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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
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 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
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.
Comparing student and educator perceptions of generative artificial intelligence for teaching, learning and assessment: results from two institutional surveys
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
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.
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.
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 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).
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.
In this report we present a detailed examination of current AI use and considerations for its safe and ethical deployment. We conclude with horizon scanning and recommendations for educational establishments beginning to incorporate AI.
Authors
Dr James Ransom is a higher education specialist whose work looks at how universities can help adapt to and solve challenges facing society, including rapid technological change. He is an Honorary Senior Research Fellow at UCL Institute of Education, Head of Research at the National Centre for Entrepreneurship in Education (NCEE), and a Specialist Advisor on higher education to the European Bank for Reconstruction and Development. Previous work includes projects for the British Council, the Royal Society, and the British Academy, as well as jobs in policy at Universities UK, UNESCO, and the Association of Commonwealth Universities.
Dr Richard Whittle is an expert in the economics of Artificial Intelligence. He researches Artificial Intelligence and Human Decision-Making and has published in world-leading journals such as Work Employment and Society, Public Administration, and the Cambridge Journal of Economics. Richard led the technical research for the Greater Manchester Independent Prosperity Review, and he is an academic advisor to the Manchester Digital Strategy. Richard has received research funding from numerous sources, including the Economic and Social Research Council (ESRC), UK Research and Innovation (UKRI), Research England, and the Money Advice Service, and he has been the recipient of a personal Capabilities in Academic Policy Engagement (CAPE) fellowship hosted at the Institute of Innovation and Public Purpose, UCL.
Commissioned by the N-TUTORR National Digital Leadership Network.
This is a short introduction to ChatGPT for people teaching in higher education, created in January 2023 and updated until this version was saved in February 2023. The resource is a slide deck which you are free to modify and update (since this is a fast-moving topic). No prior knowledge of AI or chatbots is necessary to use the slides.
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 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.
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.
Digital Skills for Success in the Workplace is a five-unit, self-paced online course which equips learners with key digital literacy skills that are essential to study and work in rapidly evolving online environments.
This OER is targeted at lecturers and describes an inclusive framework to integrate artificial intelligence (AI) learning design at third level.
This self-directed resource has been designed to help students navigate and understand the basics of GenAI. Exploring the resource at their own pace will give students an opportunity to focus on understanding some fundamental GenAI concepts, while also considering the pros and cons of using GenAI in their studies.
This faculty guide aims to help educators navigate and understand GenAI’s potential role in higher education. Created for faculty who want to explore AI tools and their implications for teaching and learning, the resource allows educators to learn at their own pace about the opportunities and challenges of these technologies.
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
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.
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.
Artificial Intelligence (AI) technologies and related automated decision-making processes are becoming increasingly embedded in the tissue of digital societies. Their impact cuts across different political, social, economic, cultural, and environmental aspects of our lives. On the one hand, AI can be used to drive economic growth, enable smart and low-carbon cities, and optimize the management of scarce resources such as food, water and energy. On the other hand, AI can also be used in a manner that infringes on human rights and fundamental freedoms, such as freedom of expression and privacy, and risks exacerbating existing socioeconomic and gender inequalities. Furthermore, the implementation of AI systems may lead to values-driven dilemmas and complex problems, often requiring trade-offs that can only be addressed through broad societal consensus.
This guide focuses on the question of how the development of AI policies can be made inclusive. Multistakeholder approaches to policymaking are part of the answer because they create the space for learning, deliberation, and the development of informed solutions. They help decision makers consider diverse viewpoints and expertise, prevent capture by vested interests, and counteract polarization of policy discourse. A multistakeholder approach to AI policy development and the consultation of stakeholders from different backgrounds and expertise are necessary to be able to develop a relevant and applicable policy for the national context.
The objective of this guide is to support policymakers in ministries and parliaments in the design and implementation of inclusive AI policies, while empowering stakeholders including civil society, businesses, technical community, academia, media, and citizens, to participate in and influence these policy processes
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.
A video that discusses how Artificial Intelligence is impacting the way disinformation is created and spread to manipulate public opinion. It also outlines importance of Media Literacy education and regulatory measures, referencing Ireland’s Online Safety and Media Regulation Act and the EU’s Digital Services Act.
This horizon scanning report examines the evolving landscape of academic and institutional integrity in higher education. It traces the historical development of academic and institutional integrity concepts, analyses current international best practices, and forecasts future challenges and opportunities. The report highlights how technological advancements, globalization, and changing educational models have transformed the nature of academic misconduct and institutional responses. Key issues addressed include contract cheating, AI-generated content, and credential fraud. The study synthesizes insights from literature reviews and related documents to provide a comprehensive overview of innovative strategies employed by leading institutions worldwide. These range from integrity-focused curriculum design to generative artificial intelligence.
Authors
Sarah Elaine Eaton is a Professor and research chair at the Werklund School of Education at the University of Calgary (Canada). She is an award-winning educator, researcher, and leader. She leads transdisciplinary research teams focused on the ethical implications of advanced technology use in educational contexts. Dr. Eaton also holds a concurrent appointment as an Honorary Associate Professor, Deakin University, Australia.
Beatriz Antonieta Moya, Ph.D. in Educational Research from the University of Calgary, specializes in ethics, leadership in higher education, and artificial intelligence. Awarded the 2023 Outstanding Student Award by the European Network for Academic Integrity, her work focuses on the Scholarship of Teaching and Learning (SoTL) and fostering ethical practices. She has co-authored peer-reviewed publications on academic integrity policy and AI ethics in education and regularly leads workshops and presentations internationally, highlighting her commitment to promoting integrity in higher education through interdisciplinary research and leadership.
Commissioned by the N-TUTORR National Digital Leadership Network.
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.
UNESCO’s first global guidance on GenAI in education aims to support countries to implement immediate actions, plan long-term policies and develop human capacity to ensure a human-centred vision of these new technologies. The Guidance presents an assessment of potential risks GenAI could pose to core humanistic values that promote human agency, inclusion, equity, gender equality, and linguistic and cultural diversities, as well as plural opinions and expressions. It proposes key steps for governmental agencies to regulate the use of GenAI tools including mandating the protection of data privacy and considering an age limit for their use. It outlines requirements for GenAI providers to enable their ethical and effective use in education.
In the denouement of the COVID-19 pandemic, talk of a return to “normalcy” in higher education belies the great challenges and ongoing disruptions that yet lie ahead for many institutions. Public perceptions of the value of postsecondary education continue their downward slide, placing institutions in the position of having to demonstrate their worth and find solutions to declining enrollments. Data and analytics capabilities continue to evolve, introducing new opportunities and new risks to the institution. Chief among these capabilities, generative AI promises to change teaching and learning in ways many of us have yet to fully understand or prepare for.
For this year’s teaching and learning Horizon Report, expert panelists’ discussions highlighted and wrestled with these present and looming challenges for higher education. This report summarizes the results of those discussions and serves as one vantage point on where our future may be headed.
Recognizing the transformative potential of AI, the ICDE Quality Network has developed this report as a key initiative to explore its application in teaching and learning globally. This endeavour underscores the Network’s commitment to advancing quality education by promoting the responsible integration of AI.
While Generative AI technologies have existed for many years, recent rapid advances in the field have pushed these technologies into mainstream use across society. As higher education institutions grappled with these new technologies, initial responses focused on potentially significant threats to academic integrity. However, as our understandings have evolved, there is an increasing awareness that these developing technologies also present opportunities for teaching, learning, assessment and research in higher education.
Against this rapidly evolving backdrop, we in the Centre for Academic Practice (Trinity College Dublin) found ourselves faced with new challenges. How could we best support our educators to respond to the challenges of GenAI? How might we influence and support strategic initiatives and policy development regarding GenAI for teaching, learning and assessment at the institutional level? Conscious that our colleagues across the sector were facing similar challenges, we decided to initiate a cross-institutional collaboration with teaching and learning leaders from across the sector, where we could tackle this together!
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.
This GenAI Learning Hub was developed with students, for students, to support the responsible and effective use of generative AI. Topics are divided across three main sections to aid understanding of GenAI before use, during use, and in relation to assessment. While aimed at students, this resource will be useful to anyone using GenAI.
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 resource presents AVINA, an automated visual novel generator using large language models to transform multiple-choice questions into interactive learning narratives. Designed for educators and students, it supports gamified training in academic integrity and ethical decision-making through adaptive storytelling and experiential learning.
This lesson is designed to aid students in understanding how to engage generative AI in an academic setting without breaching academic integrity policy.
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.
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 study explores student perceptions and behaviours concerning academic integrity and the use of Generative AI in the context of Munster Technological University (MTU). It draws insights from a comprehensive survey of 608 students across various faculties and academic stages.
This guideline document seeks to support the implementation of MTU policies and procedures which underpin Academic Integrity and help to address the implications of Generative Artificial Intelligence on assessment practices.
The increasing digitalisation of higher education institutions brings with it a range of new opportunities and risks. This report draws on international examples and best practices to synthesise the typical challenges and provide insights into potential solutions. This includes examining existing practices in educational technology acquisition and management within the public education sector, including procurement practices and the shift towards outsourcing and SaaS services. From there new challenges are explored, such as responding to external forces, managing new forms of risk, balancing efficiencies with educational quality, and maintaining diverse educational technology portfolios.
Author
Anne-Marie Scott is an education consultant with international expertise in digital, online, and open education. She was Deputy Provost of Athabasca University (Canada), and previously at the University of Edinburgh (UK) where she led many major digital and open education initiatives. She serves as a member of the Government of British Columbia’s Digital Learning Advisory Committee and is the CFO (Treasurer) of the Open Source Initiative, the non-profit which stewards global definitions of open source software and open source artificial intelligence. She currently teaches critical approaches to educational technology as adjunct faculty at Royal Roads University (Canada).
Commissioned by the N-TUTORR National Digital Leadership Network.
The horizon-scanning report will provide a critical analysis of extant knowledge related to academic integrity as a commitment to six underpinning values of honesty, trust, fairness, respect, responsibility and courage (ICAI, 2021), guiding ethical behaviour across the tripartite domains of teaching, research and administration, and as impacted by rapidly evolving digital technologies, especially artificial intelligence (AI) tools. It will provide recommendations for university leaders navigating institutional best practice and policy for academic integrity in special reference to higher education’s digital transformation (McGill/JISC, 2023), and as germane to institutional and national strategic priorities for the Irish sector and, its community of technological universities.
Authors
Richard Watermeyer is Professor of Higher Education and Co-Director of the Centre for Higher Education Transformations at the University of Bristol. He is by training and orientation a sociologist of higher education; author of well over 100 academic articles, chapters, books and commissioned reports focused on policy and practice challenges and transformations in higher education; and the recipient of research funding for leadership of 19 (inter)national higher education research studies. Richard’s current research focus is on the sociological analyses of digital disruption in global higher education contexts. In this oeuvre he has acted as the Deputy Director of the (£1m) Digital Futures of Work programme (https://digitalfuturesofwork.com) and led an international research team into the effects of digital transitioning and AI adoption in global higher education. Such work has also featured in such analyses of the impacts of generative AI adoption by UK academic researchers (Watermeyer et al. 2024, forthcoming); in recent keynote addresses to the Research in Distance Education and E-Learning and Academic Practice and Technology conferences; and commentary pieces featured by Nature (https://www. nature.com/articles/d41586-024-00115-7) and the LSE (https://blogs.lse.ac.uk/impactofsocialsciences/2024/01/22/if-generative-ai-is-saving-academics-time-what-are-they-doing-with-it/).
Danielle Guizzo is Associate Professor in Economics Education and staff researcher of the Centre for Higher Education Transformations at the University of Bristol. Her research expertise is on the political economy of higher education and the state of academic labour and knowledge production in the light of technological and economic transformations, using a combination of historical and qualitative methods to understand change. Danielle has authored 25 academic articles, co-edited a book and has written several book chapters, reports, and briefs for policymakers. She was awarded the 2024 Clarence E. Ayres scholar award from the Association for Evolutionary Economics for her research on the ceremonialism of higher education from an economic-institutionalist perspective, and has secured research grants as a P-I on the impact of research assessment tools over economics research (funded by the ESRC Rebuilding Macroeconomics Initiative) and as a co-I on how academics have been using technologies in the Covid pandemic (funded by the Royal Economics Society). Danielle has also acted as a consultant for Brazil’s Ministry of Education on the review of Brazil’s national research assessment, and as an Advisory Board member of the Review of the Subject Benchmark Statement for Economics in the UK.
Lara Dzabolova is a PhD researcher at the School of Education at the University of Bristol. Previously, Lara led the Centre for Sustainable Development within the Department of Innovation at a local university in her hometown. Her work was focused on developing sustainability-centred curriculum and research with UN WTO and UN SDSN through digital learning and communication tools.
Commissioned by the N-TUTORR National Digital Leadership Network.
This report examines five key topics that are influencing new models of teaching and learning. The 2020 Covid-19 pandemic saw a significant shift to online learning and while this raised the profile of online education, the practice since then has been a return to the on campus model, although this has often led to reports of empty lecture halls as students continue to embrace the flexibility of hybrid models. Since 2022 the advent of Artificial Intelligence, in particular Large Language Models, has led to considerable reflection in higher education on the use of essays and exams in assessment and how to best incorporate these tools into teaching. The impact of these two factors, the pandemic and AI, place Higher Education Institutions (HEIs) in the position of having to satisfy their current student base, with an economic model largely constructed around the physical campus, while also developing models that will provide robust and flexible models for students in the future.
Author
Martin Weller is Emeritus Professor of Educational Technology, at the Open University. He is the former Chair of the Open Programme, the Open University’s flexible, multidisciplinary degree, and Director of the GO-GN, a global network of Doctoral students in the area of open education. He developed the OU’s first fully online course in 1999, which attracted over 15,000 students annually. He is the author of the books The Digital Scholar, 25 Years of Ed Tech and Metaphors of Ed Tech.
He maintains a popular blog at blog.edtechie.net
Commissioned by the N-TUTORR National Digital Leadership Network.
This OER introduces students to designing and developing AI-powered assistants for agile software development using Flowise (no code). Learners as a team explore Retrieval Augmented Generation (RAG) and agent-based systems, applying AI to real-world agile practices while considering technical design, evaluation, and cost-aware decision-making
This report draws on Patricia Gibson’s research around critical approaches to Artificial Intelligence (AI) in Education and the increasing automation of Educational Technologies (EdTech).
Ireland’s Higher Education Authority (HEA) has been working with the sector to move from immediate responses to generative AI towards a more shared understanding of its implications for teaching and learning. This includes how students learn, how educators teach and how institutions approach assessment, integrity and inclusion. The HEA has brought together student representatives, staff, institutional leaders and wider stakeholders to consider how GenAI is influencing teaching, learning and assessment and what kinds of support, guidance and shared understanding are needed.
Speaker
Colin Lowry is Senior Manager for Teaching and Learning, Enhancement and Digital Innovation at Ireland’s Higher Education Authority. His work spans digital transformation, artificial intelligence, open education, professional development and education for sustainable development. He contributes to national teaching and learning initiatives, including Ireland’s National Resource Hub for Open Educational Resources, OpenCourses.ie and related professional development and recognition programmes. Colin has been closely involved in the Ireland’s national response on generative AI in higher education, supporting sectoral consultation, evidence-informed guidance and national dialogue on its implications for teaching, learning and assessment. His previous work includes research on technology acceptance and advisory roles in digital strategy, service design, change management and technology adoption.