Monograph

Monograph contents

A list of sections and page ranges. Chapter text is not published on this site.

Front matter
Cover—–—
Publication details2–2
Preface3–5
Foreword6–11
Abstract12–13
Abbreviations and symbols14–15
Terminology and author information16–17
Contents in the original layout18–30
List of figures31–32
List of tables33–35
introduction

Introduction

36–427 pages
Chapter 01

Chapter 1. Paradigm shifts in engineering education and the role of the physics–mathematics core

43–519 pages
Chapter 02

Chapter 2. Changing didactic paradigms: from knowledge transfer to model building, design, and collaboration with AI

52–6817 pages
Chapter 03

Chapter 3. The Russian/Soviet model: regulatory hierarchy, the foundational core, and the transition to Engineering Thinking 4.0

69–8113 pages
Chapter 04

Chapter 4. The American model: ABET accreditation, outcomes-based education, and learning as an evidence system

82–9110 pages
Chapter 05

Chapter 5. The European model: the Bologna Process, ECTS/ESG, and engineering quality frameworks in the AI era

92–10413 pages
Chapter 06

Chapter 6. The Chinese model: New Engineering, the reform governance chain, and redesigning the core for digitalization and AI

105–11410 pages
Chapter 07

Chapter 7. Rebuilding the physics–mathematics core for Engineering Education 4.0

115–12713 pages
Chapter 08

Chapter 8. Teaching methods 4.0: designing learning experiences and the role of the teacher

128–16235 pages
Chapter 09

Chapter 9. Assessment and quality: proving understanding in the age of generative AI

163–18119 pages
Chapter 10

Chapter 10. An implementation roadmap for Engineering Education 4.0: from pilot to institutionalization

182–19514 pages
conclusion

Conclusion

196–2038 pages
Appendices
Appendix A. Research and coding protocol204–205
Appendix B. Artifact templates and evidence package206–207
Appendix C. Physics and mathematics module redesign template208–208
Appendix D. Assessment rubrics and AI-use protocol209–209
Appendix E. Pilot study protocol210–211
Appendix F. Minimum data and visualization catalog212–213
Appendix G. Workload and credit normalization214–216
Appendix H. Completed evidence package example217–219
Appendix I. Pilot data-analysis plan220–223
Appendix J. Codebook and content-analysis matrix for university AI policies224–228
Appendix K. Effectiveness and reproducibility calculation example229–232
Appendix L. Bank of AI-resistant tasks233–235
Appendix M. Governance of Core 4.0 implementation236–239
Appendix N. Core 4.0 teacher competencies240–242
References and bibliography243–269
Colophon—–—