Handbook of Artificial Intelligence in Higher Education: (Elgar Handbooks in Education)

Table of Contents:
Contents Introduction: Rethinking higher education in the Age of AI 1 Stefan Popenici, Jürgen Rudolph, Fadhil Ismail and Shannon Tan PART I AI AND HIGHER EDUCATION: THE BIG PICTURE 1 Imagining the AI-powered university of today and tomorrow 17 Peter Waring 2 Charting an AI course: A framework for higher education strategy development 30 Rose Luckin and Ant Bagshaw 3 A human–AI co-generative framework for higher education 54 Bron Eager, Mitch Parsell and Toby Newstead 4 Conceptualising artificial intelligence as an apprentice 67 Joseph Crawford, Michael Cowling and Kelly-Ann Allen 5 Generative AI tools in academic research: applications and implications for qualitative and quantitative research methodologies 76 Mike Perkins andJasper Roe 6 The use of artificial intelligence in higher education 92 Ebrahim Mohammadkarimi 7 AI technologies and university admission systems 107 Jim Faherty 8 AI in open and distance learning 120 Mehmet Firat Firat PART II TOWARDS A CRITICAL AI LITERACY 9 Analysing modern slavery statements using large language models 134 Ser-Huang Poon, Eghbal Rahimikia, Philip Jobi Vallavanthra and Siliang Wei 10 The hidden labour in AI: Big Tech’s dirty secret and the need for critical AI literacy in higher education 152 Jürgen Rudolphvi Handbook of artificial intelligence in higher education 11 AI in our common future: AI for sustainability education beyond the Anthropocene 167 Eunice Tan 12 AI and bias: Parallels and paradoxes 182 Fadhil Ismail 13 The rise of AI: threat to graduate attributes 201 Kelum A. A. Gamage and Shyama C. P. Dehideniya 14 The impact of AI on inclusive learning communities 218 Rachel Forsyth, Claire Hamshire, Kevwe Olomu and Elizabeth King 15 AI and disability in higher education 230 Sharon Kerr and Stefan Popenici 16 Leveraging AI for neurodiversity inclusion in tertiary education 243 Rachel van Gorp and Glenys Ker 17 AI in higher education as a catalyst for positive societal transformation and inclusivity 259 Maylyn Tan and Laura Visser Kaldenbach 18 AI at the crossroads: Between the free play of forces, regulation, and control? Dispositives of Artificial Intelligence governance and discursive organizing in higher education 276 Susanne Maria Weber and Marc-André Heidelmann PART III TEACHING, LEARNING ASSESSMENT 19 “Is that all there is?” Work-integrated learning educators meet GenAI: upskilling journeys to “‘the deep end”’ 300 Martin Andrew and Beate Mueller 20 AI-powered pedagogy: Transforming education in the Digital Age 315 Diane Kalendra, Sumesh Nair, Mingwei Sun, Tareq Rasul, Wagner Junior Ladeira and Fernando de Oliveira Santini 21 Chalkboards to chatbots: A paradigm shift in teaching and learning 330 Augustine Osamor Ifelebuegu 22 Rethinking learning in the era of artificial intelligence 344 Khalid A. Khan 23 AI pedagogy: Navigating doctoral education with AI-integrated teaching and learning 361 Weina Li Chen and Samaa Haniya 24 Collusion, plagiarism, or contract cheating? How generative AI fits into existing academic integrity policies 372 Miriam Sullivan 25 The modernisation of assessment in HE: AI as a disruptive catalyst for change 387 Athanasios Hassoulas 26 Ethical and technological considerations for teaching with and about AI programs in higher education 403 Laura Dumin 27 Level up: Adaptive AI in serious gaming for training and assessment 416 Kevin Yi-Lwern Yap, William Siew and Bina Rai PART IV WORK AND EMPLOYABILITY 28 The rise of generative AI: Implications for work and learning 442 Samson Tan 29 AI and employability: Transitioning from Google to GenAI 460 Michael Choy 30 Artificial intelligence in day-to-day professional practice: implications for higher education 474 Margaret Bearman, Sarah Howard and Sarah Caouette Sarah Caouette 31 Empowering adult learners using Generative AI: Unveiling the six essential pillars 487 Michael Agyemang Adarkwah PART V DISCIPLINE- AND COUNTRY-SPECIFIC STUDIES 32 Implementing AI technologies in various business subjects 502 Nurhafiz Noor, Lance DuBos, Sook Rei Tan and Kim-Lim Tan 33 AI-assisted language education within Chinese higher education: a systematic review of the literature 2000–2024 515 Junmin Xiao and Fiona Xiaofei Tang 34 Exploring student perspectives on AI in higher education: A multidisciplinary analysis 534 Sin Manw Sophia Lam, Wai Yin Koey Chung, Wing Tung Michelle Cheng and Gary Cheng 35 AI applications in initial teacher education: A systematic mapping review 548 Melissa Bond, Emily Oxley and Lydia Lymperis 36 Responses of Japanese university and college teachers to the rise of generative AI: Analysis of 2023 and 2024 syllabi 574 Takeru Mashino 37 AI’s transformative impact on teacher education: Enhancing in-service and pre-service training 595 Lucas Kohnke 38 Artificial intelligence and higher education in Türkiye 608 Begum Burak 39 Spotlight on emerging AI trends in international universities in the UAE 623 Faiza Qureshi and Eugene Pribytkov

About the Author :
Edited by Stefan Popenici, AI Researcher, Jürgen Rudolph, Murdoch University, Fadhil Ismail, Senior Lecturer, Kaplan Higher Education Academy and Shannon Tan, Lecturer, Kaplan Higher Education Academy, Singapore

Review :
‘AI will disrupt higher education. If you want to gain a solid understanding of the implications and take advantage of the opportunities AI offers to higher education, this book is for you!’ ‘In an era where AI risks deepening social inequality, this Handbook stands as a call for critical engagement. By bringing together multiple voices from around the world, it envisions a progressive, inclusive higher education future—one that rejects corporate-driven AI hype and champions equity, transparency, and collective empowerment.’ ‘A tour de force in critical AI discourse, this Handbook fuses deep scholarship with global case studies to examine both the urgency and promise of AI in higher education. With candour and insight, it equips all stakeholders with the means to shape a more ethical, inclusive, and forward-looking academic future.’ ‘Uniting insights from authors across all continents, this Handbook offers a sweeping panorama of AI’s disruptive promise and peril in higher education. Its collective call for ‘critical AI literacy’ stands as a must-heed imperative for universities facing rapid technological upheaval.’ ‘A refreshingly candid and deeply researched volume, this Handbook transcends techno-utopian hype to deliver a necessary call to action. By laying bare AI’s hidden labour, biases, and transformative potential, it offers educators, policymakers, and innovators the critical and forward-thinking blueprint higher education urgently needs.’ ‘If you’re ready to wake the edufactory from its AI-induced slumber, read this book, and read it well. It is filled with unsettling truths, the very ones failing to engage with poses the greatest risks. Essential to developing the critical AI literacy the present situation demands.’ ‘With forty chapters contributed by 76 authors spanning all continents, this Handbook presents a truly global mosaic of diverse perspectives on AI in higher education. It forcefully advocates for ‘critical AI literacy,’ urging readers to question assumptions and champion more ethical, reflective engagement with these transformative technologies.’ ‘With forty meticulously curated chapters, this global compendium transcends the biased and manipulative narratives about AI by spotlighting the voices of practitioners and scholars worldwide. Its unflinching advocacy for a “critical AI literacy” ushers in a new era of deeper engagement and ethical accountability in academe.’ ‘Addressing the unique opportunities and constraints of higher education, this volume underscores the vital need to examine AI through ethical, cultural, and socio-economic lenses. Its wealth of perspectives from 76 contributors— including those from Africa—provides a transformative vision of equitable AI adoption on our continent and beyond.’