As generative AI reshapes how students produce work, questions about what counts as authentic inclusive assessment have become more urgent. If AI can draft essays, generate code, and simulate expertise, how do HEIs design assessments that genuinely prepare students for professional life? In response to this question, the eLearning Development Services Unit (EDSU), in collaboration with the MTU Director of Student Services, began examining authentic assessment practices across the Kerry campus in December 2025. A call was issued to staff on the Kerry Campus of MTU to showcase real examples of authentic assessment experienced by teaching staff . Early indications suggest that AI and digital technologies are not replacing the pedagogical foundations of authentic assessment but are instead strengthening and expanding the ways in which those foundations can be enacted across diverse higher‑education contexts.

The initiative generated a range of technology-enhanced assessment examples, including problem and scenario-based tasks as well as inquiry-based approaches grounded in real-world professional contexts. To move beyond simply collecting examples, we developed a working categorisation framework to analyse the submissions. Assessments were considered in terms of whether they were:

• Genuinely authentic and technologically aligned

• Designed with authentic intent but supported by superficial use of technology

• Technology-heavy but lacking authentic learning design

• AI-aware or AI-avoidant in their structure

This categorisation allowed us to examine how pedagogy, technology, and GenAI awareness were interacting in practice, rather than treating technology use as inherently innovative. This work is situated within a growing body of research examining the relationship between authentic assessment and digital technologies. Hu, Liu and Daniel’s (2025) systematic review of digital technologies in authentic assessment identifies how contemporary higher education is increasingly turning to AI‑enabled and data‑driven tools to support assessment practices that reflect real‑world tasks. Their findings reinforce and extend the earlier framework proposed by Villarroel et al. (2018), who argued that authentic assessment requires alignment between learning outcomes, real‑life professional demands and assessment design. Simulations, Inquiry-Based and Problem-Based Learning, oral exams and portfolios emerge as examples. While Villarroel and colleagues provided a conceptual blueprint for constructing authentic assessments that promote meaningful learning, Hu et al. demonstrate how digital technologies can operationalise this blueprint at scale. Examples of these include adaptive platforms, analytics dashboards and simulation environments. This suggests an evolution in practice in which authentic assessment is no longer only a pedagogical ideal but increasingly a technologically supported practice.

This session will present examples gathered through the campus initiative, reflect on patterns emerging from staff practice, and examine how technology, pedagogy and GenAI awareness intersect in the design of authentic assessment. It will offer a practice-informed framework for distinguishing between meaningful integration of technology and superficial innovation in assessment design.