How can we better support time-constrained educators to help boost student engagement in online learning environments?

This Gasta presentation shares how a recent TEL (Technology-Enhanced Learning) Engagement Series from Maynooth University used microlearning and visual design to help staff build skills and improve their digital teaching practice.

Faced with growing demands on educators and rising expectations from students, we developed a new approach: bite-sized, visual, interactive guides that rethink traditional course design support.

Using Canva and Genially for clarity and interactivity, I created a six-part infographic series, each designed to fit busy schedules while delivering high-impact guidance for course design enhancement.

Each infographic introduced approaches and tools within Moodle and was paired with bite-sized webinars to reinforce implementation. The presentation will explore the creative process behind the project including the specifics of the tools and methods and share key lessons in enhancing supports for staff in Moodle course design.

As AI helps to reshape how we work, teach, and create, one of our most powerful tools remains wonderfully human: the ability to spark new ideas. But creativity isn’t magic - and it’s not reserved for “creative types.” In this GASTA session, I’ll introduce a practical, timeless five-step method for producing ideas - one that shows creativity can be a process, not a mystery.

From collecting raw material to the elusive “aha” moment, this technique offers a structured, repeatable way to get unstuck and generate fresh thinking. In a time when adaptability and innovation are essential in education, knowing how to build ideas - rather than wait for them to randomly appear - is a serious advantage.

Whether you’re designing learning experiences, solving sticky problems, or dreaming up your next EdTech project, this fast-paced session will offer a quick, powerful reminder: good ideas aren’t born - they’re built.

With Dr. Tom Farrelly counting me in (and out!), you’ll discover that in a world full of algorithms, the real spark is you - the human in the loop, with a great idea ready to ignite.

Embarking on a research postgraduate programme demands the development of a wide range of skills, as outlined in the EU Research Competence Framework. Given the diverse academic, professional, and geographical backgrounds of incoming students, it can be challenging to ensure that everyone starts with the foundational knowledge and skills needed to succeed.

To address this, the Centre for Academic Practice at SETU is developing the Graduate Resource and Development (GRAD) Programme—an online, self-directed resource designed to support our growing community of research postgraduate students. GRAD will offer practical guidance and insights across academic, personal, professional, and research-specific skill areas.

Designed as a wraparound support available anytime, anywhere, and to all students across our campuses, GRAD is being built in close collaboration with existing support services, faculty and, of course, students.

This GASTA presentation will explore the rationale behind the initiative, share an overview of GRAD’s content, design, and delivery, and highlight the crucial role of student input in co-creating this innovative resource.

Anthropomorphic avatars have promoted social support and a sense of community. This presentation will provide instances of AI-driven anthropomorphic chatbots designed for human-AI interactions, focusing on improving performance by affecting users' perceptions of belonging, social support, loneliness, and connectedness. Interaction with AI chatbots augments human communication and can elevate performance via user involvement. The session will clarify how AI-driven chatbots foster a sense of belonging and provide social support through connectivity, analyze examples of human-AI interactions aimed at improving performance by enhancing social support and reducing loneliness, and present the outcomes of experiences with AI chatbots. Moreover, it will investigate how mitigating loneliness with AI chatbots promotes performance in professional and educational settings by augmenting concentration, motivation, and overall well-being. Participants will evaluate the effectiveness of AI chatbots in providing emotional support and enhancing connectedness. The presentation will also analyze the digital divide and strategies for overcoming barriers to enhance performance. The objectives include assessing the effectiveness of generative AI chatbots in providing social support and fostering a sense of belonging, exploring the capacity of anthropomorphic avatars to reduce loneliness and improve connectedness, and discussing methods to refine the design of these avatars to enhance user engagement and performance.

While AI’s promises are often wrapped in narratives of innovation and transformation, these technologies are grounded in deeply material realities: server farms, energy-hungry computation, rare earth minerals, and the human labour behind system maintenance (Brevini, 2021; Crawford, 2022; Saenko, 2023). Large language models (LLMs) quantify their outputs in “tokens”—a benign-sounding metric that obscures the real-world costs behind each interaction. As we design learning experiences powered by AI, we must also ask: what are we truly spending, and on whose behalf?
Drawing on metaphors from data extraction to climate catastrophe (Weller, 2022; Holmes & Tuomi, 2022), this gasta considers alternative ways of visualising the cost of AI use. Imagine if, alongside each AI-generated response, learners were confronted with the image of a rare earth mine labourer, a coal energy plant, or a melting glacier? Could such visual interventions foster a sense of ethical intentionality and digital restraint? This gasta proposes a rematerialisation of the environmental toll of AIED within our digital learning spaces—making energy consumption visible and accountable. Rather than perpetuating dominant, extractive AI narratives focused on scale and speed, this talk advocates a pedagogy of digital degrowth (Selwyn, 2023), where critical use, slowness, and sufficiency become design values.

Generative AI is capable of many things which we are becoming increasing aware of day by day. To manage the use of Generative AI, some institutions are implementing traffic light systems which categorises generative AI usage: Red = no AI use, Amber = limited AI use under guidance, Green = AI use permitted within guidelines.

Despite several institutes adopting this type of strategy which is similar to or based on the AIAS by Perkins et. al (2024), there a couple of issues with this type of strategy:

For the red-light category, as an academic, how do you detect AI use reliably? Currently, AI detection tools are not reliable and a simple defence is all that is required that "I asked Generative AI to help me rewrite my paragraphs". For any middle categories such as amber or similar, again, how can you detect its use?

For generative AI usage, the traffic light system doesn't provide a solution to assessment in s generative AI era in higher education. A strategy which is more logical in this era is the two-lane approach to assessment (Bridgeman and Liu, 2024). This categorises assessment types based on the assessment security: Secure (in person) or Open (unsupervised).

This reflective presentation explores the evolving impact of generative AI in education, not through a lens of technological advancement but through the deeper question of human value and self-worth. Drawing on educational philosophy (Piaget, Dewey, Freire) and lived experience as an educator, it reviews the persistent societal model that emphasises success as competition and measurable achievement. In a system where grades, GPAs, and awards are seen as proof of individual value, AI challenges our ability to "prove" learning and disrupts long-standing assessment practices. But perhaps more troubling is the underlying reality that we have long neglected to model or teach that self-worth, contentment, authenticity, and personal growth should be core educational goals.

This paper contends that AI is not the real threat, it is the mirror. It reflects back a system where students and educators alike must constantly justify their worth. This is why generative AI poses such grave challenges for education. Do we continue to replace essential human values with institutional performance metrics?

The rapid evolution and multifaceted nature of Artificial Intelligence (AI) presents a wide range of challenges and opportunities for higher education. Recognising the need for a coordinated response, the N-TUTORR funded GenAI:N3 national project was established as a pioneering collaboration between seven partner technological universities in Ireland. This initiative aimed to create a cohesive National GenAI Network and Hub, providing open resources to support the integration of AI into teaching, learning, and research.

Through the GenAI:N3 project, ‘AI Play’ training courses tailored for staff and students were delivered both across the sector and internationally, fostering digital literacy and practical AI skills across diverse disciplines. Additionally, the project has facilitated hackathons within each partner university, encouraging participants to experiment with AI tools, develop innovative solutions, and enhance their creative and analytical capabilities. A crowdsourced book capturing examples of good practice across the sector was also developed.

This presentation will outline the collaborative framework of GenAI:N3, showcasing how a united approach across multiple institutions can accelerate the responsible and effective adoption of AI in higher education. Furthermore, it will highlight the successes, challenges, and future potential of leveraging shared expertise to enhance AI literacy and innovation.