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Generative AI Guidance Microsite provides resources and guidance to staff and students on the appropriate use of Generative AI in teaching and learning at MIC.
These guidelines cover a host of topics including:
Introduction to Generative Artificial Intelligence (GenAI)
Overview of the technologies’ possibilities and limitations
Outline of what acceptable use might look like for staff and students
Tips and guidance on how Generative AI can appropriately be incorporated in everyday use at MIC
Examples of Generative AI infringements
Considerations for grading in the context of GenAI
Glossary of key terms
These resources are intended to help staff and students navigate their use of Generative AI in a teaching and learning context
Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND)
This work is licensed under a CC BY-NC-ND license, permitting redistribution for non-commercial use with proper attribution but prohibiting modifications.
https://creativecommons.org/licenses/by-nc-nd/4.0/If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.
This case study outlines a first-year intervention at SETU Waterford using a timetabled weekly session to tackle common causes of academic failure such as time management, assessment planning. and study skills. It is intended for programme teams seeking practical, low-resource approaches to improving student progression and retention.
This OER presents findings from a comparative study of novice programmers engaging in face-to-face and hybrid pair programming. It explores collaboration patterns, role switching, satisfaction, and challenges, offering evidence-based insights for educators seeking to prepare students for effective teamwork in modern hybrid software development.
This OER explores novice programmers’ experiences of pair programming across face-to-face, hybrid, and remote settings. It provides insights into collaboration, role switching, satisfaction, and challenges, helping educators and students understand how to effectively prepare learners for modern hybrid software development environments.
This OER guides students through human-in-the-loop software development, demonstrating how AI tools can be effectively supervised, refined, and integrated across the Software Lifecycle. Designed for computing educators and learners, it combines agile practice, teamwork, DISC awareness, testing, and critical reflection on human–AI collaboration.
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