Cogniti - webinar - Student engagement with an Ai agent

 Notes taken at this month's Cogniti Connect. (the second session)

 Notes and video of the first session found HERE -  'when a tool meets a community'

This month's topic is 'what makes students engage with an AI agent or not?'  aka 'built it and they will come!' The session is facilitated by Olga Kozar.

A survey on the webinar indicated the majority of attendees have poor Agent usage rates.

Three case studies are presented:

- the 10% to 60% engagement shift Cogniti in chemistry: student engagement across different implementations. Presented by Dr. Pierre Naeyaert from the University of Sydney. Students access the Cogniti agent Canvas LMS. Pierre does not have physical access to the students! Agent available since August 2024 with 3,5000 students enrolled. By the start of the year, only 180 students have accessed. From start of this year, Pierre worked towards increasing engagement. A report helper agent was developed for 71 students have to access this before they can submit the report. 11 students engaged. Another agent developed in semester 1 2026 for 140 students. Agent focused on practicing their viva. 50 students used this agent. An embedded video to provide support for how to use the agent may have been useful in bringing students in.

First year survey on AI indicate students use AI 2/5 and 3/5 responded that they did not. Chem1 Cogniti agent was rolled out to 1900 students. 1280 students used. Again a video was used to show students how to use the agent. 

Q&A followed. Ideas on providing information to students to encourage using agents shared (posters, naming the agent with a friendly name, 'how to use' video)

- Design dilemma: How to 'use it to leverage it' with Robert Annabel from University of Sydney on 'to and through the door: the question generator in ECON6021'. This writes practice questions and is available to 143 Masters students from the first week of the course. Access through Canvas and information also on the course outline. Students reminded about the agent during lectures. 

24 days (7 weeks) there were 41 conversations, 88 messages. Postulated that students had high workload and concerns on the reliability of the agent. A conversation starter could be useful to get them going. Worked through several system prompt redesigns including - agent to ask for missing topic. Allow one question at a time. Solution to be provided after an attempt. 

In week 12 tutorial taken to do a live demo of the tool. Information on the pedagogical purpose of the agent. Class discussion was useful. Students provided feedback. This session helped increase conversations to 109 and messages to 833. 

Discussion on how much reminder and time need to put into encouraging students to use the agent. Comments in the chat revolved around how students 'want the answer' and not willing to engage with 'Socratic' style conversations. 

Dr. Carrie Falling from University of Otago shared that first impressions are important. Short time window to obtain their attention and to see the advantages for using the agent. Agent performance has to align with the learning outcome, be easy to use and concise feedback (not long screes of text). Well-designed agents are therefore important to ensure that the user experience is encouraging further use.

- Cogniti sand boxes: 'Sandboxes for critical AI literacy and graduate attributes' with Dr. Carmen Vallis from the University of Sydney. The course Business consulting practicum simulates a project, with industry input. AI changes what 'professional' and 'authentic' mean. The AI agent is an 'AI consultant'.

Cogniti sandbox used to have students create their own agents (with speech and avatars). A safe space to experiment, with secure data and Canvas access. Students could select their own AI models For teachers, a sandbox is easy to set up and they can see agents and conversations in one place. Teachers can share editing.

A 2 hour workshop helped students write a professional profile, choose the info to share (or withhold), built an agent and add to their profile. The then tested their agent (and their values) against real scenarios. Then debriefed in groups on personal, professional and ethical implications.

Small cohort of 24 students. There were 104 conversations across 1 workshop and 2 sessions. Students needed more time and some did not create one. It was messy but the students were engaged. 6 students returned, unprompted to use the AI more. Language shifted between informal to formal. Reflected that next time, they would create a future consultant persona instead of students' professional profile. The sandbox needs to be simplified to have less strict prompt control, use new in-build features and provide more time for students to work on the AI agent.

Q & A followed. 

Olga introduced the next session in October - Bendigo Kangan Institute on Cogniti AI tutors and Manakau Institue of Technology and Unitec on their bespoke platform for end to end AI agent governance and oversight. Also call for presentations on this year's Cogniti Symposium. 

UNESCO report - An algorithm in the room

UNESCO report 2026 on AI in education - The algorithm in the room : seeing and confronting the implications of AI for the future of education. 

Similar to the four scenarios from Singapore, summarised recently in this blog, this report collates 26 think pieces organised into 6 sections.  

After an introduction on the concept of 'algorithms everywhere' along with a discussion on educational purposes and the difficulties of aligning these algorithms with these. Each section presents several think pieces. 

Part one asks 'who will hold agency, autonomy and oversight'?

Part two on 'How will young people develop relationally, emotionally and cognitively?

Part three goes into 'what will be meaningful and relevant for pedagogy and assessment?

Part four moves in 'how will we think, question and express ourselves?

Part five poses the challenges on 'how will we govern education for the common good?

Part six closes with 'how might AI affect imagination about the future?

Each section has several articles, many speculative case studies. Topics discussed provide food for thought. They also provide good conversation starters and work well as thought provokers. 

The conclusion discusses the 3 horizons to empower education in algorithmic times - to see, to steer and to rewrite the algorithm.

Many of the key ethical and educational challenges are discussed through the report. Overall, a report to dip in and out of as interests in each topic arises.

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. 

Ai agents - use in education - Sacha Garrity from Unitec

Sacha Garrity, academic advisor in digital learning from Unitec, presents on how AI agents are used to support learning. The event is convened by Whitirea/Weltec. The work has received national recognition through the Tertiary ICT Association. 

Lee Smith from Whitirea/Weltec welcomed everyone. A karakia was offered before introductions to Sacha and Sharnell Aumua. Their presentation is on the Ako AI agents project: Nursing.

Agents have been used for about a year. The Ako AI agents project involved supporting kaiako to customise mini ChatCPTs, hosted on Cogniti to be used by ākonga anytime when required, help to be responsive to ākonga needs and provide additional support to kaiako. Agents are embedded in Moodle so students do not have to move between two platforms.

An overview of Cogniti provided. Agent development informed by design-based research and Te Tiriti o Waitangi health principles. Agent developed with kaiako through co-design.

Quality assuring the agent is important. Testing undertaken through a broader group of kaiako. Follow a test protocol - does it do what is intended, promote learning, avoid unwanted responses. Then test with ākonga and gain feedback.

In short - interative design and test, extended test by kaiako, followed by student test and final Q & A. 

Shared the nursing Ako AI. 3 nursing kaiako for each agent - (de-escalation agent, deteriorating patient and drug calculations. 4 developers and technical support. Stressed importance of drawing from and integrating Te Tiriti o Waitangi health principles.

Evaluation involved questionnaire, focus groups. Two iterations of testing and data collection for each agent. 

Went through the drug calculation agent capabilities - providing fomulae for conversions/rations and calculations. Provide tutorial support. A demo ensued - basically a quiz, providing support when the student is unsure or unable to do the calculation. 

ākonga feedback indicated that their learning confidence and competence was enhanced; user experience and design interactivity was appreciated; future AI tools and expanded learning support indicated - better integrations between LMS and Cogniti, videos to do revision, gamification / progress bar useful.

Demonstrated the deteriorating patient agent. A scenario agent. Two scenarios - hospital and community. Agent generates verbal and non-verbal behaviours, reactions based on student's response. New patient profiles generated at each use along with clinical/vitals. Feedback involved debrief, reflection and overall feedback - a challenge to build.

The agent has a 'toolbox' which is a link to 'help' in using the agent. Demo of agent in role as patient, perceptor and going through the debrief loop. 

Overall, positive responses from students. Students trusted using the agents as they were developed by their tutors. Interest in having a range of agents to support learning across the nursing curriculum. Support for more clinical scenarios prior to going out to clinical.

Q & A 

Oral responses - challenge with Te Reo Māori as pronunciation not the best. 

24/7 support useful. Agents able to provide more in-depth feedback when they have time or need to undertake practice. A safe place to practice or clarify concepts etc. can be done. 

Intentional learning is a key to developing how the AI agent is structured. Cogniti is user friendly and does not need IT degree to set up. 

Volume of use brought up. Currently Cogniti coping but not sure of maximum number if a agent is open to entire institution e.g. for learning, academic or library support.

Toolbox discussed and how it can be used intentionally. Access to documents supporting the learning can also be accessed through the toolbox.

Security aspects discussed. Important to only provide resources which are relevant and Cogniti itself should not have access to internal organisational data. 

Time from start to implementation averaged 3 - 4 weeks - mostly for SMEs to test, run staff test groups and gather feedback etc. 

Four future scenarios for training and adult education in Singapore - horizon 2035

This report - Four future scenarios for training and adult education in Singapore - Horizon 2035, is written by Ang, B.J., Huang, M. & Chen, Z., the Institute of Adult Learning, Singapore University of Social Sciences. 

The horizon in the report is less than a decade away. For some, a long way off, but with AI, perhaps a shorter window may apply. The report is also deeply integrated into the Singapore training and adult education ecosystem, Therefore, the report needs to be read with the context in mind.

After a preamble section, explaining the approach, philosophies and methodology for the report, the future scenarios are presented. These are:

- the trusted system - very much based on the current system whereby national standards and skilled educators provide and enable completion of qualifications. Currency is the main challenge as technology moves quickly and standards and educators struggle to keep up.

- AI skills network - based in AI being used to provide personalised, continuous and 24/7 available training. Human support and accountability become difficult to built in when required.

- the reputation economy - draws on expertise of trainers but depends on reputation and networks.

- skills market - AI is used to build capability but visibility and trust on credentials is uneven.

The scenarios are of interest as they show how difficult it is to see into the future, given the pace of change and the many challenges related to shifting an embedded credentialling system. Each country will need to undertake similar exercises, to test the efficacy and flexibility of their current training and qualification system and to think through implications, challenges and solutions from within their own contexts. 

A new direction for students in an AI world - report from Brookings Institute

This report - A new direction for students in an AI world: Prosper, prepare and protect was prepared by M. Burns, R. Winthrop, N. Luther, E. Venetis and R. Karim and published at the beginning of 2026 by the Centre for Universal Education at Brookings Institute.

The report focuses on the formal school context. It is just over 200 pages including appendices.

It is framed on the premise that at this moment in time, AI can be useful in enriching learning experiences.

The 3 pillars anchoring the report are:

- Prosper - to use AI carefully to enhance student learning

- Prepare -ensure not only educators and students, but the communities they serve are prepared through understanding the implications of AI on education.

- Protect - safeguards are important to assure privacy, safety, and support emotional and social development.

Discussion is undertaken on how AI can enrich education AND how AI can also diminish learning if overused without adequate guardrails.

Annex A provides a good summary of various AI literacy frameworks.

ASQA - principles for the responsible use of AI in VET

The Australian Skills Standards Authority (ASQA) have released their principles for the responsible use of AI in Vocational Education and Training (VET). 

The guidance is summarised on the site - AI use in VET.  The site contains links to the principles, case studies, how the principles were developed, and an AI transparency statement. The principles are found in the section on the responsible use of AI in VET. They are high level and examples/case studies are provided to inform how the principles can be applied to teaching and learning.

Critical thinking - some models to inform teaching and learning

 The application of critical thinking towards evaluating information has been and is now an even more crucial skill. AI generates plausible responses but these must always be checked or triangulated. Ensuring everyone understands the underlying principles of critical thinking, and how the process to apply it towards becoming better equipped to deal with the avalanche of material many people wade through daily, is now more important than ever.

Three recent articles provide guidance. Each offers a model/framework to teach and preserve critical thinking skills.

1) 

Vendrell, M. & Johnston, S-K. (2026). Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education, Computers and Education: Artificial Intelligence, Volume 10, https://doi.org/10.1016/j.caeai.2026.100572

Firstly, an update on critical thinking from Vendrell and Johnston (2026). The paper presents an analysis of research in cognitive psychology, educational theory and AI ethics. These are then synthesised to develop a pedagogical framework for integrating LLMS into teaching and learning. The principles of critical engagement are defined as: conceptual interpretation, intellectual curiosity, inferential reasoning, evaluative judgement, metacognitive regulation, and epistemic integrity. The paper recommends design principles that preserve cognitive friction, scaffold LLMs as partners, embed evaluation as standard practice, activate metacognitive regulation, encourage humility and curiosity, foster epistemic integrity, align assessment with thinking and balance AI mediated and AI free phases. 

2) 

Brcic. M. & Frljic, S. (2026). The effortless trap: Productive struggle, AI, and the illusion of learning. https://arxiv.org/pdf/2606.26181

A preprint which extends on the article in 1). it advocates for ways to avoid cognitve debt but ensuring that there are elements of 'productive struggle' in learning. The framework involves working through the following when working through new concept:

- Prime - help learners find a reason/motivation 

- Probe - provide a 'hard' problem so that learners have to tryout new ideas, learn from making mistakes and problem solve their way through.

- Point - using Socratic guides or cognitive apprenticeship to help make the problem solving strategies visible

Attach - connect the new to already learnt or new concept

Strengthen - reinforce through deliberate practice so that the concept/process is anchored.

3) 

Liubertaitė AD (2026) EFFORT-AI: an effort-preserving module for cognitively aligned human-AI learning. Frontier of Education. 11:1849821. doi: 10.3389/feduc.2026.1849821

This article also advocates for the need to ensure cognitive effort is undertaken to assure learning takes place. Introduces the EFFORT-AI model as a way to iintegrate AI into learning without allowing AI to do all the work.

- Elicit - Help learners make known to themselves their prior knowledge on the topic and their motivations to learn.

- Formulate - undertake a first attempt at a problem, either through retrieval or explanation

- Feedback - use feedback cycle to find out progress (or not)

Organise - make sense of the concept/process

- Reflect - review, revise and work out how learning undertaken , gaps in understanding and where to move to next

- Transfer - apply and review (spaced) to keep the concept/process active.

Articles 2) and 3) provide examples, mostly in STEM topics but frameworks cane be adapted to many other disciplines. The frameworks in themselves are therefore useful as starting points for adapting signature disciplines and pedagogy towards pedagogical integration of AI.

Being you:: A new science of conciousness - book overview

e-book borrowed from the local library and read on Libby, across a wet winter weekend. This book 'Being you:: A new science of consciousness' by Anil Seth, was one of the books (and authors) featured in  Pollan's book 'A world appears'.  The book was published in 2021 and sets out a biological/evolutionary perspective on consciousness. 

The book has positive reviews - exampled by this one from the Guardian. In itself, the book undertakes an update on neuroscience understanding of how the brain works and how its organic nature, may not be easily replicated. 

The book has 13 chapters with introductory and concluding chapters as well. The 4 sections, lays out the argument, each building on the next to provide details of how the workings of the brain, provides each person with a highly individualised perspective on the world at large. Being organic, the brain draws on the various senses, memories and experiences of each person. Hence, it is inherently a 'work in progress'. Each chapter has several pages of notes at the end.

The processes described in the earlier chapters explains some of the challenges for transforming people's mind-set. It takes effort and persistence to over-ride what each person has learnt, through a life of being in the 'university of life' and to shift perspectives. This is not impossible, which is where education plays an important role, but moving one's way of being, doing, thinking and feeling, requires strong social and individual motivation. It is an intense  undertaking to shift tracks which is why items like political affiliation (see Haidt's book - the righteous mind) takes some doing.

As to whether AI will become 'conscious' is dependent on how consciousness is defined. As per this book, the argument is that 'qualia' a sense of what something is and the degree of someness, is already difficult to quantify as each sentient being, brings their senses and experiences to gauge the experience. My estimation is that currently, Gen AI does not exhibit qualia. Gen AI cannot 'feel' or be conscious of its selfhood. It remains to be seen what may happen into the future. For the moment, our humanness affords us many qualities that are unique to us. 

The book has many examples explaining complex concepts and processes. It is an accessible read providing a good update on current understandings of how the brain works. Important now when claims are made each day about AI and yet, there are so many things AI is not able to do. AI looks proficient, but it is still a pattern matching algorithm. The patterns look plausible to us because our brain favour tidy patterns and black and white answers. However, many aspects of life are not quantifiable, predictable or straight-forward. As such, the human brain, with its inherent malleability and ability to 'think outside the square', draw on experiences /wisdom, and actually change tack when required, will still be difficult to replace. 

A world appears: A journey into consciousness - book overview

A catch up on aspects of neuroscience, especially to inform thoughts on AI of General AI (GAI) being able to take on human consciousness. Update on readings about a decade ago including Soul Dust; Sentience; the problem of soul; Who am I? and Tell-tale brain. 

Borrowed the book - A world appears: A journey into consciousness - by Michael Pollan from the local library, published 2026 by Penguin.

I have read several of Pollan's book, due to my interest in food. His many books provide alternatives ways to view often mundane topics. He writes for the layperson, but his work draws on the corpus of literature (albeit predominantly from the Western thought canon) and interprets perspectives that connect well with everyday life.

This book is again an accessible introduction to the difficult topic of consciousness. The book brings contemporary research along with an overview of efforts in the past to understand the topic. Pollan talks to many of the researchers in the field, providing a sense of their work and interpreting how each way of understanding the difficult concept of consciousness, adds to an understanding of what might be, what might not be and the many aspects of its amorphous nature.

It is a relatively short book. The introductory chapter lays out the direction of the book. Then follows 4 interwoven chapters, sentience, feeling, thought and self. Each begins with an attempt to define the main topic and then undertakes a discussion around the many themes and variations that underpin the topic. The last chapter 'the cave' is in introspective conclusion on the many rabbit holes and directions the previous chapters traverse.

Pollan himself undertakes to be a 'test subject' in several of the projects he investigates. In previous books, he has written about his use of hallucinogens, as a way to explore alternative realities. The book wanders through the many options availed to try to understand consciousness. In short, there is no agreement or rational statement that defines consciousness. We need to be very cautious about accepting statements on 'AI attaining consciousness' when it is so difficult to pin down consciousness itself. Organic perspectives, including thinking, feeling, sensing etc. and how these contribute towards a sense of 'self' must always be carefully navigated and thought through as non-organic representations likely only 'capture' a hint of what it means to have consciousness. 

There are copious notes across the book. I will need to check out the Journal of Consciousness Studies which publishes interdisciplinary work on consciousness and several recent books.

Onwards to more reading and learning :) 

FLANZ webinar - How does a course template change teachers' teaching perspective?

 Webinar faciliated by FLANZ.

Yong Liu from Manukau Institute of Technology presents on 'How does a course template change teachers' perspective?'

Kristina Hoeppner facilitated the webinar and began with karakia.

Notes taken below:

Summarised the challenge of teachers shifting from f2f to online teaching. Always challenging but proposed the use of templates as a way forward.

After introduction, presented learning theories , then shared the course template, a teaching perspectives inventory (TPI) and a case study.

Rationalised the project as there is a trend to shift to more online learning. Teachers' challenges included technology integration, teachers' academic development (need training but time poor). An online course template provided to help ease the process.

Course template needs to include guidance and examples to provide better steer. 

Draws on constructivism (students learn by exploration and interaction); Cognitive constructivism (connecting new knowledge to existing knowledge); social constructivism (communication and collaboration - teaching and group work - involves learners); connectivism (technology integrated social constructivism). Introduced Canvas as the LMS with tools to engage learners - discussion collaboration etc.

Course template has course home page with course information (plus in-text guidance through hovering on call button). Went through the contents in each section, Information in the call buttons provide steps and required content in each section).

TPI (Pratt and Collins) is an online questionnaire to determine teachers' orientation. The teaching perspectives include: transmission; apprenticeship; developmental; nurturing; and social reform. 3 aspects in each orientation - teaching belief, teaching intention, and teaching action. 

Case study conducted with 17 participants - survey before and after using template, and along with semi-structure interviews. Firstly, established teacher beliefs, intentions and actions and repeated after template used. 

Findings shared. In general, apprenticeship, development and nurturing perspectives increased. Beliefs tended to trend towards constructivist and connectivist teaching strategies. 

Q & A followed. 

Blog on capabilities approach by Professors Leesa Wheelahan and Gavin Moody

The Society for Research in Higher Education (SRHE) in the UK are hosting a blog by Emerita Professor Leesa Wheelahan and Gavin Moodie on the capabilities approach.

The first blog introduces the approach. Following on is the blog on capability for higher education and then one on special, adult and future education. 

An important aspect of the capabilities approach is the broader range of skills. knowledge and attributes attained as outcomes of learning - whether through formalised training/education or at work and through life activities. it is especially important at this point in time to move away from tightly defined and narrow prescriptions (i.e. through competency or skills-first approaches) given the challenges brought in by AI. as educators, we need to consider the wider issues and aspects that will provide continual development to everyone. In doing, we help individuals maintain currency and develop skills to cope with the onslaught of occupational shifts. 

ATAIN - He Ara Mauri: Asking five large language models to calculate their value

 This session of ATAIN presented by Tanya Ruka (He Herenga Waka - Victoria University of Wellington).

She presents on:

He Ara Mauri: Asking Five Large Language Models to calculate their value

He Ara Mauri is a vitality framework grounded in Indigenous relational ontologies that asks a different question of AI: does this system sustain conditions for life, or degrade them? Applied to five frontier AI systems - ChatGPT, Claude, Gemini, Grok, and Meta AI - each system was asked to evaluate itself and then peer-review the others across planetary, human, and more-than-human domains. The result: every system failed.

Notes taken of presentation:

Began with a introduction to her background - starting from Native Land Digital - maintain one of the most widely accessed indigenous platforms in the world. Their remit includes providing educational resources to be used in classrooms, museums, universities etc. Develop indigenous platform. 

At the moment, funding has ceased but continues with work by passionate people.

Between 207 and 2024, she worked on the Te Aho Tapu Hou project - a Mātauranga Māori led research to create circular / regenerative cottage industries. At Victoria, there is one paper - training Korēro AI - understanding 'value' from an indigenous perspective. What happens when AI is tasked with looking into indigenous value systems.

Introduced the He Ara Mauri framework. Started investigating aspects of data sovereignty and what is indigenous AI. Coined AIRI (Artificial Indigenous relational intelligence) as a term to try to explain through a Native Land data, land and water acknowledgement chatbot.

LLMs build on linear, grab and dash and taking/scraping models. No data is safe. It is an extractive, hierarchical and predictive/control oriented. However, indigenous AI is relational in architecture, bussing from a GNN model (e.g. Deepseek) which are relational and layered. This allows use to be less, drawing more on human knowledge.

Kōrero AI created as a co-designed learning tools to move beyond static land acknowledgement. Instead of providing scripted responses, the chatbot invites users into reflection but asking 3 questions about their relationships to land and water. Across a year Feb 2025 to 2026, a million users have engaged. 

Summarised the process of creating the He Ara Mauri framework for system vitality in socio-technical systems. From this, sought to find out larger LLMs deal with the framework. 5 AI systems evaluated and each evaluated on environmental impacts, human impacts, more than human impacts, power, reciprocity and future consequences. Each system failed as they could not account for ecological consequence, more than human relations, intergenerational responsibility, power concentration and long-term vitality.

The systems could not describe themselves, acknowledge uncertainty, bias or harm, demonstrate responsibility, account of future flourishing and could not explain what they restore, instead of just that they take. Therefore, each system's responses reflected the business model, strategic priorities, and public positioning of the organisation that developed it.

Yet integration across education, public services, etc. is ongoing!!

Proposed some solutions - especially in the education context. Recommends, humans must remain responsible, teach AI critically, protect human knowledge creatin, embed future generations into governance. 

Therefore AI is not simply about efficiencies but we need to understand impacts beyond the now.

Education should be about a community of care and includes stewardship of knowledge, culture, democracy, environmental responsibility, future responsibility and technology should strengthen rather than replace relationships.

A thought provoking presentation bringing us back to the fundamental questions of what makes us human and how AI needs to be carefully handled, not just taken as a tool, but to carefully evaluate where it might fit, how it is used, who and when it is used, and how AI literacy must move beyond just using and evaluating but putting AI through different perspectives. 

Q & A provided good discussion on clarifying the principles presented along with discussion from others on implications and challenges. 

Developing curriculum for deep learning: the knowledge revival - book overvew

This is an open access book, 'Developing curriculum for deep learning' comes at a time when educators need to think about the purposes of education and their role as teachers.

The book is published by in 2025 Springer as part of their Springer Brief series in Education. The book has  5 chapters, written by eminent educator scholars - 

• Tim Surma ,
• Claudio Vanhees ,
• Michiel Wils ,
• Jasper Nijlunsing ,
• Nuno Crato ,
• John Hattie ,
• Daniel Muijs ,
• Elizabeth Rata ,
• Dylan Wiliam ,
• Paul A. Kirschner

All contribute to the chapters.

The short introductory chapter provides a rationale for the book along with a brief overview of the book's direction.

The next chapter summarises 'how knowledge matters' . It begins with a summary of how human's learn from a neuroscience perspective. The importance of attaining prior knowledge is introduced and discussed along with the importance of reading. The sociological and democratic perspectives of knowledge are also introduced.

Chapter 3 connects how curriculum is used to bring about the attainment of knowledge. The various ways curriculum contribute are introduced and discussed including the aspects of horizontal and vertical coherence and their relationships to disciplinary knowledge.

Chapter 4 provides concluding remarks and references.

The last chapter provides an executive summary. It reiterates the ways, perspectives on learning, and sociological and democratic aspects shift the ways knowledge is expressed in the curriculum. It argues for the need to ensure that there is always a knowledge rich curriculum in education, to assure the development of the individual and in turn, society at large.

The short book provides a good foundation, especially now in the age of AI, to ensure that as humans, we still treasure learning and knowledge. Worth a read for all educators. 

 

Handbook of critical studies of artificial intelligence - brief overview

This book, published by Edward Elgar provides an academic discussion on the various influences on AI including political, economic and social structures. A book preview provides the first chapter which has summaries of each of the chapters in the book.

The book is organised into 7 sections, each with many chapters. The sections are:

- AI and critical theory: conceptual discussions

- Imaginaries and discourses

- Political economy of AI: datafication and surveillance

- Transparency, ethics and regulation

- Bias, normativity and discrimination

- Politics and activism in AI

- AI and the automation of society

A book to dip in and out of. Chapters highlight the many implications of AI on society, work and human being. Hence, deploying AI in education is a double-edged sword. When (perhaps best beyond primary schooling), how (perhaps only when there is a good case that AI WILL support learning), what (with pre-requisite of strong underpinning critical thinking skills and perhaps some disciplinary foundations), and why (to support and enhance but not replace human thinking).

Unesco - Integrating AI into TVET

 Following on the heels from a recently released OECD report  on developing VET with AI, is the UNESCO work on integrating AI into TVET. This is a useful guide of institutions.

The guide hinges on: Human-centredness; equity, inclusion and non-discrimination, pedagogical purposedfulness; transparency, accountability and data protection; safety, sustainability and resilience; and critical engagement with AI. 

A relatively short report (just under 100 pages) but with good generalisable recommendations which are provided for policy makers, institutions, and teachers and trainers. There is a strong direction to ensure teacher professional development are provisioned, along with ensuring the voice of teachers is heard and taken into account. 

The annexes provide 'check-lists' for AI self-reflection and planning; AI risk register; and indicator framework to monitor and evaluate AI integration into TVET.

NZVETRF - master class #2 - Apprenticeships in Australia

 This morning, a webinar, hosted by the NZ Vocational Education and Training Research Forum (NZVETRF), facilitated by Josh Williams (Skills Group, NZ and Global Apprenticeship Network (GAN) with Gary Workman ( Executive Director, Apprentice Employer, Victoria, GAN Australia ) and Peter Canavan (Senior Policy Officer, Australian Industry Group).

Josh began with introducing himself, then the speakers. 

Josh presented following comparisons: NZ has 3.7% of employed workforce in training, 108,000 == in training, 2.9 million in workfo5ce. Australia, 2.1, 300000++ and 14.7 million in workforce. 27% of NZ school leavers into training and 40+% mature entrants, but in Australia, 51% do so, with 30% mature entrants. More females in NZ - 23% with 15% in Australia as new entrants. Both countries have decline of apprentices and trainees, with trend still going down. In NZ 25% decline between 2024 and 2025 :( Completions in NZ across 6 years 62% to 50%; for Australia 56% to 58%. 

Gary presented on the 'Return of Investment  (ROI) in supporting Australian Apprenticeships' (see report). When through definitions of ROI and also the reasons for the importance of ROI. Generally tries to measure and evaluate whether the time, financial investment, and resources dedicated to training result in tangible benefits. All of these are very variable across industries, businesses etc. both from government and wider community, employer and apprentices. Encourage audience to check through the report which provides link to online tool/calculator to try to work out the ROI. Shared examples provided through the calculator. In general, by the beginning of the 2nd year of the apprenticeship, employers start to even out and ROI rises for employers.

Summarised the key messages on ROI. Longer apprenticeships provide better ROI. 93% of apprentices who complete find full-time work in the same occupation. Group Training seen to provide good ROI. If apprentices change employers within the Group Training, there is a need to rotate the apprentices equitably so that employers are not always taking on novices and not obtaining the ROI. 

Peter then presented on the employer perspective on apprenticeships and traineeships. (see report). Australian Industry Group is an employer collective which also has a Centre of Education and Learning. Survey of employers finds 8 out of 10 employers see the importance of apprenticeships. 96% face barriers hiring apprentices. Around 1/2 indicate that they will employ apprenticeships if financial incentives were available - reduction of this will lead to less apprenticeships.

Therefore, employers weight up the economic equation, as per the ROI presented by Gary. Summarised barriers for hiring apprentices and the larges challenge was finding suitable candidates. Electrical and Plumbing have less difficulties but manufacturing has major difficulties. 1/3 indicate difficulty in training, and costs too high. Then shared how financial incentives are used for apprentices - mostly to offset costs/ reduce productivity associated with employing the apprentice. 

Warned that declining apprentice/trainee commencements are a lead indicator of future shortages. 

Discussion followed with questions around the employer/apprentice match. Why some apprenticeships struggle to attract apprentices? and trades are not promoted much at school as the general direction is still to prepare students for university. Better recruitment practices need to be supported with small businesses. Many do not have the resources to recruit and then have difficulties provisioning the training required. Chat also provided for interesting conversation within the Aotearoa context. 

Developing VET with AI - OECD report

The OECD has published their report on VET and AI - Developing VET with AI.

It is good to see a VET focused report on AI. This is especially given the role of VET in preparing people for the workforce, where occupations are incorporating AI into work tasks.

The main principles underpinning the report are: Human-centred use; ensuring diversity and inclusiveness; maintaining accountability; being transparent in understanding how, when, and for what AI is used and its limitations; and the importance of data quality, security and protection.

Policy considerations following on the principles are introduced, and discussed. These include: establishing strategy with clear purpose and support; managing risks through human-centred approaches; balancing diverse perspectives while ensuring equal access to AI; co-creating guidelines and building capacity for AI use and VET development; and strengthening data infrastructures and governance. 

The second chapter details the potential of AI in VET. In particular, to address the unique context of VET; the complexities of VET with multiple stakeholders; and to use AI to support VET development. A comparative study is undertaken across mainly EU countries with Australia data being also included.

The third chapter provides current and emerging use case studies. Policies and curriculum revision are compared across mainly EU countries. Chapter 4 then discusses the barriers and risk of leveraging AI for VET. The last chapter spells out policy considerations.

Overall, a macro/meso approach, especially comparing policy approaches across many countries. There is always much to learn from how countries handle the challenges of rapid changes as they impact on important social provisions, of which education is one of the main sectors. 

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. 

ATAIN - Navigating AI and assessment design

 ATAIN presentation on Riding the rapids, finding the pools: how AUT is navigating the turbulent waters of AI and assessment design with Dr John Davies and Dr Nell Mann from the Office of Learning, Teaching and Educational Design at Auckland University of Technology.

Irna Elgort facilitated. John and Nell introduced themselves and started with karakia. The presentation is a collaborative effort including the whole LTED team, Felicity Reid and Heather Merrick and Andrea Grant. 

Outlined AUT's approach to assessments - has principles (Mātāpono), Assessment Policies and Procedures (Aromatawai). 

Shared the main assessment principles, assessment policies (using Channel 1 and Channel 2). Naming the channels in the policy is the easy part (assurance of learning, learning is values, measured and rewarded, codesigned with staff, support for students, academic integrity, programme level design).

Covered through the presentation - a reframing assurance of learning; evidencing learning in non-invigilated settings, supporting redesign of assessments; and tclarity of assessments for students. 

Introduced the need to included manaaki into learning and assessments. Nell outlined the principles and philosophies underlying learning, teaching and assessment. What learning are we measuring? What learning are we valuing? Therefore need to reframe assurance of learning - what does it mean to assure? Should we broaden out the accepted norm of assurance of learning? 

The AUT assessment policy 'the ongoing systematic process of gathering evidence of what a students knows, and can do. Assurance is about how the process can take place and must be present in both channel 1 and channel 2. Assessments in the quicksand require redesign to move into one of the channels.

Channel 1 is assured by invigilation, channel 2 assured by points of observation of learning (POOL). 

In Channel 1, no AI is permitted. Channel 2 may include the use of AI. Channel 2 requires careful learning design of the assessment. Important to understand what happens through the assessment. POOLs take place across a range of settings in which the use of AI tools is permitted. Assessments are designed to provide insight into students' learning process beyond the final submission, ensuring that learning can be assured. POOLs can be evidence (in many forms) included in final submission. included in the rubric, encourage engagement and provide opportunities to students to demonstrate learning  - notes, screen shots, etc. Quantity of POOLs contextualised to course outcomes.

Shared an examples of POOL from a software development practice/project management - evidence from GitHub logs and project management through a Trello board. In the past, this was just an 'end-product' assessment.

Neil continued with supporting the redesign of assessments. Staff are encouraged to evaluate an existing assessment and work out how it can work in an AI world. Can POOLs be created; can POOLs be applied to the assessment and what needs to be done to re-design the assessment tasks. Creation of POOLs help to anchor the re-design. in general, POOLs weighted higher (60%) than the final product.

Clarity of assessments for students is important so that are are aware of the importance of collecting and collating relevant evidence of learning. Challenges include ensuring the things we want to measure, the need to 'look around corners' i.e. establishing an evidence base to make progress when the future is hazy. There is also a need to change long-held beliefs with students and staff. There needs to be a programme level approach. There is a shift of quality assurance from being central to local. 

Shared the impact of wearable technologies, especially its impact on Channel 1. 

Q & A followed. 

Questions revolved around the POOLs process, workload (which may increase), examples and how the process of learning can be followed through as it progresses.

Beyond skills: A capability conception of vocational education -overview

Leesa Wheelahan and Gavin Moodie have published a comprehensive collation of their work on vocational education's purposes and alternatives to competency-based education. The book 'Beyond Skills: A capability conception of Vocational Education' is published by Brill and part of the book series on 'The knowledge economy and education". It is open access and licensed under Creative Commons Attribution 4.0. 

The book has 10 chapters. Many draw on journal articles published over the last decade or so. Wheelahan and Moodie's scholarly work have critique the mechanistic, competency-driven assessment (and it turn the curriculum) for VET. They have always pushed back at the marketisation of education and sought to provide alternatives for a more humanistic and socially-responsible approach towards the provision of VET.

The introductory chapter sets out the context and the main argument for the book. That is for a shift from alignment of education to human capital theory, towards a more 'social settlement' form of VET.

Chapter 2 then presents, summarised and discusses the evolution of human capital theory. The third chapter continues on with the various approaches towards 'skill' and critique of these. In Chapter 4, micro-credentials are used as an example of how curriculum is transformed and subordinate to objectives of employability. The work of Berstein is used to unpack and better understand these concepts.

Chapter 5 undertakes to better understand the role of qualifications. Why they matter, the key theories of education and qualifications and reminds us of the true value and purpose of qualifications. 

In chapter 6, human capabilities are proposed as an alternative to the instrumentalist approaches currently standard across VET and education. The capabilities approach is introduced, discussed and critiqued. Then Chapter 7 brings a synthesis of the previous chapters to discuss the educational purposes of VET. Each of the purposes is then further expanded on and discussed in the next two chapters. Occupational purposes in Chapter 8 and social purposes in Chapter 9. The final chapter reviews the current foundations of VET and proposed a new foundation for VET.

Given the rise of AI and its impact on work, there are many concepts in the book that have relevance as the world of work shifts. At the moment, recent graduates are facing difficulties in entering the workforce. Caused by large organisations decreasing their 'graduate programmes' and lowering the number of entry level recruits.

There is advise for people to seek work in the trades - famously Geoffrey Hinton (godfather of AI) proposing plumbing as a good career path in the age of AI.

What then happens if this comes about? There will be greater competition for apprenticeships. Employers will  be supportive as they will be able to attract higher calibre people. Where does this leave school leavers who have gravitated to the trades? What sorts of jobs will be left? The restrictive nature of trades education does not (at the moment) provide a wide education, encouraging critical thinkers and provide for social cohesion. This is noticeable when I work with developing programmes of study documentation. For degree level programmes, we need to weave in academic literacies (including critical thinking) and cultural competencies. For our programmes below degree level, the emphasis is placed solely on skills and knowledge. There is no room in the curriculum for any content/topic that is not related to being able to 'do a job'. So what happens when large portions of VET graduates are 'work-ready' but not necessarily 'critically thinking citizens'? 

It is therefore important to look at alternative, like those proposed and supported through the 'beyond skills' book. We face rapid changes in how work is constituted as occupations and work tasks shift.  There is a pressing need for VET to be cognisant of these and be transformtive to meet the challenges. Without VET systems (qualification frameworks, pedagogy, strategic direction etc etc) moving towards better ways to provision VET, the populace is left to find their own way, in a difficult economic, social and political environment (sigh). 

Shaping the future of learning - World Economic Forum report

The latest report from the World Economic Forum on AI - Shaping the future of learning: Education readiness for the age of AI. Published 4th June 2026.

The report is short - 40 plus pages covering the 'new' context of education. Then a good overview of the risks of unstructured AI adoption, including the challenges AI pose on cognitive atropy; the long standing hallucinations and misinformation created by AI; AI's contribution to the breakdown in academic integrity; and the continued erosion of human connection through digitisation of modern life.

The report argues for the importance on building education readiness for the age of AI. It proposes an AI readiness framework, provides the background principles on the framework's design and how the framework can be applied.

The last section provides 'signals of readiness' for AI in education including the signs for enabling the foundations of AI readiness, along with the requirements of institutional foundations, pedagogical practices and human learning experiences.

Overall, a good introduction to the challenges with pragmatic suggestions for ways forward. 

Illuminate forum: Building capability and capacity within the VET sector using AI

 The VET Development Centre (VDC) in Melbourne hosts a day of presentations and workshops on AI. There is the option of viewing the presentations on zoom and I pop in and out as my schedule allows. Presenters would have just recently (or in the process) of completing an International Specialised Skills Institute (ISS) Institute fellowship.

The day begins with a welcome to the day, acknowledgement to country and housekeeping for the attendees at the VDC itself, from Martin Powell (CEO or the VDC) and Dr. Katrina Jojkity (CEO of the ISS Institute). Thanked everyone at the VDC for hosting the session. Provided a brief background  (and video) of the ISS fellowships which have been going since 2000 and their have been over 200 fellowships across a wide range of craft/trade skills and VET pedagogy/systems/innovations.

Craig Robertson (CEO of Victoria Skills Authority (VSA) begins with a short welcome address. Began with the quote 'we hold these truths to be self-evidenct, that all men are created equal, that they are endowed by the Creator with certain unalienable Rights. That among these are life, liberty, and the pursuit of happiness.' How does VET contribute to the pursuit of happiness? In times past, happiness was quite a different concept than its more 'frivolous' present version. In VET education, the similar attribute would be self-actualisation. Digitisation represents a major challenge to all. Task/units of competency have been the main outcomes of VET, but what happens now with AI? Education needs to now change to keeps up. We can tweak the current system but this may not be enough. There is a need to move away from task based competencies towards empower people to pursue happiness - which for everyone is always 'work in progress'. As always, Craig's summarises the challenges in a way that will be understood by the audience :) 

Notes taken from sessions:

- AI in Action: developing curriculum resources with AI with Leigh Dwyer (William Angliss) - notes on 3/4 of the session. Began with a Slido - most were 'getting there' along with their organisations ' getting there' or 'just starting'. His report had a framework of teams, tools, design, VET, Docs, ethics as the parts that inform curriculum development with Gen AI. Used this to also present on each of these with examples.

(teams) Shared a case study where a team created a game, using AI. Roles were defined, testing and feedback led to revisions. AI accelerated the workflow. Another example using Chat GPT and Grok to craft lyrics, iLovesong to make music, Leonardo to create artwork, ChatGPT and Grok for worksheets, DistroKid to publish music and Vidmuse to create music videos (for resources for English teacher training - TESOL). Album published to T-soul.  (Tools) Another example a video to help learn OSASCOMP  and discussed how to create resources which engage learners but also help them remember key concepts. Shared the work of Eric Tsui - on using ChatGPT to enhance student's personal learning.

(Design) (VET) Shared how to undertake Industry Aligned Design (IAD) - listing scenario and examples - company, role, job duties, way of working (SOP) reason to do the work. which can be used to build resources that are authentic - for instance - a day in the life of ---.

(Docs) Moved on the document management with mail merge. Workflow shared. 

- Teaching the future: Integrating cybersecurity into education. Faraz Khan (Victoria University). Report yet to be published. Began with a background on his work and the objectives of his fellowship. He visited US of A (decentralised system, high variation, education-driven approach - starting from school). Canada / Ontario has strong industry education collaboration. workforce and industry driven approach. Estonia has an integrated, system-wide digital competence. Embedded into education.

Themes include - coordination through frameworks (reduce fragmentation, shared skills and role structures, curriculum guidance, and coordination through policy and standards); Teacher capability as a constrain (requires structured learning, industry engagement and system support required); practice-based learning (using simulations/labs, work-integrated learning, and scaling these through cloud platforms and industry partnerships); cybersecurity across disciplines (across all industries, but requires sector-specific application, still largely IT-focused in practice and cross-disciplinary integration emergent). Provided examples of cross-disciplinary models in practice; and Pathways and workforce alignments (connecting education to workforce teaching - structured pathways, industry aligned learning, expand pathways, and non-formal pathways). 

Shared the various system challenges and tensions - fragmentation, sustainability, access and equity and the experience gap. Implications for VET are many - need to embed cybersecurity across disciplines, build teacher capability, expand practice-based learning and strengthen pathways and partnerships. Q & A ensued.

- AI integration for student engagement with Thuy Cao Reynolds (AMES Australia). Report yet to be published. There are challenges in the Australian workforce and VET - low completion rates in VET (50%) along with low participation rates when VET is Australia's largest workforce pipelines. Improving engagement can be useful. Engagement has cognitive, emotional, behavioural and social dimensions. These then add as forces to influence student engagement. Cognitive forces can be supported through hybrid human AI shared regulation in learning models, personalised learning and learning activity that promote critical thinking; emotion can be tapped into with game based learning to increaser fun, curiosity etc. AI can also be a team member, tutor, mentor and simulator. These influence wellbeing and change /transformation through learning. 

To test the framework above visited Singapore (SMU - chatbot to understand people and culture), Germany (VR for German language practice and ChatGPT as a language learning assistant) to see and experience AI integration. Wellbeing (through teachers acting as mediators between students and AI tools, and change management - instructor led-training, were also observed.

Shared considerations for organisations - alignment to strategic vision, invest in teaching and learning and embark on and support change management. Teachers also must be considered. Competencies and support required on how to select the appropriate AI tools as matched to learning activities - pedagogical alignment, usability, accessibility, ethics and data privacy and well-being. Shared a guide for the selection process. Thanks for presenting on two references from my work - Identity, pedagogy and technology enhanced and Ai in VET. 

Stressed importance for considerations for teachers - model enthusiasm and build trust around AI use and integrate tools to boost learning and performance. Considerations for students include the need to learn how to learn before using AI and be prepared with purpose and independence. Include learning goals, independent thinking, focused prompting, Ai literacy and learning how to learn. Proposed considerations for Department of Education and Training - quality teaching / learning and lifelong learning, future workforce and career readiness and sustainable and innovative education system development. 

Closed the presentation with UNESCO ' education transforms lives; but education must also be transformed to meet the challenges of today and tomorrow'. 

Two applied workshops of 45 minutes each follow. One with Faraz Khan - 'think like a hacker: practical cybersecurity skills for everyday protection' and Leigh Dwyer on 'building capability and capacity within the VET sector using AI'. I will need to get back to these through the recordings (along with the missed presentation earlier on).  

Magnifica humanitas - On safeguarding the human person on the time of AI

 Worth a read. Pope Leo XIV's statement/encyclical letter on AI - Magnifica Humanitas.

The argument for the primacy of human endeavours and the need to ensure that any form of technology is given deeper thought before wholesale adoption by humanity.

A brief google search will reveal many reviews, both from within the Catholic / Christian community and without.

The essence of the statement is of importance as it is a call to reevaluate where humanity is going with technology along with the free-market capitalism which funds it. There are reminders of the  many ethical issues surrounding technology. It effect, its a wake up call for many, to be vigilant and to monitor technological advances, to ensure that their adoption does not lead to detriment to the human race. 

Exploring the future of learning with Gen AI

 A webinar of the keynote and panel discussion from The Centre for the Study of Higher Education at University of Melbourne. It is an in-person event with zoom of  the opening keynote and panel session. 

Associate Professor Tim Fawns (Monash University) presents the keynote - Beyond cognitive offloading: student as a complex phenomenon. 

Notes of the presentation:

The presentation began with a welcome from Associate Professor Cochrane and an acknowledgement of country and an introduction to A/P Fawn.

Began with defining cognitive offloading - which might not be a bad thing! A sustained lack of critical thinking, through using technology, is one way to look at it. Current studies on cognitive offloading etc. have not perhaps been conducted validly. A student using AI, does not cause any form of brain damage. It is difficult to work out what students are thinking and we must not assume what students are thinking.

We move to assumptions when students use AI. We need to find out why and how students use AI. Students' practices, contexts and temporalities matter. One use of AI does not tell us much, however, intentionality matters - what are they using AI for?? 

In learning, collaboration matters. However, humans are a collective species. We need to work with others to achieve objectives. Individual knowledge matters but they need to also use this in conjunction with the milieu they are in. Dialogue with students is important to find out what they are doing with AI.

Cognitive offloading is 'the use of physical action to alter information processing requirements of a task so as to reduce cognitive demand (Risko & Gilbert, 2016). If you offload enough, the reduced task becomes the task. We offload all the time, due to the volume of information overload we encounter.

Human learning can be distinguished from 'cat learning (J. Dorn). We need to be more precise as to what we are looking at and how to better understand the values we need to protect with regard to human learning. Therefore, we cannot offload cognition that has not been thought of yet. You cannot know what would have been thought otherwise. The thing you overload to does not think what you would have thought. Offloading enables and requires (different) thinking, depending on your goals. 

There is both beneficial and bad effects of cognitive offloading. Short/long term effects are difficult to pin down. Cognitive offloading came about through work on transactive memory. A shared cognitive system where groups or couples collectively encode, store, and retrieve information. ' not traceble to any individual. Distributed cognition is the processes distributed across members of a social group, between internal and external resources, and across time (Hutchins, 2000). Therefore, it is cognitive distribution, 'remixing'.

Shared the work undertaken on student perspectives on AI in HE - AIinHE.org. The complexity and diversity of what is happening is a defining factor of the study, carried out over the last few years. Over 8000 responses show the main use to be editing/writing, brainstorming, teaching how to something, searching/researching, getting feedback (all over 50%). When an assessment task restricts AI, students think they are able to learn less deeply. 19% of students feel that being able to use AI in assessments, helps them to learn more deeply.

As an summary of using AI to undertake summaries, students found that it saved time, helped understand key concepts, manage heavy reading loads, engage with complex or unfamiliar (over 50%). Most students say they read the original text, as well as the summary.

Therefore, there is a big, messy and diverse mix, including resistance, low trust of outputs, varying confidence in their ability to use AI and worries about learning (Jung, 2025) AI is embedded in different ways. AI feedback seen as less trustworthy, less relevant, clearer, more 'objective' and less emotionally fraught (Henderson et al., 2025). Students were concerned about dependency, needed to trust themselves and their processes and were developing moral and ethics (Bearman, 2025).

Optimism, guilt, scepticism, relief, moral boundaris, fears ---- complex moral negotiation (Oberg et al. 2026). Things 'stick' to AI including alarm, distrust, enthusiasm and hope. 

Therefore, many students are worried about becoming lazy and taking ahortcuts. Overall, thoughtful. 

Shared work at Monash with a focus on evidence of learning. (Fawns, Boud, & Dawson, 2026) pm targeted learning to focus not only on product, but the performance, process and practices. Important to help students leverage off AI. However, the practices are still emergent and need to be better understood.

Questions on assessments include - are learning environments appropriate for encountering students and what they can do? Do assessment tasks allow demonstration of learning outcomes via a range of proxies? Are the conditions appropriate to generate evidence of learning? Are the evaluation methods appropriate to the evidence?

Therefore, AI relate beliefs and practices are as diverse as those of staff. AI in education is an even bigger, and more emotional and personal challenge. Students need educators who understand all of this and help them navigate. Competing demands, the competitive nature of HE, eroding trust between students and institutions are perhaps more important. 

Q & A ensured. 

Panel discussion followed (I will need to catch up on these in the recording) was moderated by Dr. Shannon Rios with Laura Chambers (board director at Mozilla), Dr. Solange Glasser (University of Melbourne) and Jim Hsiao (University of Melbourne).

Weekly collation of AI news - Ai and the future of AI & The AI Corner

 With so much 'news' and commentary on AI in education, it is difficult to keep up!. I have subscribed to these two 'news feeds' or collations to try to keep up with the flow of updates, issues, and discussion.

1) Nick McIntosh - AI and the future of HE

Nick posts on LinkedIn each Monday. Having an account is useful but not compulsory. This week's post covers various relevant publications, news on NVIDIA and Micorsoft moving AI off the cloud on onto your desks, and the Pope's Magnifia Humaitas.

2) The AI Corner

Subscription to the AI corner and a weekly (Monday) email is posted into your inbox summarising AI developments of relevance in Aotearoa NZ. Recent new is summarised  through a commentary along with updated happenings across the major AI providers - Anthropic, Open AI, Microsoft, Google/Deep Mind etc.

The above safes me time but serendipitous finds through LinkedIN, Google News feeds, Google Scholar alerts etc. still yield scholarly material :) 

ATAIN - Human-led, tech-empowered: Evaluating educational AI tools for impact, ethics and pedagogy

 Notes taken from the monthly ATAIN session.

This month, Joan Sutherland and Associate Professor Trish McCluskey Director Digital Learning from Deakin University on 'Human-led evaluation process: learning and teaching.

Joan presented, beginning with a acknowledgement of country and emphasising the human in technology.

Asked for what tools are used and why are these used.

What are the challenges? Drew on Laurillard (2012) Teaching is Design - knowledge acquisition, collaboration, inquiry, production, discussion and practice to place emphasis on the pedagogy and not on the tool itself. This was to address what tools, when, what good practice looks like and where to get support. 

The initial evaluation surfaced the following: subjective view, lack of transparency, manual process, security risks, AI integration, workflow diversity, lack of alignment, duplication.

An explicit process required and aligned with institutional direction. Therefore, the current process was mapped; alignment and gaps identified; what does the research say? defined the ideal process; align and refine; how can automation be leveraged? 

Shared process that was initiated. A new request is raised, need analysis and alignment, research and tool selection, pilot and test, evaluation and recommendations, implementation, ongoing monitoring and support, and evaluation for license renewal. The process is visible to all staff at the university. Each stage is recorded and available so that progress through the evaluation process is shared. 

It is important to do the needs analysis is a human-led conversation to provide consistency, one source of truth, alignment, transparency and to avoid duplication. To identify gaps/duplication cover what challenges will the tool address? which activity types does the tool best align to (as per Laurillard and pedagogy approach) ? what key features expected of the tool? what specific tasks must this tool support? the tool is evaluated against a function and a feature matrix. 

AI is challenging as it is probabilistic and will not provide the same output consistency. Privacy and cybersecurity are added challenges. Cross cutting principles include privacy-by-design, data minimization, security by design and ethics and compliance. Therefore, context needs to be taking into account along with user experience, AI components (transparency, clarity, relevance, usability, integration to ensure strategic alignment and pedagogical impact.

Shared an AI tools heatmap evaluation to help users/staff understand all of the above parameters. 

Impact measured using SAMR (Puentedura, 2006), does it enhance and transform? However, it does not reflect the complexities of AI. Therefore, adding the layer of people, process, practice may help to provide a bit more representation for the wide range of AI.

A good overview of a process to evaluate technology tools that support teaching and learning. Q & A followed. 

However, my take is that perhaps we are trying to fit a problem into an existing framework. AI is especially tricky as it is what the user does, that actually defines its pedagogical role. AI is therefore not a tool but more of a 'social-cultural' partner. It can be used as a 'sage on the stage' giving answers, a 'guide on the side' to support nascent conceptualisation and learning, or 'a muddler in the middle' a socratic opponent, thinking partner etc. AI literacy for our teachers and then in turn our students is a major key to reach the potential use of AI to support teaching and learning. Learning becomes a hybrid of human+AI rather than a 'tool'. 

AI likely needs another evaluative process. 

Mysterious brain - Royal Society Te Apārangi presentation by Emeritus Distinguished Professor Cliff Abraham

 Notes from last night’s presentation organised by the Royal Society Te Apārangi on ‘Our mysterious brain: the making and breaking ofmemories’. 

The session is presented by Emeritus Distinguished ProfessorCliff Abraham - who worked for many years at the University of Otago.

After a welcome from the Royal Society and ‘housekeeping’, Professor Abraham is introduced through a background of his long research career.

Began with an overview of the parts of the brain, its structure and the function of various parts. Then the microscopic structure of axons, nodes (90 million ++) and the speed at which it works. Defined learning as the process by which experiences change the nervous system and hence behaviour (referred to as memories).

Summarised memory hyper-functionality during early development. Psychiatric disorders (psychosis, PTSD) and additions also bring about hyper-functionality. Memory hypo-functionality occurs and exampled by amnesia and dementia.

Mechanisms of memory storage through neural connections include dendrites receiving inputs and axons sending outputs. The synapse forms the connection between axon and the spines from the dendrite through neurotransmitters (glutamate, dopamine, serotonin, adrenaline, histamine) and electrical activity. Synapses are work-horses of memory, there are 1015 of them, they are metabolically active and individually modifiable. Astrocytes are also in the mix. All densely packed together.

Summarised the ‘making of memory’ through from the early 1900s. Long term potential (LTP) or depression (LTD) allows for modifiability (plasticity) of synaptic transmission. If the LTP is blocked, impairment of spatial memory formation occurs.

Therefore, does altered plasticity contribute to memory impairments in neurological disorders? Can knowledge drive new cognitive enhances and disease therapies.

Introduced Alzheimer’s disease and its effect on the human brain (lost of large amount of brain cells and inclusion of plaques and tangles). Causes neuroinflammation, synapse dysfunction / loss and nerve cell loss.

From a research and clinical perspective, understanding the process helps inform prevention/delay, lead to earlier detection, and towards more effective treatment.

Prevention involves ‘using it or losing it’. Good diet, weight control, physical exercise, good quality sleep, and keeping up with mental and social activity. Early detection of plaques with ‘PET’ scan. Blood tests being developed for early stage Alzheimer. Shared work at University Otago on ‘microRNA’ that may be a useful contribution.

Treatment – new drugs increase brain ‘tone’ – about ½ of the people taking these drugs experience modest improvement in cognition. However, effective treatment needs to be more effective, long-lasting, non-invasive, have a brain-wide delivery, cross the blood-brain  barrier, have few side effects and be affordable. Some progress presently on antibodies that remove plaques from the Alzheimer brain. Presently not widely available, very expensive and only deal to the plaque, not the tangles.

Stressed the importance of building brain resilience and maintaining cognitive reserve. Persons with brain resilience hold off dementia for longer. Shared a new treatment strategy to amplify production of neuroprotective proteins. How can these specific proteins in the brain be increased. Gene therapy approach alters cell function at a genetic level to generate a therapeutic outcome. For instance, to make more of its own neuroprotective proteins eg. sAPPa. Explained how virus-mediated gene transfer can be used. The gene encoding protein (sAPPa) is packaged into a virus shell (Trojan horse). This package is administered (injection – intracranial, intravenous). The gene enters the nerve cell nucleus, the virus shell dissolves and the protein enter the cell.

Trial of above through intracranial virus injection increased sAPPa rescued spatial memory in mice with Alzheimer. Also reduced plaque development in the hippocampus and the cerebral cortex. Future work on a human-ready virus shell. The hope is to increase neuroprotective proteins in the brain. 

An interesting foray into neurobiology and neuroscience. 

 

Future postdigital classroom - Special issue of Postdigital science and education

 The September 2025 issue of Postdigital science and education focused on the topic of the future postdigital classroom.  

The special issue was edited by I. Forsler, E. Bardone and M. Forsman.

There are 20 open access articles covering a range of topics. Each is provides interesting perspectives and provoke thought and trigger further investigations. Most are schools or higher education focused but frameworks and discussions are useful to inform VET.

- Walls come tumbling down: imaginaries and materialities of the postdigital classrooms by the editors sets the scene for the issue. The objective of the issue is to envision, discuss and critique the 'future postdigital classrooms' and on how technology impacts on teaching and learning. ChatGPT was used to generate images of a classroom without walls and found it wanting as it drew on the historical conceptualisation of classrooms with desks, chairs and whiteboards. The goals of the issues are to understand the dominant imaginings and narratives of a future classroom; how educators enact and negotiate these narrative; what methods or approaches can be used to imagine the future; can such futures be translated into the physical world; what are the boundaries of the classroom and how can the risks and promises be met or transcended?

Articles are then briefly summarised.

A 'pick and mix' of the articles for a first reading through recommended as there are many ideas introduced through the chapters. Then a focus on the pertinent ones will pay dividends. A recommended read. 

AI is not the answer, it is how it is used to support learning which is the key

 Some learning from chalkbeat, reporting on why the Khanmigo chatbot has not yet met its promised goals. 

Three years ago, an AI chatbot was launched in Khanmigo. Uptake by students has been lukewarm. The Khanmigo chatbot was used by students to find answers, rather that as a 'study buddy'. The key seems to be, as always, to educate students, rather than for them to just try things out. 

A recent German study to evaluate the relationship between AI-chatbots, student assessment performance and learning outcomes in Higher Education,  The findings indicate that students may be able to complete tasks faster, but not better or lead to higher grades.

Again, it is important to plan carefully, the objectives of using AI to support students. Are the chatbot/agents used to support learning? If yes, what are the specific learning objectives? Is the chatbot/agent 'ring-fenced' sufficiently to actually support the attainment of the learning outcomes? In our current projects, we need to be very clear about how and why the chatbot/agent is being utilised. This helps delimit the range of the chatbot and to ensure that it stays on task and does not deviate from its assigned objectives.