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Mathematics Education in the Age of Artificial Intelligence

How Artificial Intelligence can Serve Mathematical Human Learning

  • Highlights the contribution of artificial intelligence for mathematics education
  • Provides concrete ideas supported by mathematical work obtained through dynamic international collaboration
  • Discusses the development of new mathematics in the contemporary world

Part of the book series: Mathematics Education in the Digital Era (MEDE, volume 17)

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-xxiii
  2. Creation of AI Milieus to Work on Mathematics

    1. Front Matter

      Pages 1-2
    2. Automated Reasoning Tools with GeoGebra: What Are They? What Are They Good For?

      • Zoltán Kovács, Tomás Recio, M. Pilar Vélez
      Pages 23-44
    3. A Decision Making Tool for Mathematics Curricula Formal Verification

      • Eugenio Roanes-Lozano, Angélica Martínez-Zarzuelo
      Pages 77-88
    4. A Classification of Artificial Intelligence Systems for Mathematics Education

      • Steven Van Vaerenbergh, Adrián Pérez-Suay
      Pages 89-106
    5. AI and Mathematics Interaction for a New Learning Paradigm on Monumental Heritage

      • Álvaro Martínez-Sevilla, Sergio Alonso
      Pages 107-136
  3. AI-Supported Learning of Mathematics

    1. Front Matter

      Pages 137-139
    2. Using Didactic Models to Design Adaptive Pathways to Meet Students’ Learning Needs in an Online Learning Environment

      • Brigitte Grugeon-Allys, Françoise Chenevotot-Quentin, Julia Pilet
      Pages 141-165
    3. Experimental Study of Isoptics of a Plane Curve Using Dynamical Coloring

      • Thierry Dana-Picard, Zoltán Kovács
      Pages 231-250
    4. Teaching Programming for Mathematical Scientists

      • Jack Betteridge, Eunice Y. S. Chan, Robert M. Corless, James H. Davenport, James Grant
      Pages 251-276
  4. The present and future of AI in ME: Insight from empirical research

    1. Front Matter

      Pages 277-282
    2. CAS Use in University Mathematics Teaching and Assessment: Applying Oates’ Taxonomy for Integrated Technology

      • Daniel Jarvis, Kirstin Dreise, Chantal Buteau, Shannon LaForm-Csordas, Charles Doran, Andrey Novoseltsev
      Pages 283-317

About this book

This book highlights the contribution of artificial intelligence for mathematics education. It provides concrete ideas supported by mathematical work obtained through dynamic international collaboration, and discusses the flourishing of new mathematics in the contemporary world from a sustainable development perspective. 

Over the past thirty years, artificial intelligence has gradually infiltrated all facets of society. When it is deployed in interaction with the human designer or user, AI certainly raises new ethical questions. But as soon as it aims to augment intelligence in a kind of human-machine partnership, it goes to the heart of knowledge development and the very performance of work. The proposed themes and the sections of the book address original issues relating to the creation of AI milieus to work on mathematics, to the AI-supported learning of mathematics and to the coordination of « usual »  paper/pencil techniquesand « new » AI-aided educational working spaces. The authors of the book and the coordinators of each section are all established specialists in mathematics didactics, mathematics and computer science. In summary, this book is a must-read for everyone interested in the teaching and learning of mathematics, and it concerns the interaction between the human and the machine in both directions. It contains ideas, questions and inspiration that invite to take up the challenge of Artificial Intelligence contributing to Mathematical Human Learning.

Editors and Affiliations

  • Département de didactique, Université de Montréal, Montréal, Canada

    Philippe R. Richard

  • Departamento de Ingeniería Industrial, Universidad Antonio de Nebrija, Madrid, Spain

    M. Pilar Vélez

  • Departamento de Matemáticas, Estadística y Computación, Universidad de Cantabria, Santander, Spain

    Steven Van Vaerenbergh

About the editors

Philippe R. Richard is professeur titulaire (full professor) in the Département de didactique at the Université de Montréal. He is a specialist in didactics of mathematics and computer science. He has participated in and has led several major programs concerning didactics, mathematics and computer science. His current research activity extends the recent technological achievements of his research team in artificial intelligence. He is regularly invited to chair thematic groups (CERME, ICME) and to preside over symposia on mathematical work (ETM). He also gives research seminars and participates in the writing of synthesis texts and as editors for books. He has been a visiting professor at the Universitat Autònoma de Barcelona, the Université de Paris and the École Polytechnique de Montréal, and he is currently editor-in-chief of the journal Annales de didactique et de sciences cognitives (IREM, Université de Strasbourg).

M. Pilar Vélez is professor of applied mathematics at the Universidad Antonio de Nebrija (Madrid, Spain). She is member of the research group PID2020-113192GB-I00 (Mathematical Visualization: Foundations, Algorithms and Applications) from the Spanish MICINN.  She has been Rector of Universidad Antonio de Nebrija from 2010 to 2014. She authorship several scientific papers in different indexed journals and many scientific communications and conferences on topics as Real Algebraic Geometry, Computer Algebra, Automatic Reasoning in Dynamic Geometry and Mathematics Education. Now her research interest is focused in automatic reasoning in geometry, as well as algorithms, implementation and its applications to other fields as math education, linkages visualization and augmented reality. She has been organizer of international workshops, special sessions and conferences, as well as program committe (ACA,  CAGDME, ATCM, Maple Conference, Bienal RSME, RAAG). She has been a guest researcher at Università di Pisa, Louisiana State University,  Johannes Kepler University and at the University of Montreal. She has been invited to deliver lectures at the IHP of Paris, the University of Trento, the Eindhoven University of Technology, the Louisiana State University or the University of Pisa.

Steven Van Vaerenbergh is assistant professor in the Department of Mathematics, Statistics and Computing at Universidad de Cantabria (Spain). He has conducted research in artificial intelligence, co-authoring scientific publications on machine learning theory and multivariate statistics. Drawing upon this experience, his current research activity focuses on the applications of artificial intelligence in mathematics education, in particular on novel technological learning environments and automated systems to provide individualized learning experiences. He has co-authored several scientific papers on these topics, as well as publications on related subjects such as dynamic geometry systems. He hasparticipated in the organizing committees of international conferences and, in particular, he recently co-organized the Symposium on Artificial Intelligence for Mathematics Education (AI4ME).

Bibliographic Information

  • Book Title: Mathematics Education in the Age of Artificial Intelligence

  • Book Subtitle: How Artificial Intelligence can Serve Mathematical Human Learning

  • Editors: Philippe R. Richard, M. Pilar Vélez, Steven Van Vaerenbergh

  • Series Title: Mathematics Education in the Digital Era

  • DOI: https://doi.org/10.1007/978-3-030-86909-0

  • Publisher: Springer Cham

  • eBook Packages: Education, Education (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Hardcover ISBN: 978-3-030-86908-3Published: 10 March 2022

  • Softcover ISBN: 978-3-030-86911-3Published: 10 March 2023

  • eBook ISBN: 978-3-030-86909-0Published: 09 March 2022

  • Series ISSN: 2211-8136

  • Series E-ISSN: 2211-8144

  • Edition Number: 1

  • Number of Pages: XXIII, 450

  • Number of Illustrations: 76 b/w illustrations, 156 illustrations in colour

  • Topics: Mathematics Education, Artificial Intelligence, Teaching and Teacher Education, Machine Learning, Educational Psychology

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access