The rapid emergence of Generative Artificial Intelligence (GAI) has introduced a transformative age of technology, gaining prominent attention in higher education. This mixed-methods case study examines the applications of GAI, and how it is understood, applied, and managed within an Irish Technological University. By focusing on lecturers’ professional and personal engagement with GAI, the research provides insight into how this technology is shaping academic practice, providing valuable insights for researchers and policymakers, including its challenges and potential to add value to teaching experiences.

Key findings reveal a continuum of responses and experiences, ranging from resistance to optimism among educators. Instead of viewing these reactions solely through the lens of technology acceptance, we have applied change management theories as a framework to better capture the nuance and complexity of staff responses. To this end, the presentation provides an opportunity to introduce a heuristic device that combines Kotter’s 8-Step Model with Kübler-Ross’ Change Curve, offering a way to capture participant perspectives on GenAI.

This research highlights the importance of proactive and empathetic change management and AI-informed teaching methods, providing recommendations for HEIs seeking to navigate the pedagogical, ethical, and institutional implications of GAI adoption.

This study was undertaken to highlight the ecological implications of EdTEch, the excessive nature of modern digital technology, to examine the need for sustainable practices in the ICT sector and education's involvement therein. The environmental impact of EdTech remains an underexamined consequence of the use of digital technology in education contexts, one that is not often considered among known issues of digital education. This impact is growing exponentially with the presence of Artificial Intelligence in the sector. The selection and adoption of EdTech tools is deeply influenced by institutional policies and governance, which have remits to reduce ecological impact and carbon footprint, but rarely consider digital technology and EdTech as part of the harmful contributors. Understanding and addressing these interconnected challenges is critical for aligning EdTech with planetary and social equity goals. The study follows a "possible action structure" used by Neil Selwyn that considers “business as usual”, “greening” EdTech, and “burning it to the ground” to critically analyze the sustainability claims and practices within the EdTech sector. Actionable insights are drawn from the empirical examination of case studies; selected socio-technical educational practices, in which computing technologies are embroiled, including solar-powered websites, self-hosted systems, and upcycled hardware infrastructures. The outcomes of the research identify practical strategies, for people to come together and directly counter EdTech’s environmental footprint. The research uses an exploratory case study methodology, and a theoretical framework which is directly influenced by the principles of ecojustice and permacomputing. These perspectives provide a lens for evaluating the ecological, social, and cultural dimensions of EdTech and for proposing sustainable alternatives. The study situates EdTech within broader socio-political and cultural contexts, contributing to critical debates on its future. By connecting the critical analysis with possible solutions, it opens avenues for constructive dialogue on aligning digital education with ecological responsibility, aiming to offer critical insights for policymakers, educators, and technologists.

This study explores the changing digital experiences of students in an Irish Higher Education Institution, building on the findings of the 2019 INDEx (Irish National Digital Experience) survey, and aligned with an Erasmus+ project on supporting educators' digital competencies (CUTIE) and work with supporting student digital champions (Digichamps). Conducted in early 2025, our research gathered over 1,000 student responses to assess digital engagement, support, and expectations, with a particular focus on the impact of emerging generative AI (genAI) technologies on learning practices. A retrospective analysis highlights key shifts since 2019. Notably, the study captures students' diverse perceptions of genAI tools, and some insights into more detailed usage. Comparisons across disciplines, modes of study, and year groups reveal nuanced differences in adoption and attitudes. We will discuss the main findings in detail, providing insights into how to frame questions around students' evolving digital competencies and critical engagement with AI technologies, and digital education more widely. The paper offers a timely update on students' digital experiences in higher education in 2025.