ATAIN - Using LMS 'Nuku' to read and engage with policy - Dr. Lorena Gibson

An AI policy was designed for the Cultural Anthropology programme at Te Herenga Waka-Victoria University of Wellington. The presentation, hosted by ATAIN is provided by Dr. Lorena Gibson - lecturer in cultural anthropology.

The presentation is on 'Discussing AI use with cultural anthropology students'. Shared the guidelines for using AI - AI assessment scale (Perkins, Furze, Roe & MacVaugh, 2024) and how this has been used with her colleagues and students.

Her students work through the guidelines through a LMS module. There are 6 modules and students have to complete a quiz. Modules on [ need to complete before assessment!, AI, how and why to use, how to use AI in assessments, acknowledging Ai use, what not to do with AI, lecturer's own practice with AI.

Shared content of some modules which provide not only links and information but also examples which are of relevance to their context. Modeling by Lorena, and transparency from her examples, set up good practice and show authentic use of AI. 

Shared the section on using AI with course tutors. A pragmatic approach and for them to reinforce the advice provided through the AI modules. Good to see this as well as most of the time, teachers do not access information provided to students.

Interesting Q & A followed.

Important to also ensure students understand the difference between various assistive technologies and AI. Students are embarrassed or ashamed of using AI and clear, visible and educative information is always good practice. AI anxiety is very real and reported in a recent 2026 report on NZ students well-being.

Discussion on the challenges encountered in academic settings. In all, educators need to be sensitive to learners' difficulties. However, students need to engage in 'productive struggle', otherwise, they do not actually attain academic writing skills. 

Assuring quality learning in a Gen AI integrated future

This is the third in a series on AI from the Tertiary Education Quality and Standard Agency (TESQA) in Australia. 

Assuring quality learning in a gen AI-integrated future: The role of adaptive capabilities follows on from two other reports - Assessment reform from the age of AI and Enacting assessment reform in a time of AI (summary on this blog).

In this report, adaptive capabilities in the age of AI are defined as drawn from the report authors' understandings of digital literacy tools to be used ethically and safely; distributed cognition as tasks shared between people, tools, artefacts and gen AI systems; hybrid cognition as thinking and learning within cognitive systems; and life long learning to sustain motivation, capability and adaptability. Agency and regulation from individuals, draw the four aspects of adaptive capabilities towards deeper disciplinary knowledge. 

The report argues well for the attaining of the above capabilities before moving on to how learning environments need to be reshaped to help learners. Propositions for policy and practice are presented:

- establish adaptive capabilities as  core graduate attributes.

- build institutional infrastructure for learning process evidence

- design learning environments that promote adaptive capabilities through evidence-informed practices

- transform pedagogical practice toward process-focused assessment

All in, a short but insightful and pragmatic report providing some ways forward into the age of AI. 

Assignments in the AI era

 In light of this article from Radio NZ, whereby some universities in Aotearoa are no longer checking assessments using AI tracking platforms, a summary of ways to think about assessments in the AI age is of importance. There has been much discussion on how assessments in higher education need to be evaluated and re-thought, given the infiltration of AI into our work and study. This article in Times Higher Education, distills many of the main discussion points in academia on how AI affects academic writing.

The work undertaken at my institute is focused around holistic / programme wide assessment design, rather than on individual courses. The term 'programmatic assessments' is sometimes used to describe this approach

Some of the other strategies we have used, are summarised in this blog - NavigateAI (Dr. Ryan Baltrip)  In summary, to place greater weighting on recording the evidence of learning, rather than the product of learning. Therefore, portfolios and similar assessments are more useful than one off invigilated exams, or assignments. 

In Aotearoa, Otago Polytechnic's Bruno Balducci, have introduced the concept of AI safe design, a framework for the design of assessments which take into account the influences of AI. These are useful as a way to help educators work through the many pitfalls involved in redesigning assessments that will be authentic and relevant, but will not tempt learners into using AI to complete them.

The other concept we have used to help our teachers work out how to structure assessments in an AI age is the 'two lanes' assessment structure.  Here, lane 1 assessments are used to as assessments OF learning - or summative, higher stakes assessments. Lane two are the assessments FOR learning, taking on formative approaches to inform learners as they progress to the course.

Therefore, it is important to not just assume that current assessments will be appropriate but to undertake a stock take to understand the purposes of each assessment, and to put in place relevant assessments that will meet the purposes of each assessment i.e. evidence that the learner has met learning outcomes.