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Generative Artificial Intelligence Applications

Holistic Reflections From The Educational Landscape

by Hasan Tinmaz (Volume editor) Seda Gökçe Turan (Volume editor)
©2024 Edited Collection 300 Pages

Summary

Artificial Intelligence (AI) is a rapidly evolving field that leverages computers to perform tasks at a speed and scale previously unimaginable. As technological advancements continue to shape every aspect of life, they are also driving significant changes in education, bringing about transformations that redefine teaching and learning.
Generative AI, a prominent development in this field, has emerged as a critical component of digital transformation in education. This book aims to explore how rapid advances in Generative AI capabilities are reshaping the educational landscape, offering innovative solutions and new possibilities for educators and learners alike.

Table Of Contents

  • Cover
  • Title
  • Copyright
  • About the author
  • About the book
  • This eBook can be cited
  • Contents
  • Preface
  • From Data to Dreams: Understanding Generative Artificial Intelligence (Hasan Tinmaz)
  • Artificial Intelligence Literacy Curriculum for Secondary School Students (Meltem Özmutlu and Şirin Karadeniz)
  • Gen-AI Use Cases for Mathematics Education: Experiments and Discussions (Ozan Evkaya and Ozhan Genc)
  • Enhancing Educational Assessment Through GenAI: Leveraging Revised Bloom’s Taxonomy for Question Generation with ChatGPT (Amine Hatun Atas, Berkan Celik, Tugce Aldemir)
  • Exploring Artificial Intelligence in Assessment: Unpacking the Whats and Hows in Education (Gürsu Aşık, Ali Öztüfekçi)
  • Beyond Gaze: Unveiling the Impact of AI-Enhanced Posture on Academic Performance in Online Entrepreneurship Education (Inhyouk (David) Koo, Hojung Ha)
  • Unlocking Potential? The Transformative Role of Artificial Intelligence in Special Education (Dorota Chimicz)
  • Artificial Intelligence in Educational Therapy of Children with Special Educational Needs (Magdalena Wójcik)
  • The Use of Artificial Intelligence in Personalized Learning (Doğan Aydın)
  • Optimizing Content for Educational Curricula with Large Language Models (LLMs) (Storm Schutte, Hasan Tinmaz)
  • Next-Generation Learning: Unleashing Generative AI in Chinese K12 Education (Yunze Liu, Hasan Tinmaz)
  • Illuminating Teachers’ Artificial Intelligence Insight in Turkish Educational Terrain (Sezin Eşfer Öndünç, Meltem Özmutlu, Seda Saraç, Seda Gökçe Turan)
  • Ethical Considerations for the Use of Artificial Intelligence (AI) in Education (Gregory Gresko)

Preface

Generative Artificial Intelligence is no longer just a futuristic concept; it has permeated various facets of our lives, significantly impacting the educational landscape. As educators, researchers, policymakers, and technologists navigate this transformative era, it becomes imperative to foster a nuanced understanding of AI’s applications and implications in education.

The chapters within this book offer a comprehensive exploration of Generative AI’s role in education, ranging from understanding generative AI to its practical implementations in curriculum development, personalized learning, assessment, and special education. Each chapter delves into specific aspects of Generative AI in education, providing insights, methodologies, and real-life case studies that shed light on both the opportunities and challenges presented by this rapidly evolving technology.

Chapter 1, ‘From Data to Dreams: Understanding Generative Artificial Intelligence,’ sets the stage by establishing a foundational understanding of generative AI, encapsulating its evolutionary timeline, technological foundations, global recognition, and potential future issues.

Subsequent chapters delve deeper into various applications of AI in education. Chapters 2 and 3 focus on curriculum development and educational assessment, respectively, showcasing how AI literacy curricula and Generative AI tools are shaping learning experiences and enhancing educational outcomes.

Chapters 4, 5, 6 and 7 explore the intersections of Generative AI with specific domains within education, such as assessment, mathematics education, online entrepreneurship education, and special education, highlighting the transformative potential of Generative AI in fostering inclusivity, personalization, and individualization.

Chapter 8 examines the practical applications of Generative AI in educational therapy, demonstrating how AI tools can support children with special educational needs, while Chapter 9 discusses personalized learning and the role of Generative AI in adapting educational content to meet the unique needs of each student.

Chapters 10 and 11 delve into content optimization and next-generation learning, illustrating how Generative AI-driven approaches can revolutionize content delivery and learning experiences, particularly in the context of Chinese K12 education.

Chapter 12 focuses on illuminating teachers’ insights on AI in the Turkish educational landscape, addressing concerns and perceptions to inform effective integration strategies.

Lastly, Chapter 13 delves into ethical considerations surrounding the use of Generative AI in education, emphasizing the importance of responsible Generative AI implementation that respects learner autonomy, fairness, and inclusiveness.

Collectively, these chapters offer a multidimensional perspective on AI’s transformative potential in education, while also highlighting the ethical, social, and practical considerations essential for its responsible deployment. By engaging with the insights and findings presented in this book, educators, policymakers, researchers, and technologists can navigate the evolving intersection of AI and education with informed decision-making and a commitment to promoting equitable, inclusive, and ethical learning environments.

Finally, the editors extend their gratitude to all the authors who contributed to this book, and we wish all our readers an enjoyable and enlightening journey through its pages.

December, 2024

Editors

Hasan Tinmaz, PhD.

AI & Big Data Department, Woosong University, Daejeon, South Korea

ORCID: 0000-0003-4310-0848

Email: htinmaz@endicott.ac.kr

From Data to Dreams: Understanding Generative Artificial Intelligence

Abstract: This chapter endeavors to establish a robust and foundational understanding of generative artificial intelligence, laying a solid groundwork for deeper exploration in subsequent sections. Beginning with a clarification of generative AI’s definition, it progresses to unravel the evolutionary timeline and technological foundations that have shaped its landscape. Delving further, it scrutinizes global recognition and adoption rates, before delving into a thorough examination of the advantages and challenges posed by generative AI applications. Culminating with an exploration of potential future issues, the chapter encapsulates its findings through a SWOT analysis, summarizing the inherent strengths, weaknesses, opportunities, and threats within generative AI. Through this comprehensive framework, readers are equipped with a nuanced comprehension essential for navigating the complexities of generative AI in the chapters ahead.

Keywords: Generative AIartificial intelligenceGen-AILarge Language Models

Introduction

The Accenture Technology Vision (2023) report which concentrates on the technological trends that form the basis of the merging of the physical and digital realms, emphasizes that the dominance of generative artificial intelligence has witnessed a rapid proliferation, wherein emerging tools have gathered attention at an accelerated pace compared to other contemporary technologies.

For instance, when launched in November 2022, ChatGPT, possibly the most famous generative AI tool, became the fastest-growing consumer application in history, reaching 100 million users in record time in 2 months. The same number of users have been reached in 7 years for WWW, 5 years for Twitter, 4.5 years for Facebook, 3.5 years for WhatsApp, 2.5 years for Instagram and 9 months for TikTok (Citi GPS, 2023).

Presently, the predominant utilization of these generative AI tools involves the creation of digital images and content; however, such applications represent merely the initial phase. It is apparent that this technological paradigm is poised to exert a transformative impact on diverse domains, including but not limited to science, enterprise data management, product design, educational processes, manufacturing methods, and countless other spheres.

Details

Pages
300
Publication Year
2024
ISBN (PDF)
9783631911839
ISBN (ePUB)
9783631930731
ISBN (Softcover)
9783631911822
DOI
10.3726/b22561
Language
English
Publication date
2025 (February)
Keywords
cyber-harassment digital media emotional intelligence
Published
Berlin, Bruxelles, Chennai, Lausanne, New York, Oxford, 2024. 300 pp., 17 fig. b/w, 24 tables
Product Safety
Peter Lang Group AG

Biographical notes

Hasan Tinmaz (Volume editor) Seda Gökçe Turan (Volume editor)

Hasan Tinmaz, PhD, completed his undergraduate (2001) and graduate (2004) studies in education at Middle East Technical University. Now an Assistant Professor at Woosong University, South Korea, he specializes in social media, educational technology, AI, and the metaverse. His research interests focus on tech integration, curriculum design, and advancements in Industry 4.0. Seda Gökçe Turan, PhD, is an Assistant Professor in Early Childhood Education at Bahçes¸ehir University, Istanbul, with over 15+ years of experience in teaching, research, and consultancy. She earned her BA (2005, METU), MA (2012, Gazi University), and PhD (2016, Marmara University). Currently a visiting scholar at Bournemouth University, her research covers digital media literacy and cyber-harassment.

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