Handbook of artificial intelligence in education / edited by Benedict du Boulay, Antonija Mitrovic, Kalina Yacef.
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. 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.
Record details
- ISBN: 9781800375406 (hardcover)
- Physical Description: xviii, 678 pages : illustrations ; 25 cm.
- Publisher: Cheltenham : Edward Elgar Publishing, 2023.
- Copyright: ©2023
Content descriptions
Bibliography, etc. Note: | Includes bibliographical references and index. |
Formatted Contents Note: | Foreword -- Part I. Scene setting -- 1. Introduction / Benedict du Boulay, Antonija Mitrovic and Kalina Yacef -- 2. The history of artificial intelligence in education -- the first quarter century / Gordon McCalla -- Part II. Theories underpinning AIED -- 3. The role and function of theories in AIED / Stellan Ohlsson -- 4. Theories of metacognition and pedagogy applied to AIED systems / Roger Azevedo and Megan Wiedbusch -- 5. Theories of affect, meta-affect, and affective pedagogy / Ivon Arroyo, Kaśka Porayska-Pomsta and Kasia Muldner -- 6. Scrutable AIED / 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 / Vincent Aleven, Jonathan Rowe, Yun Huang and Antonija Mitrovic -- 8. Student modeling in open-ended learning environments / Cristina Conati and Sébastien Lallé -- 9. Six instructional approaches supported in AIED systems / 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 / Susanne Lajoie and Shan Li -- 11. Deeper learning through interactions with students in natural language / Vasile Rus, Andrew M. Olney and Arthur C. Graesser -- 12. Authoring tools to build AIED systems / Stephen Blessing, Stephen B. Gilbert and Steven Ritter -- Part IV. Analytics -- 13. Continuous student modeling for programming in the classroom: challenges, methods, and evaluation / 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 / Ken Holstein and Jennifer Olsen -- 15. Using learning analytics to support teachers / Stanislav Pozdniakov, Roberto Martinez-Maldonado, Shaveen Singh, Hassan Khosravi and Dragan Gasević -- 16. Predictive modeling of student success / Christopher Brooks, Vitomir Kovanović and Quan Nguyen -- 17. Social analytics to support engagement with learning communities / 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 / Alberto Casas-Ortiz, Jon Echeverria and Olga C. Santos -- 19. Artificial intelligence techniques for supporting face-to-face and online collaborative learning / Roberto Martinez-Maldonado, Anouschka van Leeuwen and Zachari Swiecki -- 20. Digital learning games in artificial intelligence in education (AIED): a review / Bruce M. McLaren and Huy A. Nguyen -- 21. Artificial intelligence-based assessment in education / Ying Fang, Rod D. Roscoe and Danielle S. McNamara -- 22. Evaluations with AIEd systems / Kurt VanLehn -- 23. Large-scale commercialization of AI in school-based environments / Steven Ritter and Kenneth R. Koedinger -- 24. Small-scale commercialisation: the golden triangle of AI EdTech / Rosemary Luckin and Mutlu Cukurova -- 25. Critical perspectives on AI in education: political economy, discrimination, commercialization, governance and ethics / Ben Williamson, Rebecca Eynon, Jeremy Knox and Huw Davies -- 26. The ethics of AI in education / Kaśka Porayska-Pomsta, Wayne Holmes and Selena Nemorin -- Part VI. The future -- 27. The great challenges and opportunities of the next 20 years -- 1. AIED and equity / Maria Mercedes T. Rodrigo -- 2. Engaging learners in the age of information overload / Julita Vassileva -- 3. Pedagogical agents for all: designing virtual characters for inclusion and diversity in STEM / H. Chad Lane -- 4. Intelligent textbooks / Peter Brusilovsky and Sergey Sosnovsky -- 5. AI-empowered open-ended learning environments in STEM domains / Gautam Biswas -- 6. Ubiquitous-AIED: pervasive AI learning technologies / James C. Lester -- 7. Culture, ontology and learner modeling / Riichiro Mizoguchi -- 8. Crowdsourcing paves the way for personalized learning / Ethan Prihar and Neil Heffernan -- 9. AIED in developing countries: breaking seven WEIRD assumptions in the global learning XPRIZE field study / Jack Mostow -- 10. The future of learning assessment / Claude Frasson -- 11. Intelligent mentoring systems: tapping into AI to deliver the next generation of digital learning / Vania Dimitrova -- Index. |
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Subject: | Artificial intelligence > Educational applications. |
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Location | Call Number / Copy Notes | Barcode | Shelving Location | Holdable? | Status | Due Date |
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The Pas Campus Library | LB 1028.43 .H363 2023 (Text) | 58500001256213 | Stacks | Volume hold | Available | - |