Overview

Gathering insightful and stimulating contributions from leading global experts in Artificial Intelligence in Education (AIED), this comprehensive Handbook traces the development of AIED from its early foundations in the 1970s to the present day. The Handbook evaluates the use of AI techniques such as modelling in closed and open domains, machine learning, analytics, language understanding and production to create systems aimed at helping learners, teachers, and educational administrators. Chapters examine theories of affect, metacognition and pedagogy applied in AIED systems; foundational aspects of AIED architecture, design, authoring and evaluation; and collaborative learning, the use of games and psychomotor learning. It concludes with a critical discussion of the wider context of Artificial Intelligence in Education, examining its commercialisation, social and political role, and the ethics of its systems, as well as reviewing the possible challenges and opportunities for AIED in the next 20 years. Providing a broad yet detailed account of the current field of Artificial Intelligence in Education, researchers and advanced students of education technology, innovation policy, and university management will benefit from this thought-provoking Handbook. Chapters will also be useful to support undergraduate courses in AI, computer science, and education.

Full Product Details

Author:   Benedict du Boulay ,  Antonija Mitrovic ,  Kalina Yacef
Publisher:   Edward Elgar Publishing Ltd
Imprint:   Edward Elgar Publishing Ltd
ISBN:  

9781800375406

ISBN 10:   1800375409
Pages:   696
Publication Date:   28 April 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Contents: Foreword xii PART I SCENE SETTING 1 Introduction 2 Benedict du Boulay, Antonija Mitrovic and Kalina Yacef 2 The history of artificial intelligence in education – the first quarter century 10 Gordon McCalla PART II THEORIES UNDERPINNING AIED 3 The role and function of theories in AIED 31 Stellan Ohlsson 4 Theories of metacognition and pedagogy applied to AIED systems 45 Roger Azevedo and Megan Wiedbusch 5 Theories of affect, meta-affect, and affective pedagogy 68 Ivon Arroyo, Kaśka Porayska-Pomsta and Kasia Muldner 6 Scrutable AIED 101 Judy Kay, Bob Kummerfeld, Cristina Conati, Kaśka Porayska-Pomsta and Ken Holstein PART III THE ARCHITECTURE AND DESIGN OF AIED SYSTEMS 7 Domain modeling for AIED systems with connections to modeling student knowledge: a review 127 Vincent Aleven, Jonathan Rowe, Yun Huang and Antonija Mitrovic 8 Student modeling in open-ended learning environments 170 Cristina Conati and Sébastien Lallé 9 Six instructional approaches supported in AIED systems 184 Vincent Aleven, Manolis Mavrikis, Bruce M. McLaren, Huy A. Nguyen, Jennifer Olsen and Nikol Rummel 10 Theory-driven design of AIED systems for enhanced interaction and problem-solving 229 Susanne Lajoie and Shan Li 11 Deeper learning through interactions with students in natural language 250 Vasile Rus, Andrew M. Olney and Arthur C. Graesser 12 Authoring tools to build AIED systems 273 Stephen Blessing, Stephen B. Gilbert and Steven Ritter PART IV ANALYTICS 13 Continuous student modeling for programming in the classroom: challenges, methods, and evaluation 287 Ye Mao, Samiha Marwan, Preya Shabrina, Yang Shi, Thomas W. Price, Min Chi and Tiffany Barnes 14 Human–AI co-orchestration: the role of artificial intelligence in orchestration 309 Ken Holstein and Jennifer Olsen 15 Using learning analytics to support teachers 322 Stanislav Pozdniakov, Roberto Martinez-Maldonado, Shaveen Singh, Hassan Khosravi and Dragan Gašević 16 Predictive modeling of student success 350 Christopher Brooks, Vitomir Kovanović and Quan Nguyen 17 Social analytics to support engagement with learning communities 370 Carolyn Rosé, Meredith Riggs and Nicole Barbaro PART V AIED SYSTEMS IN USE 18 Intelligent systems for psychomotor learning: A systematic review and two cases of study 390 Alberto Casas-Ortiz, Jon Echeverria and Olga C. Santos 19 Artificial intelligence techniques for supporting face-to-face and online collaborative learning 422 Roberto Martinez-Maldonado, Anouschka van Leeuwen and Zachari Swiecki 20 Digital learning games in artificial intelligence in education (AIED): a review 440 Bruce M. McLaren and Huy A. Nguyen 21 Artificial intelligence-based assessment in education 487 Ying Fang, Rod D. Roscoe and Danielle S. McNamara 22 Evaluations with AIEd systems 507 Kurt VanLehn 23 Large-scale commercialization of AI in school-based environments 526 Steven Ritter and Kenneth R. Koedinger 24 Small-scale commercialisation: the golden triangle of AI EdTech 539 Rosemary Luckin and Mutlu Cukurova 25 Critical perspectives on AI in education: political economy, discrimination, commercialization, governance and ethics 555 Ben Williamson, Rebecca Eynon, Jeremy Knox and Huw Davies 26 The ethics of AI in education 573 Kaśka Porayska-Pomsta, Wayne Holmes and Selena Nemorin PART VI THE FUTURE 27 The great challenges and opportunities of the next 20 years 608 1. AIED and equity 608 Maria Mercedes T. Rodrigo 2. Engaging learners in the age of information overload 610 Julita Vassileva 3. Pedagogical agents for all: designing virtual characters for inclusion and diversity in STEM 613 H. Chad Lane 4. Intelligent textbooks 616 Peter Brusilovsky and Sergey Sosnovsky 5. AI-empowered open-ended learning environments in STEM domains 620 Gautam Biswas 6. Ubiquitous-AIED: pervasive AI learning technologies 626 James C. Lester 7. Culture, ontology and learner modeling 629 Riichiro Mizoguchi 8. Crowdsourcing paves the way for personalized learning 632 Ethan Prihar and Neil Heffernan 9. AIED in developing countries: breaking seven WEIRD assumptions in the global learning XPRIZE field study 635 Jack Mostow 10. The future of learning assessment 639 Claude Frasson 11. Intelligent mentoring systems: tapping into AI to deliver the next generation of digital learning 642 Vania Dimitrova Index 653

Reviews

'The Handbook of Artificial Intelligence in Education is a great resource for people studying the field of AI and data-directed education, which is a complex tapestry, with many different elements feeding into its design and development. The Handbook supports readers to experience the full tapestry and to pull out and examine individual threads, without losing the underlying purpose. The field has grown tremendously in the past 30 years. Intelligent tutors now listen to and speak to learners, model student expertise and knowledge, examine theories (about how humans learn, think, collaborate and socialize), and support classroom orchestration, learning at scale, assessment, and human-machine interaction. The Handbook nicely documents progress in the field without overwhelming a new generation of AIED researchers.' -- Beverly Woolf, author of Building Intelligent Interactive Tutors and and faculty at the University of Massachusetts, Amherst, US 'This is a really great Handbook written by some of the most well known authors in the field of Artificial Intelligence in Education (AIED). It describes both the most important topics and future trends in a very comprehensive way for a wide range of stakeholders.' -- Cristobal Romero, University of Cordoba, Spain

'This is a really great Handbook written by some of the most well known authors in the field of Artificial Intelligence in Education (AIED). It describes both the most important topics and future trends in a very comprehensive way for a wide range of stakeholders.' -- Cristobal Romero, University of Cordoba, Spain

Author Information

Edited by Benedict du Boulay, Emeritus Professor of Artificial Intelligence, University of Sussex, UK, Antonija Mitrovic, Professor, Department of Computer Science and Software Engineering, University of Canterbury, New Zealand and Kalina Yacef, Associate Professor of Computer Science, University of Sydney, Australia

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