Toolkit for the Ethical Use of GenAI in Learning and Teaching

[favorite_button]

Description

The Toolkit includes an introduction to generative AI and lexicon of terms, guidelines for ethical use, recommended adjustments to common modes of assessment to mitigate against the potential risk of unethical use, and discipline-specific case studies of good practice that share innovative forms of learning, teaching and/or assessment.

Benefit of this resource and how to make the best use of it

This toolkit has been specifically designed to assist staff in considering the ethical integration of Generative Artificial Intelligence (GenAI) into their learning and teaching practices, including case studies from across disciplinary contexts. By exploring this toolkit, staff will gain a solid understanding of GenAI and its potential applications and challenges in the field of education. Moreover, the content can be directly utilised by staff to educate and inform students about GenAI and the importance of ethical use.

Creative Commons Attribution-NonCommercial (CC BY-NC)

This work is licensed under a CC BY-NC license, permitting sharing and adaptation for non-commercial purposes with proper attribution.

https://creativecommons.org/licenses/by-nc/4.0/
? This citation is automatically generated and may require adjustment. Always verify it against your style guide.
Goff, L., & Dennehy, T. (10/04/2024). Toolkit for the ethical use of genai in learning and teaching. National Resource Hub (Ireland). Retrieved from: https://hub.teachingandlearning.ie/resource/toolkit-for-the-ethical-use-of-genai-in-learning-and-teaching/ License: Creative Commons Attribution-NonCommercial (CC BY-NC).

Adapting this resource? Share your version!

If you have modified or adopted this resource, share your version here. Tracking adaptations helps us measure impact and connects others with useful updates.

Related OER

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 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.