This book presents the first practice-based account of Generative AI (GenAI) integration in postgraduate courses, structured across three approaches: course redesign and delivery, assessment redesign, and evaluation adaptations. The book introduces GenAI as a knowledge collaborator and reports the practical approaches, such as redesigning group activities into applied, research-driven tasks, providing detailed GenAI usage instructions, and requiring acknowledgement and reporting tools such as AI Contribution Forms, GenAI Integration Rubrics, and AI Contribution Assessment Forms, while adapting evaluation rubrics to ensure that the technology cannot act as a substitute for student work. Through guided experimentation in these areas, students were able to explore GenAI’s capabilities and limitations, reflect on appropriate and inappropriate use cases, and strengthen their digital literacy, reflective synthesis, and ethical awareness.A rigorous Monitoring & Evaluation (M&E) framework, built on a Theory of Change, pretested survey instruments, and detailed research protocols, was used to assess impacts on student knowledge, confidence, application, and awareness, both in the short term and the medium term. All instruments and procedures are included, making them directly reusable or adaptable by peers seeking to replicate or scale similar interventions in their courses.This book is a practical and methodological resource for educators and institutions, offering tested integration strategies, ready-to-use instruments, and a replicable evaluation framework to embed GenAI responsibly and effectively into academic practice while safeguarding academic integrity.

This book presents the first practice-based account of Generative AI (GenAI) integration in postgraduate courses, structured across three approaches: course redesign and delivery, assessment redesign, and evaluation adaptations. The book introduces GenAI as a knowledge collaborator and reports the practical approaches, such as redesigning group activities into applied, research-driven tasks, providing detailed GenAI usage instructions, and requiring acknowledgement and reporting tools such as AI Contribution Forms, GenAI Integration Rubrics, and AI Contribution Assessment Forms, while adapting evaluation rubrics to ensure that the technology cannot act as a substitute for student work. Through guided experimentation in these areas, students were able to explore GenAI’s capabilities and limitations, reflect on appropriate and inappropriate use cases, and strengthen their digital literacy, reflective synthesis, and ethical awareness.A rigorous Monitoring & Evaluation (M&E) framework, built on a Theory of Change, pretested survey instruments, and detailed research protocols, was used to assess impacts on student knowledge, confidence, application, and awareness, both in the short term and the medium term. All instruments and procedures are included, making them directly reusable or adaptable by peers seeking to replicate or scale similar interventions in their courses.This book is a practical and methodological resource for educators and institutions, offering tested integration strategies, ready-to-use instruments, and a replicable evaluation framework to embed GenAI responsibly and effectively into academic practice while safeguarding academic integrity.

This book presents the first practice-based account of Generative AI (GenAI) integration in postgraduate courses, structured across three approaches: course redesign and delivery, assessment redesign, and evaluation adaptations. The book introduces GenAI as a knowledge collaborator and reports the practical approaches, such as redesigning group activities into applied, research-driven tasks, providing detailed GenAI usage instructions, and requiring acknowledgement and reporting tools such as AI Contribution Forms, GenAI Integration Rubrics, and AI Contribution Assessment Forms, while adapting evaluation rubrics to ensure that the technology cannot act as a substitute for student work. Through guided experimentation in these areas, students were able to explore GenAI’s capabilities and limitations, reflect on appropriate and inappropriate use cases, and strengthen their digital literacy, reflective synthesis, and ethical awareness.A rigorous Monitoring & Evaluation (M&E) framework, built on a Theory of Change, pretested survey instruments, and detailed research protocols, was used to assess impacts on student knowledge, confidence, application, and awareness, both in the short term and the medium term. All instruments and procedures are included, making them directly reusable or adaptable by peers seeking to replicate or scale similar interventions in their courses.This book is a practical and methodological resource for educators and institutions, offering tested integration strategies, ready-to-use instruments, and a replicable evaluation framework to embed GenAI responsibly and effectively into academic practice while safeguarding academic integrity.