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.
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.
