Beställningsvara. Skickas inom 7-10 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.
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.
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
Contents:Foreword xiiPART I SCENE SETTING1 Introduction 2Benedict du Boulay, Antonija Mitrovic and Kalina Yacef2 The history of artificial intelligence in education – the first quarter century 10Gordon McCallaPART II THEORIES UNDERPINNING AIED3 The role and function of theories in AIED 31Stellan Ohlsson4 Theories of metacognition and pedagogy applied to AIED systems 45Roger Azevedo and Megan Wiedbusch5 Theories of affect, meta-affect, and affective pedagogy 68Ivon Arroyo, Kaśka Porayska-Pomsta and Kasia Muldner6 Scrutable AIED 101Judy Kay, Bob Kummerfeld, Cristina Conati, Kaśka Porayska-Pomsta and Ken HolsteinPART III THE ARCHITECTURE AND DESIGN OF AIED SYSTEMS7 Domain modeling for AIED systems with connections to modeling student knowledge: a review 127Vincent Aleven, Jonathan Rowe, Yun Huang and Antonija Mitrovic8 Student modeling in open-ended learning environments 170Cristina Conati and Sébastien Lallé9 Six instructional approaches supported in AIED systems 184Vincent Aleven, Manolis Mavrikis, Bruce M. McLaren, Huy A. Nguyen, Jennifer Olsen and Nikol Rummel10 Theory-driven design of AIED systems for enhanced interaction and problem-solving 229Susanne Lajoie and Shan Li11 Deeper learning through interactions with students in natural language 250Vasile Rus, Andrew M. Olney and Arthur C. Graesser12 Authoring tools to build AIED systems 273Stephen Blessing, Stephen B. Gilbert and Steven RitterPART IV ANALYTICS13 Continuous student modeling for programming in the classroom: challenges, methods, and evaluation 287Ye Mao, Samiha Marwan, Preya Shabrina, Yang Shi, Thomas W. Price, Min Chi and Tiffany Barnes14 Human–AI co-orchestration: the role of artificial intelligence in orchestration 309Ken Holstein and Jennifer Olsen15 Using learning analytics to support teachers 322Stanislav Pozdniakov, Roberto Martinez-Maldonado, Shaveen Singh, Hassan Khosravi and Dragan Gašević16 Predictive modeling of student success 350Christopher Brooks, Vitomir Kovanović and Quan Nguyen17 Social analytics to support engagement with learning communities 370Carolyn Rosé, Meredith Riggs and Nicole BarbaroPART V AIED SYSTEMS IN USE18 Intelligent systems for psychomotor learning: A systematic review and two cases of study 390Alberto Casas-Ortiz, Jon Echeverria and Olga C. Santos19 Artificial intelligence techniques for supporting face-to-face and online collaborative learning 422Roberto Martinez-Maldonado, Anouschka van Leeuwen and Zachari Swiecki20 Digital learning games in artificial intelligence in education (AIED): a review 440Bruce M. McLaren and Huy A. Nguyen21 Artificial intelligence-based assessment in education 487Ying Fang, Rod D. Roscoe and Danielle S. McNamara22 Evaluations with AIEd systems 507Kurt VanLehn23 Large-scale commercialization of AI in school-based environments 526Steven Ritter and Kenneth R. Koedinger24 Small-scale commercialisation: the golden triangle of AI EdTech 539Rosemary Luckin and Mutlu Cukurova25 Critical perspectives on AI in education: political economy, discrimination, commercialization, governance and ethics 555Ben Williamson, Rebecca Eynon, Jeremy Knox and Huw Davies26 The ethics of AI in education 573Kaśka Porayska-Pomsta, Wayne Holmes and Selena NemorinPART VI THE FUTURE27 The great challenges and opportunities of the next 20 years 6081. AIED and equity 608Maria Mercedes T. Rodrigo2. Engaging learners in the age of information overload 610Julita Vassileva3. Pedagogical agents for all: designing virtual characters for inclusion and diversity in STEM 613H. Chad Lane4. Intelligent textbooks 616Peter Brusilovsky and Sergey Sosnovsky5. AI-empowered open-ended learning environments in STEM domains 620Gautam Biswas6. Ubiquitous-AIED: pervasive AI learning technologies 626James C. Lester7. Culture, ontology and learner modeling 629Riichiro Mizoguchi8. Crowdsourcing paves the way for personalized learning 632Ethan Prihar and Neil Heffernan9. AIED in developing countries: breaking seven WEIRD assumptions in the global learning XPRIZE field study 635Jack Mostow10. The future of learning assessment 639Claude Frasson11. Intelligent mentoring systems: tapping into AI to deliver the next generation of digital learning 642Vania DimitrovaIndex 653
‘I highly recommend the book as a comprehensive resource on AIED. It provides valuable insights and cross-references across chapters, with a well-structured approach that guides readers from historical context and theoretical frameworks to technological foundations, practical applications, and forward-looking reflections. Readers can also explore individual chapters for in-depth knowledge on specific topics. Each chapter is thoroughly supported by a wide range of sources, making the book a useful guide to further resources in EdTech, pedagogy, and psychology.’