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This paper entitled 'Developing an Academic Integrity Policy and Academic Misconduct Procedures in an Era of Generative Artificial Intelligence: Five Tips for Success' may be of interest to policy developers and educators in further and higher education and training organisations as they adapt to challenge of AI.
This resource portal is dedicated to providing centralised access to policies, guidelines, and resources for teaching and learning in higher education in the context of generative artificial intelligence. The curated policies and frameworks offer authoritative guidance and practical support to inform and enhance institutional practice.
The following ‘ten considerations for generative AI adoption’ outline key issues identified through dialogue with stakeholders across Ireland’s higher education sector, industry, and associated agencies between September and December 2024
Y. Mormul, J. Przybyszewski, T. Siriburanon, J. Healy and P. Cuffe, “Gauging the Capability of Artificial Intelligence Chatbot Tools to Answer Textbook Coursework Exercises in Circuit Design Education”, presented at IEEE International Conference on IT in Higher Education and Training, Paris, France, November 2024
Y. Mormul, J. Przybyszewski, A. Nakoud and P. Cuffe, “Reliance on Artificial Intelligence Tools May Displace Research Skills Acquisition Within Engineering Doctoral Programmes: Examples and Implications”, presented at IEEE International Conference on IT in Higher Education and Training, Paris, France, November 2024
The HEART project explored the impact of generative AI on 3rd-level education in Ireland, using modules delivered in the UCD School of Biology and Environmental Science (SBES) at University College Dublin. We wish to thank the Strategic Alignment of Teaching and Learning Enhancement (SATLE) fund for making this project possible.
This project website aims to support students and teaching staff in UCD College of Arts and Humanities in navigating teaching, learning and assessment in the context of new developments in generative AI (e.g. OpenAI’s ChatGPT and Google Gemini).
AI is expected to bring about profound changes for the higher education sector, presenting numerous opportunities as well as serious and urgent challenges that must be addressed in the transition towards AI-driven systems. This chapter provides a Practical Guide targeted at higher education leaders, setting out actionable recommendations and steps that can be taken at an institutional level to adapt to AI in a responsible and ethical manner. The Practical Guide has been designed with HEIs in resource-constrained contexts in mind, but it is also intended to be flexible and responsive to a range of local/ global institutional and regulatory situations. It signals actions that affect internal capacity building, institutional governance, teaching, research, and community engagement. These actions also include specific recommendations on gender equality that can lead to transformation by addressing the root causes of gender inequalities.
This project explores the impact of AI text generation on 3rd-level education in Ireland, using modules delivered in the UCD School of Biology and Environmental Science (SBES) at University College Dublin. It was co-created by students and staff.
This Quick Start Guide introduces ChatGPT, an Artificial Intelligence (AI) tool that has taken the world by storm, reaching 100 million users just two months after being launched. The Quick Start Guide provides an overview of how ChatGPT works and explains how it can be used in higher education. Artificial Intelligence (AI) is a rapidly developing field. This guide is based on GPT-3.5, the latest free version of ChatGPT available at the time of writing. As well as dynamic changes in technology, the ethical implications of ChatGPT and other forms of AI are also swiftly advancing. Readers are advised to constantly check reliable sources for the latest news and updates.
The use of AI systems can potentially enhance teaching, learning and assessment, provide better learning outcomes and help schools to operate more efficiently. However, if those same AI applications are not properly designed or used carelessly, this could lead to harmful consequences. Educators need to be aware and ask questions whether AI systems they are using are reliable, fair, safe and trustworthy and that the management of educational data is secure, protects the privacy of individuals and is used for the common good. “Ethical AI” is used to indicate the development, deployment and use of AI that ensures compliance with ethical norms, ethical principles and related core values.
This recommendation approaches AI ethics as a systematic normative reflection, based on a holistic, comprehensive, multicultural and evolving framework of interdependent values, principles and actions that can guide societies in dealing responsibly with the known and unknown impacts of AI technologies on human beings, societies and the environment and ecosystems, and offers them a basis to accept or reject AI technologies. It considers ethics as a dynamic basis for the normative evaluation and guidance of AI technologies, referring to human dignity, well-being and the prevention of harm as a compass and as rooted in the ethics of science and technology.
This document sets out a detailed, values-led framework to support the ethical adoption of generative artificial intelligence (gen AI) in teaching and learning across Irish higher education. It builds on the HEA Generative AI Policy Framework by translating high-level principles into concrete provisions to guide institutional policy, governance and educational practice.
The principles address five core areas: academic integrity, equity and inclusion, critical engagement and AI literacy, privacy and data governance, and sustainable pedagogy. Together, they provide institutions with a practical reference for navigating the ethical, pedagogical and organisational challenges associated with generative AI, while safeguarding academic standards, student rights and institutional autonomy.
This policy framework provides national guidance for the responsible and values-based use of generative artificial intelligence (gen AI) in teaching and learning within Irish higher education. It is designed to support educators, academic leaders and professional staff in making informed decisions about the adoption and integration of gen AI technologies in educational practice.
The framework focuses specifically on teaching and learning, addressing issues such as academic integrity, assessment design, equity and inclusion, AI literacy, privacy and data governance, and sustainable pedagogy. It sets out five core principles to guide institutional policy development and practice, while allowing for local adaptation and institutional autonomy.
The report – Generative AI in Higher Education Teaching and Learning: Sectoral Perspectives – was commissioned as part of the Higher Education Authority’s evidence-led approach to policy development.
The report captures the views of staff, students, and leaders across the Irish higher education system on the opportunities and challenges posed by artificial intelligence.
It brings together insights from ten thematic focus groups and a leadership summit, involving over 80 participants from across Ireland’s higher education institutions, alongside student representatives and sectoral stakeholders.
This open course is designed to facilitate the development of your Artificial Intelligence (AI) literacy so that you can explore and innovate using Generative AI (GenAI) within your teaching, learning, and assessment practices.
In light of the potential opportunities and challenges of these technologies, this course will facilitate you in exploring the fundamentals of GenAI and AI Literacy, whilst focusing on an ethical practice. You will consider innovative ways in which you can respond to the challenges arising from the impact of these technologies in Higher Education.
Completion of this course will support you in developing a GenAI teaching strategy to apply to your own practice.
Student interns explaining how to use Artificial Intelligence in a way that upholds Academic Integrity.
This suite of short videos was create by our student interns in 2023. The videos are a useful resources for students and staff.
The topics covered include Academic Integrity resources at DkIT, Academic Integrity and Group Work, and Academic Integrity and Artificial Intelligence.
This suite of short videos was created by our student interns in 2023. The videos are a useful resource for students and staff. The topics covered include Academic Integrity resources at DkIT, Academic Integrity and Group Work, and Academic Integrity and Artificial Intelligence.
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.
A. Hickey, C. O’Faolain, J. Healy, K. Nolan, E. Doheny and P. Cuffe, “A Threat Assessment Framework for Screening the Integrity of University Assessments in the Era of Large Language Models”, presented at 8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, Lecco, Italy, September 2024