Artificial Intelligence in Teaching, Learning, Assessment

Artificial Intelligence (AI), and particularly Generative AI (GenAI), continues to present a significant impact on society in general, and very particularly on education. In March 2025, DCU published its Position Statement on the Use of Artificial Intelligence Tools, a living and evolving document to guide the university’s response to AI. Our work in the TEU aligns with this position statement, and we provide training, support, and guidance to DCU staff on aspects of teaching, learning, assessment in response to GenAI. 

Our work is guided by national guidelines including the HEA’s National Policy Framework on GenAI in Teaching and Learning and the National Academic Integrity Network’s (NAIN) guidelines on GenAI for Educators. We align with the view outlined in the HEA’s National Policy Framework, which states that “[GenAI] is a set of tools that, regardless of any individual professional or personal perspective, must be integrated thoughtfully into teaching and learning in ways that are consistent with academic values, national policy commitments, and the lived realities of HEIs in Ireland” (O’Sullivan et al., 2026, p.3). We recognize the complexity that GenAI presents across teaching, learning, and assessment, and are committed to supporting staff in navigating the opportunities and challenges in a thoughtfully considered and informed way. As the technology continues to evolve, we will continue to regularly review and update our resources in line with local, national, and international developments, to ensure what we provide is current, relevant, and targeted.

GenAI in Teaching, Learning & Assessment

DCU has always been innovative in teaching, learning and assessment. It is important to ensure that our students know about GenAI, how to use it ethically in a disciplinary context and they can learn that from how we integrate it into approaches to teaching. To support this, the TEU has developed a range of resources, including DCU’s version of the National Forum’s Digital GenAI Badge, to help staff build their GenAI literacy and reflect on strategies for integrating GenAI in their teaching practice. The TEU also works with staff  to share discipline-specific approaches to embed knowledge and use of AI tools in student learning, and to support them in reviewing their modules to identify the best way to integrate knowledge and use of AI tools. More information can be found in the ‘GenAI & Teaching Support’ tab section below.  

Artificial intelligence, Assessment and Academic Integrity

Artificial Intelligence tools, particularly Generative AI (GenAI) tools do require responses to protect academic integrity via assessment design.. The TEU has created a Design In/ Design Out Decision Tree to support staff’s assessment approach in response to GenAI. Staff are asked to carefully consider and reflect their assessment design and have GenAI tools designed into them (designed-in) or (re-)designed to avoid possible breaches of academic integrity with the use of GenAI tools (designed-out). DCU is an active member of the National Academic Integrity Network (NAIN), and the Head of the TEU and the Academic Integrity Officer) are monitoring and disseminating information to staff on this topic. We do not employ GenAI detectors, due to the high number of false positives and other concerns stated in DCU’s Position Statement on the Use of Artificial Intelligence Tools. We  also promote the expansion of the use of alternative assessment approaches, such as Interactive Oral (IO) assessments and e-portfolio assessments. These actions form part of DCU’s ongoing commitment to designing authentic assessment approaches.

Programme analysis for AI-world readiness

We have a responsibility to ensure that our offerings to students are relevant and prepare them to be successful in whatever they do once they graduate. As part of our commitment to prepare our students for a world in which AI tools will be used in a variety of ways, DCU will continue to analyse the current portfolio of programmes to ensure that 1) each programme is anticipated to remain relevant and demand for the numbers of graduates to be strong and 2) content reflects the emphasis on knowledge frameworks, competency over information etc which will ensure our graduates will continue to be relevant and ready for an AI-infused world.