Inquiry in action: Using AI to reimagine learning and teaching: Case studies from the frontline of Higher Education practice

 This open access book, collates a series of case studies from the University of Queensland on 'Using AI to reimagine learning and teaching: case studies from the frontline of higher education practice.

It is edited by Rachel Fitzgerald. 

The book begins with an introduction from the editor, followed by 12 chapters. There are 11 'case studies' with a final collation of themes chapter. 

There are chapters on AI literacy (chapter 1); ethics (chapters 2 and 3); inclusiveness (chapter 4); subject-specific chapters (1 - health, 4 - dentistry, 5 - dietetics, 8,10 -economics/business); inquiry-based learning (chapter 6); Critical thinking (chapter 7(; web/mobile development (chapter 9); and pedagogy across most of the chapters.

Useful for providing examples of the may ways in which Gen AI can be integrated into learning activities.

ATAIN - #3 presentation for 2026 - Dr. Brendan Sheridan on 'old problems, new tech

Today's presentation is from Dr Brendan Sheridan, Teaching and Learning Developer from Te Puna Ako - Centre for Tertiary Teaching and Learning, University of Waikato.

The abstract is: This talk discusses the various factors driving use of Generative AI by students, in particular unauthorised use of Generative AI. It applies an adapted framework of Unified Technology Utilisation and Acceptance Theory 2 proposed by Bouteraa et al., 2024 and compares it to the Academic Integrity Motivation framework of Murdock and Anderman (2006)

Presented on 'motivation factors for Gen Ai use in tertiary education. Covered the framework above (Bouteraa et al.); overviewed more literature along with student engagement along these parameters. The moved to Murdock & Anderman and the case study at UoW.

Summarised the UTAUT & UTAUT2 which is a large framework. Bouteraa et al's driving factors for understanding the diffusion of Gen AI. The second framework on motivators for using Gen AI is tighter and more aligned to Gen AI.

Moved to short review of the literature (6 readings). Themes include Gen Ai being easier to get into then previous AI tools; media commentary and social discussion about Gen AI increase student's willingness to use it. With educational self-efficacy, use of AI connected to a sense of succeeding academically. Some use it as a reflective tool and refine thinking. However, solid disciplinary knowledge needed to use Gen AI effectively. In technological self-efficacy, many ways to use it positively - improved productivity, ability to synthesise content etc. Risks of privacy and transparency acknowledged.

Personal anxiety picked up - performance academic anxiety drives adoption of Gen Ai tools, however, academic integrity affected. Perceptions that Gen Ai use is unethical, this leads t cautious adoption of AI, overly embracing AI content lead to assuming students used AI for assessments, and sceptical students avoiding AI altogether.

In general, contextual and individual influences may push students towards breeching academic integrity.

Commonalities between the frameworks are that the purpose, is weighed up with can it be used and the costs of being caught.

UoW case study (Fester, 2025) on taught Masters programme. Some came from work where Gen AI was used. Students co-constructed AI policy with lecturer. 50% used Gen AI to complete assignments. 74% of students completed the survey.

Awareness of AI and integrity through co-construction of the Ai policy. Students felt well supported and appreciated importance of Gen AI in future work and learning. Various tools were used - Chat GPT, Copilot, Grammarly, Deep Seek. Used to explain concepts, check grammar/spelling, improve / proof read writing, summarise readings, draft communications.

Student perceptions indicate academic integrity policies on their own are insufficient. Saw Gen AI as cognitive/research assistant. Used critical engagement to filter information. Aware of limitations and challenges. Perceived that lecturers need to rethink assessments. Inconsistent messaging across programme on use of AI. 

In general the students' motivation factors was on performance, effort and social dimensions. There was awareness of Gen Ai limitation, critical engagement with AI, inconsistent messaging across programme alleviated by lecturer and awareness of academic integrity and understanding the inappropriate use of Gen AI.

Moved to teaching and instructional design response a UoW. Shared the factors around staff engagement and the active PD provided to support lecturers and impacts on self; and across the university. 

Considerations for the future: Bouteraa et al framework useful towards understand students' motivation. Motivation and use are not the same. important to mitigate users' anxiety; integrity not only around use but to support student's appropriate use of AI; external factors like user training and clear assignment instructions can help mitigate ideas for self-efficacy and alleviate user anxiety. 

Q & A followed. 

Microsoft Copilot - supporting research

 This article, was published mid-2025, providing an overview of the impact of Copilot researcher and analyst agents on work. 

Having now used both for 6 months plus, my take on these two agents, is that they can be useful, but need to used with care. 

1) working out what is to be done is important. Responses from researcher or analyst agents, arise through the prompts provided. Careful structuring of prompts is therefore essential in obtaining the types of actions required. Otherwise, researcher may go off topic quite easily.

2) providing context is important and delimiting the researcher/analyse agents to specific papers, websites or attachments help ringfence the direction of responses.

3) using the prompt writing agent in Copilot can be useful for tightening prompts.

4) ensuring that 'work or 'web' is selected, along with depth of responses (auto, quick, think deeper) helps again to ensure responses fit expectations.

5) Triangulation is always required, to check the validity of the responses. Limiting resources also help to save time, so that triangulation is restricted and does not have to go all over the place.

6) Draw on the advantages of AI. Summarising key points, comparison of key points across papers/sites, drilling deeper to extend insights, providing 'neutral' perspectives on conceptualisations, frameworks etc.

7) be aware of 'cognitive debt' / 'cognitive atrophy' and how this can come about very easily when your critical thinking is replaced by AI doing the work. You still need to read deeply, cogitate, make your own judgements and come up with your own synthesis. Then use AI to cross check these and see if it provides other insights which are viable.

8) Continue to learn how to manage AI to draw on it's ability to automate some research processes. The key is to use AI as a thinking partner, not to replace your own effortful thinking.

Copilot agents

A bit of 'research' into Copilot agents this morning, following on from yesterday's session on building agents in CoPilot. 

Microsoft 365 Copilot Premium (now often simply M365 Copilot) offers "declarative agents" designed for lightweight, personalized tasks using organizational data, managed within the M365 environment.  on the other hand Copilot Studio enables creation of advanced, custom agents with complex, multi-step workflows, API connections, and full lifecycle governance. 

Microsoft Copilot Studio in New Zealand is generally licensed as a tenant-wide capacity 

pack, starting at approximately NZ$323.60 per pack/month. This subscription provides 25,000 "Copilot Credits" monthly, which are consumed when agents complete actions or responses

The cost of Microsoft 365 Copilot in New Zealand varies depending on whether you are 

purchasing for an individual or a business, with prices generally starting around NNZ$34–$40 per user/month for business subscriptions

Microsoft 365 Copilot for Education is priced at approximately NZ$30–$32 for academic institutions. This specialized academic license provides AI-powered assistance for faculty, staff, and higher education students, acting as an add-on to existing Microsoft 365 A3/A5 license.

Templates for business type agents include a Quiz tutor template and a series of  'assistants' for various job tasks including travel planning, peer feedback agent, training content writer.

A guide for educators  provides ideas for using agents in educational settings. 

Overall, there are good possibilities :) 

Microsoft - introduction to building agents

 The last in the 'back to campus series' offered through Microsoft (based in Australia). 

As with the other two sessions I attended, Jennifer Ruan is the facilitator and Victor Kochetkov does the demonstration.

Notes taken during the session:

Covering what are agents, what tools exist, to through building an agent and Q & A. 

Explained Copilot as a user interface for AI. Currently there are agents accessible through Copilot and also customised agents can be build in individual copilot accounts.

Copilot is for human augmentation, private, personal assistant and 1:1 interaction.

Agents connected to Copilot, chat or autonomous and can contact with other agents.

Out of the box agents on Copilot include surveys, researcher, analyst etc. If (frontier) then they are in initial phase.

Copilot is off the shelf, retrieval only and connects to Microsoft 365 only. Copilot Studio provides task/autonomy and for developers with more complex task. Developers can also build customised agents with Copilot Studio + Azure AI.

Went through Copilot - using 'new agent' on the left menu to access. Generally, describe what you want to do, configure the agent by adding knowledge and capabilities, try out as it is being build and then use/share with others. 

Copilot agents can be shifted across to Copilot Studio to make them more sophisticated. Studio has more comprehensive tools, wide selection of models, able to publish to multiple channels and has more powerful orchestration. 

Agents generally retrieve information and reason, summarise etc. They can also take action to automate workflows and replace repetitive tasks. Automous agents will operate independently, plan, orchestrate other agents, learn and escalate. 

Example in education, an IT helpdesk agent, devise refresh agent, research tracker agent, budget management agent, study guide agent, student support agent etc.

Note: agents build in premium cannot be used by others who only have access to Copilot basic without extra billing!!

Demonstrated how to create an agent. I create one to compare Learning Outcomes against NZQA criteria in 2 minutes! Also, ask prompt agent or chat to help create the agent, providing the best prompts to use. Copilot studio has help and examples, along with templates for creating agents. Analytics are also available. Evaluation also possible, to test an agent. Remember to use AI to do the work where required. 

Discussion on who will see or have access to the agent as various people in the institution have access to various type of Copilot (basic/premium). Also with each type, there are functions that some have access to and others do not :(

A link from Moodle for a agent will work - if the learners have the right version of Copilot and use it within their Ara digital environment. Otherwise, Copilot Studio needs to be used. 

Another series later this year is seeking pre-registration - Future ready with Copilot.

Cowork by microsoft - alternatives

 Yesterday's microsoft presentation introduced Cowork. To have this available in my institution's Copilot premium, requires the turning on of access to Claude. I can see some advantages to having Cowork, as it automates tasks which are carried out, often across several apps, regularly.

An AI query (on Google) reveals that all the other main LLMs have equivalents. Claude itself has Claude Cowork. Open AI has 'operator' which costs US$200 a month. Google has Project Mariner. Manus and even Amazon (Nova Act) also have similar capabilities. 

Plus, there are a whole host of  enterprise tools - Eigent, OpenClaw,  Composio etc. O-mega offers an overview of 10 Claude Cowork alternatives 

Therefore, agentic AI is now mainstream and will have further reaching implications on work and education than Gen AI itself. 

Microsoft - Copilot chat for researchers

 Notes from a session with Microsoft on how researchers can use Copilot chat (M365 copilot (licenced) for researchers (aka Copilot premium).

The same microsoft representatives hosts and deliver the workshop.

Jennifer Ruan is the facilitator and Victor Kochetkov does the demonstration.

The session explores literature reviews, data analysis and research documentation.

Shared recent CSIRO's six month M354 Copilot trial with 7,400 Australian Public Service staff. In general, 1 hour saved each day with ability to reallocate 40% of time to higher level research activities (analysis, discovery and strategic thinking). Copilot can assist with literature reviews, grant applications, meeting and collaboration time, data analysis bottleneck, document drafting.

Demonstrated upload of document to interrogate it with the standard chat. In Auto, there is ability to select different LLMs (we seem to only have ChatGPTs but access to Sonnet, Claude etc. possible). Used notebook (only on premium) to store responses along with how to bring the sources /suggested references and sites into the notebook. Then how to share notebook. Audio summary is available (quick create button) similar to capability in Notebook LM. Study guide is available (but not on my version of  Copliot). The chat next to the notebook has the option of bringing in the Researcher agent (button not to the +). 

Then when through how to use Analyse agent to summarise trends in an uploaded Excel files. Then transfer of these into pages by using the edit in pages button (icons at bottom of response).

Copilot notebook is like Onenote (storing a variety of files). Copilot pages stores responses. Onenote files can be uploaded into notebook or chat to be used for analysis etc. by Copilot. 

Excel and powerpoint agents are also not available on my version of Copilot :( 

Previewed the 'cowork' agent which will be avaialble (for some probably!!) next month. This seems to automate tasks like organising your inbox, organising your week, prep for a meeting, research a company, find files and merge or bring files together in a certain way or for a certain purpose etc. basically pre-prompted tasks. Needs Claude to work so if this is not in your LLM list then need to work with IT to see if it will be available. 

Need to check with local organisational IT for access to LLMs other than ChatGPT and also for Excel/ Pp. However, for Excel and ppt, Copilot integrated into these and can be used when each is opened, just not connected to the Copilot premium chat.

A bit of a marketing at the beginning and usual whizz through all the various items. Will view the recording again to catch up on missed items!

Generative AI in education: Theories, applications and ethical frontiers - overview

 This book collates 21 chapters on how Gen AI is shifting education and the role of educators in understanding and utilising AI to support teaching and learning.

The book is edited by G. Durak, S. Cankaya and M. Sharples with chapter authors from Europe and Asia. It is not open access and the short pdf available provides a  preface, and list of chapters and authors.

A good selection of topics is collated through the book including:

- sustainable education - chapter 2

- classroom orchestration - chapter 4

- lesson planning - chapter 5

- deep fakes to voice cloning - chapter 7

- learning analytics - chapter 8

- smart learning environments - chapter 9

- VR and AR - chapter 10

- AI literacy - chapter 11

- Prompt design - chapter 12 & 13

- dialogic feedback - chapter 14

- creative learning - chapter 19

- ethical considerations - chapter 20

- teacher training and PD - chapter 21

Will recommend the book to the library and add chapter summaries after I have looked through them. 

MIT - unified framework of five principles in AI society

 This article, A unified framework of five principles for AI in society, written by L. Floridi and J. Cowls in 2019, provides a synthesis of other frameworks. The work predates the arrival of ChatGPT but the principles are even more important now as Gen AI moves towards becoming Artificial General Intelligence (AGI).

Table 1 in the article summarised where each principle is also present in 9 frameworks. The principles are beneficence, non-maleficence, autonomy, justice and explicability. These concur with the principles published of late, calling for increased ethical actions as Gen AI and agentic AI take hold. 

From personalised to precision learning

This paper from Educause was in George Siemen's presentation last week. It proposes a tightening of personalised learning through 'precision learning'.

The paper was published in Novermber 2025 with authors from the U S of A - 

Tanya Gamby, David Kil, Rachel Koblic, Paul LeBlanc, Mihnea Moldoveanu and George Siemens.

The article proposes a 'computed curriculum' using AI to generate and deliver content and activities dynamically.

An important first step is to review institutional data architectures so that they can be drawn on to support the demands of adaptive and personalised learning. Real-time adaptivity is required so that 'just-in-time' feedback is availed to learners. Hence, in the article, the following is required:

"Delivering real-time recommendations and interventions that improve learning outcomes requires a fundamentally reimagined architecture. Instead of static, siloed data collection, institutions need systems capable of dynamic ingestion, immediate processing, and centralized analysis of learner interactions and performance. Such an architecture might leverage event streaming platforms, robust APIs, cloud-native databases, or other technologies to make data available and actionable the moment it is created. With this shift, educational systems can identify learning gaps, trigger personalized recommendations, and adapt curricula in real time—moving from post hoc analysis to proactive support."

The combination of agile learner data and LLM can then allow for real-time support and intervention. Then, combining the above with learning profile and curriculum leads to 'precision learning'.

The paper provides a way forward, explained in lay language for those with little computer science background. Now the first steps are to find out how my institute stores their learner data and see how complex or large the task ahead will be to format and provision precision learning!

The precursors to this article are also worth a read - Ai tsunami is here (2025 - Sept); and Dialogue at scale (October 2025).

Aotearoa AI Tertiary Network (ATAIN) - George Siemens on 'AI in Higher Education"

 Session 2 for 2026 from ATAIN with  a presentation from Professor George Siemens on 'How AI changes practices in higher education'.

Abstract of the presentation: 

After several decades of bold proclamations and unending hype of the future of learning, from Web 2.0 to open courses to flipped classrooms, artificial intelligence arrives in our university classrooms at a moment of change fatigue across the sector. This presentation will explore how AI impacts learning and knowledge practices, focusing on which specific tasks, now done by humans, are most amenable to AI. System level Implications of the core change of “what is done by human cognition and what is done by artificial cognition” will be explored.

Notes:

Mark Nichols introduced George. 

Began with the conundrum represented by the arrival of AI. Too much is changing and things are moving very fast. Almost impossible to anticipate what is going to happen. AI said to replace software developing but the data does not hold up on job replacements in this area.

We are currently moving from chatbots to agentic AI. Many platforms being launched and many people using, experimenting, evaluating. Check podcast - Software developers provide the idea but AI does the coding. Examples out there where coding is being done by AI by startups etc. 

Provided an example of how Claude can work if provided a folder of sources - pdfs, reports, etc. The ppt created is accurate. Therefore AI becoming a work bot. Then put the ppt back into Claude to tidy it up and 'approve' the various items that will be used to build the slides. Therefore, one 'manages' AI . 

Started the main presentation with assumptions that we are familiar with Gen AI, multimodal and world models, reasoning models, advances in models and encroachment into human capabilities. The uncertainty of labour market impact and that negative aspects of AI (bias, hallucination, IP abuse, environmental and human harm etc.)

Postulated that with distance education in 2002 - open education helped scale content. Then in 2008 open courses scale instruction and now, perhaps ability to scale engagement. 

Benefits - personalised learning, positive influence on learning, reduced planning and admin, greater insight into student understanding but negatives in ethics, need for learning design for AI.

All the AIs are dropping LMMs - Claude for education; chatGPT study mode etc.

However, students tend to rely on AI, rather than learn from or using AI :( 

Explained how AI LLMs may work. We can not just send students to Claude/ChatGPT to learn; the value add for education is the structure, curriculum, pathways, learning support etc. which are required to help novices learn specialised knowledge. Therefore connect learner profile and content knowledge, through systems prompt/context window (LLM) and compute personalised curriculum in the form of learning content, learning activities which matches the preferences and profiles of the learner.

Agents in higher education can support:

recruitment/registration; wellness support; guide and direct through university experience; create content; teach and coach; assess and evaluate; research. Therefore agents will be LMS, textbook, assessments, teaching, tutoring, apps etc.

Software engineering provide examples of what will happen. In the last 18 months, companies have been built in a weekend; product speed is accelerating and this will happen across many 'knowledge work'. 'Its building coalitions that work - issue by issue, with partners who share enough ---

Stages of engagement:

personal - join open spaces and contribute (your blog, huggingface, share your learning); 

coordinate: across institutions, share governance, share strategies and resources.

systems level:

Agency is important as individuals. We can create with AI but there is importance in first defining, thinking, planning and develop the skills to monitor and track what is available.

Encouraged getting lined up with key AI tools and the infrastructure that supports them. Git, Obsidian and file systems, skills and similar repeatable processes and start taking all the free courses (OAI, Deeplearning.ai, Anthropic, Gemini). 

Q & A followed.

As a summary, things are moving rapidly and there is no turning back. As individuals, need to keep up with the play. As institutions, need to be pro-active, collaborate and resource innovation/change.

World Economic Forum - Four futures for jobs in the new economy: AI and Talent in 2030

The World Economic Forum published a white paper in January 2025 on 'Four futures for jobs in the new economy: AI and Talent in 2030.

It is a short report - just 20 plus pages. 

The report is based on their annual survey of 10,000 executives (globally).

The scenarios are:

- Supercharged progress

- The age of displacement

- Co-pilot economy

- stalled progress

Each is presented and discussed and as usual, there is no right/correct way through, but perhaps a combination. National and social imperatives - including workforce readiness, actual progress of digital and AI technologies, political environment etc. will dictate national, regional and global effects.

For education, it will still be a time of rapid change. Whether education can keep up is dependent on many variables including capability, capacity, resourcing and future vision. Best to keep moving along with building capability as all innovations will be founded on human interactions and reactions.

Microsoft Copilot for educators webinar

 Notes taken from Copilot for educators webinar this afternoon. 

The session hosted by Microsoft  based in Australia. Beginning with acknowledgement of country and instructions for live captions and transcriptions.

Hosted by Jennifer Ruan (overview/facilitator) and Victor Kochetkov (demonstrator).

Started with running through the 'Teach' module with its various teaching tools. Tools are specific to sectors. For example, alignment to standard for school sectors. Went though 'create lesson plan', attaching files (allows specific standards to be added) and the drop down menu. UK English will be available soonat present, only American English. Once the lesson plan created, save to onedrive as a word doc.

Standards for vocational education in plans to be added for Australia. 

Demonstrated how to then draw on the lesson plan that was created to generate lesson notes/handouts using 'new chat'. Then showed how to edit the handout in Notes and then add it to a Notebook. 

Advised to use custom instructions (in settings) to provide specific instructions that cover the tone and specificity of AI responses. 

Then showed capabilities in 'Create'. So infographics can be created from the handout/lecture notes. Now stored in the 'Library'. Then did the same with powerpoint which should have organisational template available. Images etc. for ppt are from microsoft pool for copyright accreditation or AI generated. Institutional images can also be availed. 

Then used new chat to compare transcript of the lecture with the notes to identify gaps in delivery.

Next, demonstrated rubric creator in Teach module. Description only allowed, as no download/attach file capability yet. 

Then showed how the quiz creator works. Created a quiz into microsoft forms. Then used Analyst agent to do a analysis of the quiz responses (converted into excel spreadsheet). Then using the analysis, create another lesson plan which addresses the content that students did not achieve in the quiz. 

Then went back to 'create module' to create a video based on the ppt slides with a voice over.

Lastly, focused on notebooks - to collate items in one topic and how this forms the base for use in different ways. Especially for putting parameters on AI reference for responses, to create quizzes, flashcards etc.

Q & A ensured.

Many of the participants seemed to not have used copilot M365, so time spent to show how to access and where the Teach module is, how to  navigate through Copilot and use the various icons, enterprise/organisational data security etc.

Presentation recorded for further review. 

Case studies - AI - special issue of International Journal of Designs for Learning,

 The International Journal of Designs for Learning published a special issue on Gen AI in learning design at the end of 2025.

There are 30 articles, including 6 'short-form design cases.

There are 8 case studies followed by a special section with 16 articles on learning design for Gen AI.

An editorial by the special edition editors, opens the issue. Articles and themes across the issue are summarised

-Gen AI as a facilitation tool for learning workflow

- Gen AI as a site for AI literacy and critical thinking

- Gen AI as a creative and material partner

- Gen AI, ethics and the work of 'holding the line'

- Designing with Gen AI in a rapidly evolving landscape.

Of note for learning design in the VET  context are the articles:

- G. Fares' article Ch(AI)r: Advancing furniture design through AI craftsmanship - using poetic prompts to generate images using Midjourney and DALL-E. The images are then used as starting points for students' engagement with materials to create a chair.

-  Capturing elusive technology: designing a course on Ai for learning and development practitioners by Da Silva - the learning design of an asynchronous online course for learning desigers.

-  J. Yu and H. Rho on 'just seeing can be deceiving: Gen AI - supported design case for critical visual literacy -  uses AI as a 'cognitive partner' to intentionally create misleading versions of students' data visualisation to encourage and learn critiqueing skills.

-  R. M. Quintana, C. Quintana and M. McCurry on 'unpacking design of an online course series - Gen AI as a learning design partner - presents and discusses the opportunities and applications of Gen AI for supporting and enhancing learning design activities

- Implementing AI course assistances: a rapid design case from concept to full rollout at Los Angeles Pacific University by G. Henshaw and M. Wilday. Used AI as a Socratic partner to support greater student engagement, critical thinking and motivation. Involved faculty as co-designers. 

-  Davis. J. Utilization of ChatGPT to create materials of flipped classroom. - Use to revise pre-class resources and found that develop that it as effective in saving resource development time, improvement in student outcomes noted and quiz questions did not have as many mistakes. 

- Brinkman, E. - redesigning an introduction to writing assignment in the age of AI - emphasised the use of AI as a writing collaborator. Worksheets, scaffolds for learning and prompts are shared in the article. 

- Designing for AI literacy: a modular, Gen AI integrated course interdisciplinary graduate students in education by N. King and J. Yan. - describes the development of a graduate seminar to explore what Ai is and how to use it. 

Many of the articles provide good examples for educators as to how to incorporate AI into courses/programmes. Projects drew on disciplinary and constructivist pedagogies, with AI used to support rather than replace learning. Overall, a good resource to show how AI integration needs to be founded on Ai literacies, good understanding of pedagogy and the learning contexts, and the reflective practice required to utilise technology to enhance learning. 

Short papers from 2025 eportfolios Australia conference

 Short papers from the 2025 eportolios Australia conference are now available. 

There are 8 published papers.

- From foundation to practice-the journey of co-designing an eportfolio that supports reflective, competent occupational therapy graduates. The project was undertaken at the University of Tasmania - Associate Professor A. Hamilton, H. Titmuss, Professor A. Berndt, S. Batur, and C. Hunter. A new programme, so the opportunity to create eportfolio for assessment and learning to support student's professional progress was undertaken. Details the process and principles for programmatic assessment and eportfolio practice.

- Beneath the surface: advocating and influencing eportfolios practice - Dr. I. D'Souza and C. Sapsed from Monash University. Presents the work of educational designers on using an adapted TPACK in humanities and health disciplines. 

- Developing global competencies in agricultural sciences: eportfolio assessments as a catalyst for global citizenship and leadership in agricultural education with T. P. Nguyen, Professor S. Schmidt and Dr. N. Robinson from University of Queensland. Mixed methods survey of students to gauge their perspective on whether eportfolios contribute to supporting professional skills development.

- Authenticity in the age of AI: A framework for eportfolio assessment based on process, provenance and persona by N. Taptama from the University of Queensland. Details a framework to record the learning journey as AI becomes integrated into programmes of learning. The framework includes the PROCESS to capture the learning journey. PROVENANCE as a way to make visible and evaluate students' progress to document, synthesise and appy learning. PERSONA focuses on the unique human qualities students bring to the process.

- Resolution of building resilient eportfolios for online higher degree by research students by M. B. Fisher from the University of New England. Records the processes and journey of PhD and MPhil students using eportfolios to support their learning journey and the supports and strategies required to support them.

- Finding the sweet sport: Portfolios, programmatic learning and student belonging - H. Pate and R. Scriven from Edith Cowan University. Details the merging of programmatic learning with a whole course portfolio to help students engage with learning and build a sense of belonging to their profession.

- Making audience tangible in career-focused eportfolios with Dr. H. L. Chen and Dr. J. J. Tarbox from Stanford University. The application of eportfolios from a career planning and development focus. 

A good collection of papers, providing good concepts to follow through. 

AI in Higher Education - Australia - New Zealand Symposium - Cogniti

 Notes taken from several sessions of the 2026 AI in HE ANZ symposium organised by the University of Sydney, with case studies based on using Cogniti to provide AI agents to support learning. The symposium is offered f2f and online. Recordings available as of 8th February. 

Danny Liu opens with a welcome and overview of the format of the sessions. There is a meet up session at the end of the day. 

The symposium opens with a plenary - From exams to enterprise: the AI reality for graduates, presented by Ray Fleming and Dan Bowen.

Disconnect between what is happening (through the media - layoffs etc. Amazon, Dow, Pininterest etc.) and what we actually experience. AI 'washing' one way for corporations to pass blame on for other underlying challenges. AI potential but not AI performance seems to be the main point. 

In education we are keen to guide our students but we currently have little clarity on what is happening now, let alone into the future. Strategy could be hire entry level with AI skills and partner them with an expert employee. Back to the move from horse powered to motor vehicles - 40,000 companies wiped out in 20 years but mostly replaced by people working with cars. What new careers will come about? 3 key scenarios to use AI - personal, process and paradigm productivity. 

At present, AI mostly used for personal productivity. The big picture is difficult to work out. Shared 1,600 case studies of AI and build a AI case study hunter to help provide examples of how AI is used (ChatGPT agent and Gemini agent). Demonstrated using law, drilling down to legal document management. Useful for comparative studies (for students and teachers). Recommended following AI in Education podcast 

3 streams then run through the rest of the day, each for 15 minutes! I attend several, in between other commitments. 

- Scaffolding learning and assessment in business writing with Gen AI in mind with Hans Hendrischke, David Jun Zhoa and Carmen Vallis from the University of Sydney. Presented by David. Course teaches students to work in global corporations. 100% of students seed guidance on how to reasonably integrate Gen AI into their professional roles. Focus there needs to be on building workplace-ready workflows and critical literacy. Core scaffolding framework on collaboration (between human teams with AI); research (AI enhanced tutorials where students build their own firm databases throughout the semester); and analysis (iterative prompting routines that align with complex strategic management frameworks). Therefore not only for initial scoping but also to 'dig deeper' and to probe further. Teach students to apply strategic frameworks to their work. Shared details of assessment design (first essay - 1250 words 25%, second individual essay 1250 words 25%; group case report - 3000 words - 30%; 3 AI tasks and datasheet 5% each). AI teaks are to undertake case company selection, scan the macro environment and map regulatory and market shareholders (external stakeholders) and internal stakeholders with AI analysis of firm's value proposition, resources and internal strategic dynamics. also use AI to apply business model canvas (BMC) to visualise platforms.

Individual essays require contrasting and theoretical analysis (compare media to lecture notes etc.)  Student feedback is positive. 

-Cultivating ethical agency through critical AI literacy: a seven stage learning framework presented by Meena Jha from Central Queensland University. Students use ChatGPT or Copilot. Framework includes - evaluation accuracy and factual reliability; Assess logical and conceptual coherence; Identify bias and ethical blind spots; examine source transparency and attribution; Analyse depth of understanding; evaluate style and communication quality; and reflect on purpose and context. Information systems analysis example provided. 

Professor Wombat- your personal biochemistry tutor - with Barbara Hadley from Griffith University. Introduced Professors Wombat and Wilson, used to help students come to grips with complex content. Students come with diverse levels of prior knowledge and the course draws second year students from a wide range of disciplines. Conceptual derailment (Burrow, Hill, Ratner & Fuller-Rowell (2020) means students disengage when faced with threshold concepts they are unfamiliar with. Therefore Professor Wombat provides high school level explanations in a friendly manner. The Professor Wilson takes students to a higher order if explanation in a supportive way. Then, revisit text book and work through lecture content. Acknowledged that imperfect understanding is better than no understanding at all! 60% students used chatbots, longer conversations with Wombat and more clarification with Wilson. Students encouraged to spot hallucinations, share on teams and 'reward'  provided to all.

Each week, used AI to analyse interactions. Found persistent misconceptions and foundational gaps, adjusted teaching to address and noted resource improvements for the next round of lectures. Misconceptions surfaced and addressed early and in-time rather than coming up across exams.

- Using generative AI to strengthen research and reasoning: integrating AI critique and reflection into law assessments for non-law students - Mark McConnell from the University of Auckland - business, not law school with Master of Professional Accounting courses. Small class of 15 student mainly of Chinese internationals. Intensive law course for professional accountancy. Written assessment 20%, mid-quarter test -30% and final test - 30% (closed booked). Challenge not to design a take home written assessment but to design a home written assessment that draws on AI. Standard approach is to give an AI response and have students critique. One step further to emphasis legal reasoning and critical thinking and to also use AI to critique both the AI and their critique. 

- Multi-modality, AI and design education: The use of text, image and 3D models for co-creation, with Anastasia Gomez from the University of Sydney (a recorded presentation). Shared workflows to help students learn resilience and critical thinking. Ai used in architecture and design for degeneration/co-creation, performance analysis /design evaluation.. Modalities include text, image, 2D, 3D, code, sound, video and each can be generated through AI - usually text to image,  test/image to 3D, 3D to video. Examples shared. Master level elective using a range of digital tools including text to image to code to 3D to printed 2D. Ai can be used during conceptual design to explore design strategies and student needs to learn how to translate the digital into the physical realm. Often, the physical 3D difficult to realise. Hybrid forms encouraged to bring the virtual and physical worlds together, using AI to help ease the processes for generating the various versions. In turn students learn the limitations and  how to work through challenges. Critical/computational thinking attained and helps them to understand how to control the process, for example to reverse engineer (and explain what was done) from AI to physical or hybrid solutions. 

- From prompt builder to pedagogical  partner: iterative AI learning with kaiako with Karll McGuirk from the University of Auckland. Building Ai literacy with educators. Prompting is not a skill problem but a pedagogical design challenge. educators want to use AI but unsure as to where to start and don't to get it wrong. Shared a course 'AI 101' with introduction to AI, AI in context, and AI for learning and teaching. (see Wegerif and Casebourne - dialogical theoretical foundation for integrating Gen AI in pedagogical design (2025)). Stressed the importance of ako to encourage use of AI. Introduced an agent ' prompt builder'. To scaffold into AI - start with a teaching goal, add context and constrains, choose the right tool, co-design the prompt and test, reflect, adjust. Shared challenges including prompt builder access, increasingly complex system prompts, multiplicity of AIs, how to find the right AI and response time when demonstrating live!

- The promise and the pushback: understanding student reactions to AI-supported learning. Katherine Jensen and Shahper Richter from the University of Auckland.

Embedded Gen AI into an undergraduate course of 800 students in marketing. Shift from focus on plagiarism; viewing AI as a shortcut, passive consumption of technology. To using AI to engage in prompting to create AI-powered brand personas, create spatial environments that required story-telling and technical fluency. Work with AI to support their learning. Attain AI literacy through hands-on experience, critical analysis, through creative partnership. 

Students pushed back that the integration was 'gimmicky' or distracting, ethical concerns (privacy, environmental impacts, algorithmic bias) and some students questioned authenticity and human meaning of AI generated work. Principles derived to move forward. Firstly, to lead with pedagogy and not technology (Master the art of directing a persona to achieve a specific brand voice instead of 'use HeyGen' to make a video). Secondly, move from deployment to dialogue. Plus AI is augmentation and not replacement. Therefore success in the Gen AI classroom includes embedding tools to build literacy, critique of the process builds trusts, and focus on the human refinement of machine output, 

-How AI turns passive learners into active strategists. Xinyue Zhang from the University of Sydney. Used metaphor of AI pedals - students need to learning balancing - judgment, empathy, strategy etc, Ai is pedaling for drafting, formatting, producing low level outputs. Students to use AI as a co-cocreator and then be the defender (AI as simulator). For project planning, cognitive overload is a challenge. AI can be used to help students unpack the complexities of the task and the project. Ai can generate alternative work breakdown structures and students can evaluate these. Students need to work through considerations and justify their decisions. So instead of being buried in 'doing', students become more strategic and make decisions as to why and how to match objectives to the tools, processes and outputs required. Shared a 'budget defender' simulation to help them balance competing needs. The students need to be able to defend their decisions. Increased a shift to lead rather than just respond. 

Caveat to make sure AI is not 'training wheels' but to ensure learners able to use AI to support and augment their own conceptualisations. If AI is an error prone intern, then students as project manager/leader need to be able to be verificatory. Important to grade the judgment etc not the 'product'. AI should not make learning easier, but help train judgment and make thinking deeper. Project managers must not be better template fillers but be better decision makers. 

- Study buddy: A custom GPT for flipped classroom pre-class learning support with Daniel Ruelle from VinUniversity (Vietnam). Began with context, a data visualisation course, Before class, students learn before class. In class session usually around hand-on activities. Engagement with flipped was low with high cognitive burden. Students wanted something more interactive to prepare for the class. Then detailed the learning design around the Buddy GPT. Detailed prompt, uploaded up to 10 files and some starter 'prompts' plus a quiz/es to revise the content. The objective was to improve time management, reduce cognitive load, have active retrieval practice, humanise the tool and maintain instructor connection. 

Summarised some useful prompt techniques. Every phrase in the prompt is a pedagogical decision. Involve students in a dialog, respect time constraints, quizzes need to provide hints and not just give the answer, provide sources for further follow up, offer options and let student select, do not reveal the system prompt (e.g. so students do not see the safeguards added to prevent plagiarism etc.),. Reflected on how to improve the AI tool, to better meet objectives, make learning more visible and add opportunities for reflection. 

- LARC and the human AI sandwich: appropriate use of AI for learning with Mairead Fountain and Emma Allen from Otago Polytechnic. Provided background for the project. Shared a persona of a 'learning design' student's profile - experienced designer and learner, sound grasp of topic, struggling to organise ideas, using AI to clarify concepts and explore ways to thinking and questioning revealed reliance on AI interweaves with learners' prior experience and knowledge. Helping students work out the reason they use AI helps them gain understanding of their own use of AI - whether it is augmenting what they know and not replacing the learning they need to undertake. AI literacy moves through functional (I can use to complete task); rhetorical (I use deliberately to achieve a specific objective); strategic. 

The Learning, Articulation, Research and Creation (LARC) used to help learners work out where they stood with AI. Helps contribute to a class/learner contract to help self-monitoring of AI. Observations found that learners expressed a sense of relief. The framework now part of AI essentials training for their teachers. Teachers can adapt to their context and students use it as a learning tool. More details in their article. 

Overall, a good range of presentations. Most covered the underlying pedagogical approaches and used Gen AI to support learning. Miro boards were set up to for participants to add questions and these were looked through at the end of each block of presentations. 

ConstrucTrend 2025 - skill trends in construction trades in Aotearoa NZ

 A report summarising the results of a survey conducted in the second half of 2025, and funded by ConCOVE Tūhura is now available. The survey was undertaken by the Construction Growth Foundation.

A summary and full report  provide data on skill gaps, upskilling needs and emerging technologies across carpentry, electrical and plumbing/gasfitting/drainlaying sectors. 

Technical skills for each specific trade are well-covered through workplace learning and off-job training. what is missing are the 'non-tool' skills exampled by costing/quoting and use of apps/software. Specific emergent technology skills around the internet of things, digital/electric vehicles, AI etc. show the need to ensure providers keep up with the rapidly changing technical expertise required.

Of note is that 24% of business owners had started their business two years after finishing a level 4 qualification and another 22% started their business between 3 - 5 years. Hence, small business skills are of importance and are not part of present trades qualifications. Granted the entry into construction trades, when compared to other disciplines like hospitality, has lower start-up costs. 

Employer stakeholders have always been reluctant to include specific business skill sets (accounting) into trades qualifications. Generic skills like communications, team work, time management etc. transfer well but there is indeed a gap, with regard to costing/quoting, which needs to be addressed early on in trades careers.

Overall, an good overview of current and future skills needs for construction trades. 

Aotearoa AI Tertiary Network (ATAIN) - Mark Nichols on AI and the future of online delivery

 In this first session  for 2026 from ATAIN we have a presentation from  Dr Mark Nichols who presents on 'AI and the future of online delivery: some whakaaro (thoughts). 

An updated version (and updated regularly) of a presentation to the Open Polytechnic as the field is moving rapidly. 

Began with AI as being helpful and then shared examples including in education, closing with some thoughts on the future. 

Billions are being invested in AI and this accounts with some of the speed of development and the ways AI is shifting in its focus and capabilities. Anthropic for example, is worth much more that NZ's yearly output! 

Demonstrated how quickly AI can provide resources, but paints a positive picture of how AI can be useful in education. Humans still need to have input, otherwise, it only provides a shallow view point.

Used Meta AI glasses and Hugging Face with Reachy Mini - built it yourself AI desktop robot. 

Warned if AI as 'slop' but the relentless pace of development continues! Rise of agentic AI perhaps not so far away. Shared examples of AI generated videos and bands - Velvet Sundown; Doppl to allow you to try out outfits; jobs being taken over by AI, especially entry level jobs; AI will cheat and hide its tracks if it is in its own interest ! - See Popular Mechanics blog - AI has learned to cheat and punishing it makes it smarter! and Times on when AI thinks it will lose, it can cheat; able to outsmart CAPTCHA tests; fake videos; deep fakes :( flaws in AI therapy chatbots; 

Ethics is trailing the ways AI is being used for nefarious activities (sigh). Positive outcomes include accelerating drugs and vaccines; research - lit reviews, analysis, etc. but care needs to be used - case of company having its data erased when testing an AI agent.

What does it mean to be artistic, creative, have expertise?? What happens in education when we have personal coaches / teachers / mentors? What is the future of book writing?? 

AI is non-anthorpomorphic - has no conscience/shame, here to stay and reminds disruptive. Important to keep the human in the loop (HitL) How can AI fit into education - not to increase cognitive debt but to augment our human capabilities.

Shared two sides of the coin - AI useful in education but important it does not replace the learning required to attain knowledge and skills. Be critical - see article by Sparrow and Flenady (2025). 

How students use AI? AI users now increasing in personal use, instead for organisations. Primarily used for searching (rather than browsers). See this on use of ChatGPT. AI destroying universities.  Student use of AI - Microsoft report.  Educators use of Anthropic. 

Concerns - cognitive self harm - metacognitve laziness; cognitive debt; reducing cognitive friction; -inequitable access; passing off - not only needing to think. Young people are no longer reading and AI exacerbates this. 

AI can bring these roles -  Socratic dialogue partner, personal coach, drill sergeant, study buddy. Reminder of the science of learning and apply AI to support these to occur. 

Short Q & A followed. Good summary of the challenges and possible direction. 

OECD Digital Education Outlook 2026 - exploring effective usses of generative AI in education

 This report from the OECD is worth a look through. A summary reviews the key findings. These include:

-  indication from several studies that Gen AI increases quality of student work but the advantage is obviated when the tool is removed - indicating cognitive debt.

- planned and structured use of Gen AI to improve learning, critical thinking, creativity and collaboration works.

- Gen AI can add to teaching while still supporting teachers' agency

- Gen AI can boost scientific research and streamline institutional operations.

The report has 13 chapters organised into 3 main parts.

There are two introductory chapters before Part 1 (4 chapters) on the topic 'enhancing student learning with Gen AI.

Part 2 has 4 chapters on 'augmenting teachers' performance using Gen AI.

The last part focuses on 'improving system and institutional management' with 3 chapters.

Of note are the following:

- Page 15 - figure 1.1 increase of ChatGPT users as a share of internet users, 2024 to 2025. NZ is 7ths with usage between 30 - 40 %. Stats need to be carefully used - China has very little use of ChatGPT but use their own Gen AIs - DeepSeek, Manus etc.

- Page 17 - figure 1.2 - most students still use gen AI for obtain information, about 1/2 use it to explain terms and concepts. Data from a few European countries only.

- Page 18. figure 1.3 - similar pattern for teachers (German study).

Page 26 - personalised learning discussion.

Annex 1.A provides examples of country strategies and frameworks for Gen AI and two chapters (5 and 6) capturing perspectives from researchers/practitioners

Chapter two - Gen AI for human skills development and assessment: implications for existing practices and new horizons by D. Gasevic and L. Yan is worth putting some time into reading and unpacking.

Part 1 chapters provide case studies, examples and evaluations of various approaches.

- chapter 3 on - dialogue-based AI - implementing the Socratic method with Gen AI

- chapter 4 - fostering collaborative learning

chapter 5 - developing creativity

chapter 6 - AI in education unplugged. 

Part 2 has 3 chapters with one as an interview.

Chapter 7 - conceptual framework for teaching -AI teaming

Chapter 8 - transforming from general-purpose to educational-oriented Gen AI

Chapter 9 - Gen AI as a teaching assistant

Chapter 10 - Gen AI to support teachers.

In the last section, chapter 11 covers AI in institutional workflows; Chapter 12 on Gen AI for standardised assessments; and the last chapter on Gen AI and the transformation of scientific research.

Currency is the main motivation to read through this report. Although mostly covering the formalised school and higher education sectors, there is much commonality of use to vocational education approaches. 

Handbook on personalised learning - book overview

 The Handbook on Personalised Learning, edited by M. L. Bernacki, C. Walkington, A. Emery and L. Zhang and published by Routledge late in 2025 is a timely resource. Editors and authors are all based at  US of A Universities. 

A preview pdf with the preface summarising the book's content, Chapter one by J. L. Plass and F. Froehlich on 'Trends in personalised learning' is available. 

There are 7 sections in the book The first section has chapters to define and provide the theoretical background for individualised learning.

Section 2 reports on 2 approaches, exemplifying what personalised learning can achieve. The contexts are digital and game-based learning environments).

Section 3 centres around the psychological theories of learning on how individuals learning and what characteristics support learning.

Section 4 covers instructional design principles for individualises/personalised learning

Section 5 digs deeper into learning design for specific disciplines - math, reading, social studies, computer science).

Section 6 revolve around the advantages of personalised learning

Section 7 has a focus on the policies and environmental factors which support/or disrupt tje implementation of personalised learning. 

Chapter 1 - lays out the definition of personalised learning, along with how it is designed. Integrates the contribution of Gen AI into the mix, how can Gen AI be leveraged to support personalised learning and especially to provide greater accuracy for adaptive learning - which has been a major challenge for personalised learning platforms. 

 A book setting down some of the precepts and foundations for personalised learning with the inclusion of Gen AI and its potential. 

Discussing AI in vocational education with Kai Pākiki Canterbury

Last week (January 5th) on the podcast with the Canterbury branch of the Royal Society of NZ - Kai Pākiki Canterbury. Dr. Amit Sarkar and myself, present our work on AI in vocational education. 

The podcast runs for an hour and includes Morgan Merien from the NZ enthomological society on the 'bug of the year' initiative. The hosts Tom Goulter and Adrian Paterson discuss facts and the probabilistic worldviews (from 21 minutes), and Amit and myself present and discuss AI (from 30minutes) 

We discuss the initiatives, challenges (digital divide, data sovereignty) and some solutions. The importance of attainment of AI literacies for both our teachers and students, ethics and the pedagogy of integrating AI are aspects discussed. This includes using AI to support learning and not to replace the processes of learning. The ensure the effectiveness of AI as a coach requires careful training of the AI. Customisation or localisation is also important to ensure that there is authenticity in the interactions between learners and AI. 

Plans for 2026

Back into the fray after a few weeks back in the home country to support by aging mother. I am looking forward to what this year will bring. 

Progrramme review and redevelopment will take up much of my time. It is a great opportunity to get to know a degree programme well and to built relations with the teachers. Professional Development for our teachers will revolve around AI. We need to develop a good understanding of what, how and when to use AI. The selling point for AI is that it can be used to take some of the workload off teachers. However, it can also add to teachers' workload, especially if the effect of AI on assessments is not worked through. 

On the research front, our AI projects continue with work on personalised learning based on Cogniti and continuance of our work to develop AI chatbots to support specific disciplines and learning activities. Next month, I will be sending out a call for chapters towards a book to collate initiatives and perspectives on deploying AI to support personalised learning. The goal will be to publish this book early 2028.

I am also working on co-editing a book that records the many initiatives and projects undertaken between the initiation and cessation of the Reform in Vocational Education. Through the 5 -6 years across the reform, the new entities which were formed, have worked conscientiously to improve vocational education across NZ. Therefore it important to archive these in one package, as many entities  no longer exist beyond the end of 2025. Their work either disappears or is curated in sites hosted by other institutions and the knowledge and wisdom of their staff and communities of experts is dispersed and rearranged in the new configurations for Aotearoa VET.. 

It will be another busy year but one that already has several objectives to reach. There is much work to be done with respect to learning design and curriculum development as we normalise the use of AI across the institution and VET along with the business as usual objectives to ensure aspects of cultural competencies, academic literacies and sustainability are also woven through the curriculum.