carefully dry-picked or semiscalded,
and must be free from bruises, skin tears, and broken joints. The
breastbone must be straight or only slightly dented (not more than
one-fourth inch in depth). For the U. 3. Prime grade it is required
that birds be well fleshed, well fattened, and well bled, but they may
have slight imperfections such as scattered pinfeathers, slight flesh
or skin abrasions, and one disjointed but not broken wing or leg.
Slightly curved and slightly dented breastbones, not to exceed one-
half inch in depth, are permitted. To grade U. S. Choice, turkeys
must have fairly well-fleshed breasts and carcasses fairly well

covered with fat. These birds need be only fairly well bled and
dressed and may have slight flesh or skin bruises, small skin tears,
or larger sewn-up tears, and one broken leg or wing. Turkeys not
meeting these grade requirements, including birds poorly fleshed,
poorly bled, or slightly deformed, but suitable for food, make up the
lowest or U. S. Commercial grade.
Another system of grading in common use in buying dressed
turkeys is to make only 2 or 3 grades, except that sometimes the
birds within the top grades are divided into classes based on weight
and sex. The no. 1 grade usually consists of young toms weighing
12 pounds or more and young and old hens weighing 8 pounds or
more, dressed. For this grade the birds must be well finished and
free from serious tears, bruises, and severely crooked breastbones.
The crops must be empty and the carcasses reasonably free from
pinfeathers and reasonably well bled. The no. 2 grade includes all
old toms and such young toms, young hens, and old hens as are too
light for the no. 1 grade. The no. 2 grade also includes turkeys with
severely crooked breastbones, broken wings, bad blemishes, bad
tears, bad abrasions, feed in crops, numerous pinfeathers, and birds
that have been poorly bled or poorly fleshed. The no. 3 grade
includes birds not good enough for the no. 2 grade but still fit for
food. These are culls that never should have been marketed. The no.
3 grade is not always used, since turkeys of this kind are often
rejected by the buyers. On some markets a medium grade of birds—
between the no. 1 and the no. 2 grades—is used.
When graded and packed for market turkeys are further graded
as to size, birds of similar weight being placed in the same container,
which is labeled according to the grade.
ORGANIZATION OF THE UNITED STATES
DEPARTMENT OF AGRICULTURE WHEN THIS
PUBLICATION WAS LAST PRINTED

Secretary of Agriculture Henry A. Wallace
Undersecretary M. L. Wilson
Assistant Secretary Harry L. Brown.
Coordinator of Land Use Planning and
Director of Information.
M. S. Eisenhower.
Director of Extension Work C. W. Warburton
Director of Finance W. A. Jump
Director of Personnel Roy F. Hendrickson
Director of Research James T. Jardine
Solicitor Mastin G. White
Agricultural Adjustment Administration H. R. Tolley, Administrator.
Bureau of Agricultural Economics A. G. Black, Chief.
Bureau of Agricultural Engineering S. H. McCrory, Chief.
Bureau of Animal Industry John R. Mohler, Chief.
Bureau of Biological Survey Ira N. Gabrielson, Chief.
Bureau of Chemistry and Soils Henry G. Knight, Chief.
Commodity Exchange Administration J. W. T. Duvel, Chief.
Bureau of Dairy Industry O. E. Reed, Chief.
Bureau of Entomology and Plant
Quarantine
Lee A. Strong, Chief.
Office of Experiment Stations James T. Jardine, Chief.
Farm Security Administration
W. W. Alexander,
Administrator.
Food and Drug Administration Walter G. Campbell, Chief.
Forest Service Ferdinand A. Silcox, Chief.
Bureau of Home Economics Louise Stanley, Chief.
Library
Claribel R. Barnett,
Librarian.
Bureau of Plant Industry E. C. Auchter, Chief.
Bureau of Public Roads Thomas H. MacDonald, Chief.
Soil Conservation Service H. H. Bennett, Chief.
Weather Bureau
Francis W. Reichelderfer,
Chief.

For sale by the Superintendent of Documents, Washington, D. C.
Price 5 cents
U. S. GOVERNMENT PRINTING OFFICE: 1939
Transcriber Note
Illustrations were moved to avoid splitting paragraphs.
Display of numbers was standardized in the tables to show
leading zeros.

*** END OF THE PROJECT GUTENBERG EBOOK TURKEY RAISING
***
Updated editions will replace the previous one—the old editions will
be renamed.
Creating the works from print editions not protected by U.S.
copyright law means that no one owns a United States copyright in
these works, so the Foundation (and you!) can copy and distribute it
in the United States without permission and without paying
copyright royalties. Special rules, set forth in the General Terms of
Use part of this license, apply to copying and distributing Project
Gutenberg™ electronic works to protect the PROJECT GUTENBERG™
concept and trademark. Project Gutenberg is a registered trademark,
and may not be used if you charge for an eBook, except by following
the terms of the trademark license, including paying royalties for use
of the Project Gutenberg trademark. If you do not charge anything
for copies of this eBook, complying with the trademark license is
very easy. You may use this eBook for nearly any purpose such as
creation of derivative works, reports, performances and research.
Project Gutenberg eBooks may be modified and printed and given
away—you may do practically ANYTHING in the United States with
eBooks not protected by U.S. copyright law. Redistribution is subject
to the trademark license, especially commercial redistribution.
START: FULL LICENSE

THE FULL PROJECT GUTENBERG LICENSE

PLEASE READ THIS BEFORE YOU DISTRIBUTE OR USE THIS WORK
To protect the Project Gutenberg™ mission of promoting the free
distribution of electronic works, by using or distributing this work (or
any other work associated in any way with the phrase “Project
Gutenberg”), you agree to comply with all the terms of the Full
Project Gutenberg™ License available with this file or online at
www.gutenberg.org/license.
Section 1. General Terms of Use and
Redistributing Project Gutenberg™
electronic works
1.A. By reading or using any part of this Project Gutenberg™
electronic work, you indicate that you have read, understand, agree
to and accept all the terms of this license and intellectual property
(trademark/copyright) agreement. If you do not agree to abide by all
the terms of this agreement, you must cease using and return or
destroy all copies of Project Gutenberg™ electronic works in your
possession. If you paid a fee for obtaining a copy of or access to a
Project Gutenberg™ electronic work and you do not agree to be
bound by the terms of this agreement, you may obtain a refund
from the person or entity to whom you paid the fee as set forth in
paragraph 1.E.8.
1.B. “Project Gutenberg” is a registered trademark. It may only be
used on or associated in any way with an electronic work by people
who agree to be bound by the terms of this agreement. There are a
few things that you can do with most Project Gutenberg™ electronic
works even without complying with the full terms of this agreement.
See paragraph 1.C below. There are a lot of things you can do with
Project Gutenberg™ electronic works if you follow the terms of this
agreement and help preserve free future access to Project
Gutenberg™ electronic works. See paragraph 1.E below.

1.C. The Project Gutenberg Literary Archive Foundation (“the
Foundation” or PGLAF), owns a compilation copyright in the
collection of Project Gutenberg™ electronic works. Nearly all the
individual works in the collection are in the public domain in the
United States. If an individual work is unprotected by copyright law
in the United States and you are located in the United States, we do
not claim a right to prevent you from copying, distributing,
performing, displaying or creating derivative works based on the
work as long as all references to Project Gutenberg are removed. Of
course, we hope that you will support the Project Gutenberg™
mission of promoting free access to electronic works by freely
sharing Project Gutenberg™ works in compliance with the terms of
this agreement for keeping the Project Gutenberg™ name associated
with the work. You can easily comply with the terms of this
agreement by keeping this work in the same format with its attached
full Project Gutenberg™ License when you share it without charge
with others.
1.D. The copyright laws of the place where you are located also
govern what you can do with this work. Copyright laws in most
countries are in a constant state of change. If you are outside the
United States, check the laws of your country in addition to the
terms of this agreement before downloading, copying, displaying,
performing, distributing or creating derivative works based on this
work or any other Project Gutenberg™ work. The Foundation makes
no representations concerning the copyright status of any work in
any country other than the United States.
1.E. Unless you have removed all references to Project Gutenberg:
1.E.1. The following sentence, with active links to, or other
immediate access to, the full Project Gutenberg™ License must
appear prominently whenever any copy of a Project Gutenberg™
work (any work on which the phrase “Project Gutenberg” appears,
or with which the phrase “Project Gutenberg” is associated) is
accessed, displayed, performed, viewed, copied or distributed:

This eBook is for the use of anyone anywhere in the United
States and most other parts of the world at no cost and with
almost no restrictions whatsoever. You may copy it, give it away
or re-use it under the terms of the Project Gutenberg License
included with this eBook or online at www.gutenberg.org. If you
are not located in the United States, you will have to check the
laws of the country where you are located before using this
eBook.
1.E.2. If an individual Project Gutenberg™ electronic work is derived
from texts not protected by U.S. copyright law (does not contain a
notice indicating that it is posted with permission of the copyright
holder), the work can be copied and distributed to anyone in the
United States without paying any fees or charges. If you are
redistributing or providing access to a work with the phrase “Project
Gutenberg” associated with or appearing on the work, you must
comply either with the requirements of paragraphs 1.E.1 through
1.E.7 or obtain permission for the use of the work and the Project
Gutenberg™ trademark as set forth in paragraphs 1.E.8 or 1.E.9.
1.E.3. If an individual Project Gutenberg™ electronic work is posted
with the permission of the copyright holder, your use and distribution
must comply with both paragraphs 1.E.1 through 1.E.7 and any
additional terms imposed by the copyright holder. Additional terms
will be linked to the Project Gutenberg™ License for all works posted
with the permission of the copyright holder found at the beginning
of this work.
1.E.4. Do not unlink or detach or remove the full Project
Gutenberg™ License terms from this work, or any files containing a
part of this work or any other work associated with Project
Gutenberg™.
1.E.5. Do not copy, display, perform, distribute or redistribute this
electronic work, or any part of this electronic work, without
prominently displaying the sentence set forth in paragraph 1.E.1

with active links or immediate access to the full terms of the Project
Gutenberg™ License.
1.E.6. You may convert to and distribute this work in any binary,
compressed, marked up, nonproprietary or proprietary form,
including any word processing or hypertext form. However, if you
provide access to or distribute copies of a Project Gutenberg™ work
in a format other than “Plain Vanilla ASCII” or other format used in
the official version posted on the official Project Gutenberg™ website
(www.gutenberg.org), you must, at no additional cost, fee or
expense to the user, provide a copy, a means of exporting a copy, or
a means of obtaining a copy upon request, of the work in its original
“Plain Vanilla ASCII” or other form. Any alternate format must
include the full Project Gutenberg™ License as specified in
paragraph 1.E.1.
1.E.7. Do not charge a fee for access to, viewing, displaying,
performing, copying or distributing any Project Gutenberg™ works
unless you comply with paragraph 1.E.8 or 1.E.9.
1.E.8. You may charge a reasonable fee for copies of or providing
access to or distributing Project Gutenberg™ electronic works
provided that:
• You pay a royalty fee of 20% of the gross profits you derive
from the use of Project Gutenberg™ works calculated using the
method you already use to calculate your applicable taxes. The
fee is owed to the owner of the Project Gutenberg™ trademark,
but he has agreed to donate royalties under this paragraph to
the Project Gutenberg Literary Archive Foundation. Royalty
payments must be paid within 60 days following each date on
which you prepare (or are legally required to prepare) your
periodic tax returns. Royalty payments should be clearly marked
as such and sent to the Project Gutenberg Literary Archive
Foundation at the address specified in Section 4, “Information

about donations to the Project Gutenberg Literary Archive
Foundation.”
• You provide a full refund of any money paid by a user who
notifies you in writing (or by e-mail) within 30 days of receipt
that s/he does not agree to the terms of the full Project
Gutenberg™ License. You must require such a user to return or
destroy all copies of the works possessed in a physical medium
and discontinue all use of and all access to other copies of
Project Gutenberg™ works.
• You provide, in accordance with paragraph 1.F.3, a full refund of
any money paid for a work or a replacement copy, if a defect in
the electronic work is discovered and reported to you within 90
days of receipt of the work.
• You comply with all other terms of this agreement for free
distribution of Project Gutenberg™ works.
1.E.9. If you wish to charge a fee or distribute a Project Gutenberg™
electronic work or group of works on different terms than are set
forth in this agreement, you must obtain permission in writing from
the Project Gutenberg Literary Archive Foundation, the manager of
the Project Gutenberg™ trademark. Contact the Foundation as set
forth in Section 3 below.
1.F.
1.F.1. Project Gutenberg volunteers and employees expend
considerable effort to identify, do copyright research on, transcribe
and proofread works not protected by U.S. copyright law in creating
the Project Gutenberg™ collection. Despite these efforts, Project
Gutenberg™ electronic works, and the medium on which they may
be stored, may contain “Defects,” such as, but not limited to,
incomplete, inaccurate or corrupt data, transcription errors, a
copyright or other intellectual property infringement, a defective or

damaged disk or other medium, a computer virus, or computer
codes that damage or cannot be read by your equipment.
1.F.2. LIMITED WARRANTY, DISCLAIMER OF DAMAGES - Except for
the “Right of Replacement or Refund” described in paragraph 1.F.3,
the Project Gutenberg Literary Archive Foundation, the owner of the
Project Gutenberg™ trademark, and any other party distributing a
Project Gutenberg™ electronic work under this agreement, disclaim
all liability to you for damages, costs and expenses, including legal
fees. YOU AGREE THAT YOU HAVE NO REMEDIES FOR
NEGLIGENCE, STRICT LIABILITY, BREACH OF WARRANTY OR
BREACH OF CONTRACT EXCEPT THOSE PROVIDED IN PARAGRAPH
1.F.3. YOU AGREE THAT THE FOUNDATION, THE TRADEMARK
OWNER, AND ANY DISTRIBUTOR UNDER THIS AGREEMENT WILL
NOT BE LIABLE TO YOU FOR ACTUAL, DIRECT, INDIRECT,
CONSEQUENTIAL, PUNITIVE OR INCIDENTAL DAMAGES EVEN IF
YOU GIVE NOTICE OF THE POSSIBILITY OF SUCH DAMAGE.
1.F.3. LIMITED RIGHT OF REPLACEMENT OR REFUND - If you
discover a defect in this electronic work within 90 days of receiving
it, you can receive a refund of the money (if any) you paid for it by
sending a written explanation to the person you received the work
from. If you received the work on a physical medium, you must
return the medium with your written explanation. The person or
entity that provided you with the defective work may elect to provide
a replacement copy in lieu of a refund. If you received the work
electronically, the person or entity providing it to you may choose to
give you a second opportunity to receive the work electronically in
lieu of a refund. If the second copy is also defective, you may
demand a refund in writing without further opportunities to fix the
problem.
1.F.4. Except for the limited right of replacement or refund set forth
in paragraph 1.F.3, this work is provided to you ‘AS-IS’, WITH NO
OTHER WARRANTIES OF ANY KIND, EXPRESS OR IMPLIED,

INCLUDING BUT NOT LIMITED TO WARRANTIES OF
MERCHANTABILITY OR FITNESS FOR ANY PURPOSE.
1.F.5. Some states do not allow disclaimers of certain implied
warranties or the exclusion or limitation of certain types of damages.
If any disclaimer or limitation set forth in this agreement violates the
law of the state applicable to this agreement, the agreement shall be
interpreted to make the maximum disclaimer or limitation permitted
by the applicable state law. The invalidity or unenforceability of any
provision of this agreement shall not void the remaining provisions.
1.F.6. INDEMNITY - You agree to indemnify and hold the Foundation,
the trademark owner, any agent or employee of the Foundation,
anyone providing copies of Project Gutenberg™ electronic works in
accordance with this agreement, and any volunteers associated with
the production, promotion and distribution of Project Gutenberg™
electronic works, harmless from all liability, costs and expenses,
including legal fees, that arise directly or indirectly from any of the
following which you do or cause to occur: (a) distribution of this or
any Project Gutenberg™ work, (b) alteration, modification, or
additions or deletions to any Project Gutenberg™ work, and (c) any
Defect you cause.
Section 2. Information about the Mission
of Project Gutenberg™
Project Gutenberg™ is synonymous with the free distribution of
electronic works in formats readable by the widest variety of
computers including obsolete, old, middle-aged and new computers.
It exists because of the efforts of hundreds of volunteers and
donations from people in all walks of life.
Volunteers and financial support to provide volunteers with the
assistance they need are critical to reaching Project Gutenberg™’s
goals and ensuring that the Project Gutenberg™ collection will

remain freely available for generations to come. In 2001, the Project
Gutenberg Literary Archive Foundation was created to provide a
secure and permanent future for Project Gutenberg™ and future
generations. To learn more about the Project Gutenberg Literary
Archive Foundation and how your efforts and donations can help,
see Sections 3 and 4 and the Foundation information page at
www.gutenberg.org.
Section 3. Information about the Project
Gutenberg Literary Archive Foundation
The Project Gutenberg Literary Archive Foundation is a non-profit
501(c)(3) educational corporation organized under the laws of the
state of Mississippi and granted tax exempt status by the Internal
Revenue Service. The Foundation’s EIN or federal tax identification
number is 64-6221541. Contributions to the Project Gutenberg
Literary Archive Foundation are tax deductible to the full extent
permitted by U.S. federal laws and your state’s laws.
The Foundation’s business office is located at 809 North 1500 West,
Salt Lake City, UT 84116, (801) 596-1887. Email contact links and up
to date contact information can be found at the Foundation’s website
and official page at www.gutenberg.org/contact
Section 4. Information about Donations to
the Project Gutenberg Literary Archive
Foundation
Project Gutenberg™ depends upon and cannot survive without
widespread public support and donations to carry out its mission of
increasing the number of public domain and licensed works that can
be freely distributed in machine-readable form accessible by the
widest array of equipment including outdated equipment. Many

small donations ($1 to $5,000) are particularly important to
maintaining tax exempt status with the IRS.
The Foundation is committed to complying with the laws regulating
charities and charitable donations in all 50 states of the United
States. Compliance requirements are not uniform and it takes a
considerable effort, much paperwork and many fees to meet and
keep up with these requirements. We do not solicit donations in
locations where we have not received written confirmation of
compliance. To SEND DONATIONS or determine the status of
compliance for any particular state visit www.gutenberg.org/donate.
While we cannot and do not solicit contributions from states where
we have not met the solicitation requirements, we know of no
prohibition against accepting unsolicited donations from donors in
such states who approach us with offers to donate.
International donations are gratefully accepted, but we cannot make
any statements concerning tax treatment of donations received from
outside the United States. U.S. laws alone swamp our small staff.
Please check the Project Gutenberg web pages for current donation
methods and addresses. Donations are accepted in a number of
other ways including checks, online payments and credit card
donations. To donate, please visit: www.gutenberg.org/donate.
Section 5. General Information About
Project Gutenberg™ electronic works
Professor Michael S. Hart was the originator of the Project
Gutenberg™ concept of a library of electronic works that could be
freely shared with anyone. For forty years, he produced and
distributed Project Gutenberg™ eBooks with only a loose network of
volunteer support.

Project Gutenberg™ eBooks are often created from several printed
editions, all of which are confirmed as not protected by copyright in
the U.S. unless a copyright notice is included. Thus, we do not
necessarily keep eBooks in compliance with any particular paper
edition.
Most people start at our website which has the main PG search
facility: www.gutenberg.org.
This website includes information about Project Gutenberg™,
including how to make donations to the Project Gutenberg Literary
Archive Foundation, how to help produce our new eBooks, and how
to subscribe to our email newsletter to hear about new eBooks.

Welcome to our website – the perfect destination for book lovers and
knowledge seekers. We believe that every book holds a new world,
offering opportunities for learning, discovery, and personal growth.
That’s why we are dedicated to bringing you a diverse collection of
books, ranging from classic literature and specialized publications to
self-development guides and children's books.
More than just a book-buying platform, we strive to be a bridge
connecting you with timeless cultural and intellectual values. With an
elegant, user-friendly interface and a smart search system, you can
quickly find the books that best suit your interests. Additionally,
our special promotions and home delivery services help you save time
and fully enjoy the joy of reading.
Join us on a journey of knowledge exploration, passion nurturing, and
personal growth every day!
ebookbell.com

Teaching And Learning In The Digital Era Issues And Studies Jun Xu

More Related Content

Similar to Teaching And Learning In The Digital Era Issues And Studies Jun Xu (20)

Recently uploaded (20)

Teaching And Learning In The Digital Era Issues And Studies Jun Xu