Article #2 of AI in Education Article Series: January 2025
Curious about what AI agent projects exist across education in Oceania? See our log, understand why they are relevant and who to contact for each.
Written by
Superpower: Romance languages
Fixations: Sunday drives
Phoebe works predominantly in social and market research, as well as monitoring and evaluation. Her projects often involve large-scale surveying and interviewing, and more recently, Artificial Intelligence in education.
She began her journey to research and evaluation in Brazil in 2020, supporting projects on social services, gender violence and education, for NGOS, governments and intergovernmental agencies. Prior to this, she worked as an English language teacher for adults.
Outside of work, Phoebe loves history, languages, animals and the outdoors. Together with her partner, she offers support services for Latin American migrants in New Zealand.
Phoebe has a Conjoint Bachelor of Arts and Commerce in Marketing (Market Research), International Business and Spanish.
Everywhere you look, New Zealand organisations are exploring Artificial Intelligence (AI). Within the educational space, most organisations are still at the beginning of their journey. However, as 2025 rolls in, a few are piloting AI tools to solve problems whose solutions have seemed dim until now.
This article is the second in a series titled “AI in Education”, aimed at education providers interested in AI. The intention is for this series to act as a beginner’s guide to the use of AI in education, with a particular focus on AI agents. This series is being developed as part of our project to develop an AI agent for learner oral assessment, funded by the Food and Fibre Centre of Vocational Excellence (FFCoVE). We invite you to follow along as we (Scarlatti) document our learnings about this exciting space.
The article below provides an overview of the emerging AI projects within Oceania’s education sector. This list is not intended to be exhaustive – but provides a glimpse of the landscape and their relevance to the AI agent Scarlatti is currently developing.
Country: Australia
Phase: Mature
Cogniti is a generative AI platform (rather than an AI agent itself), designed to enable educators to build custom AI agents. Since its soft launch in October 2023, educators from 30 institutions in Australia, New Zealand, and Singapore have created more than 600 AI agents using Cogniti.
For example, the University of Sydney itself has built a peer-based learning tool for chemistry tutorials, a tool that provides tailored revision questions for their immunology courses, and an agent which allows students to role-play responding to racism in everyday conversations. Further examples can be found here. Cogniti has recently won Gold for Best Use of Generative AI in Oceania.
Relevance for us:
Key person(s): Danny Liu
Country: New Zealand
Phase: Launched
Sofia is an anthropomorphic AI agent being trialled with marketing students at the University of Auckland. It has a wide range of functions, including answering common questions, providing course details, acting as a tutor, and producing quizzes. Built-in analytics give teachers insights into student usage and understanding, helping identify areas for additional support. The Sofia team have recently been awarded Silver for Best Use of Generative AI in Oceania, published an academic article on their work, and been mentioned in The Conversation.
Relevance to us:
Key person(s): Shahper Richter, Patrick Dodd and Inna Piven
Country: New Zealand
Phase: Launched
Toi Ohomai Institute of Technology has used Cogniti to build a wide range of AI agents, for different programmes. As part of this, Toi Ohomai have inputted law and case studies from Aotearoa to make content relevant for students. These agents have included but may not be limited to:
Relevance for us:
Key person(s): Josh Burrell, Jonathan Adams and Rochelle Flight
Country: New Zealand
Phase: Launched
Auckland University of Technology has also adopted Cogniti’s technology to create an agent which aids their postgraduate Nursing and Science students in writing research proposals for their Masters programme. This agent does so by bringing together a large set of example abstracts and provides students with feedback and possible edits.
Relevance for us:
Key person(s): Kiri Hunter and Lucy Macnaught
Country: New Zealand
Phase: Launched
kahu.code specialises in creating bilingual text and voice models as well as large-scale translations, with a focus on reo hangarau (tech terminology). Their mission is to “facilitate seamless kōrero (communication) between technology and humans, enabling effective interactions and understanding, supporting the revitalisation of indigenous languages.” Their products include:
They are also in the early stages of developing a transcription tool (not yet named).
Relevance to us:
Key person(s): Michael Puhara and Xaviere Murray-Puhara
Poipoia te kākano, kia puawai.
Country: New Zealand
Phase: Mature
Te Reo Irirangi o Te Hiku o Te Ika (Te Hiku Media), has created a suite of ‘te reo Māori’ natural language processing (NLP) tools that can enable the creation of new digital products and services that leverage te reo Māori speech recognition, including a speech-to-text system (audio transcription), text-to-speech system (TTS), and other pronunciation focussed language tools. For example, see the following products:
Relevance to us:
Key person(s): Peter-Lucas Jones
Country: Australia
Phase: Launched
Coach M is a text-based AI agent that workplaces can purchase to help employees learn critical skills and improve their on-the-job performance. Over eight weeks, employees engage in three 30-minute instant messaging chats with Coach M. This is possible due to it being based on a database of over 20,000 real-life coaching conversations. These sessions enable employees to reflect on goals and keep themselves accountable. Coach M then tracks their progress and provides insights on how employees are performing.
Relevance to us:
Key person(s): Unknown
Country: Australia
Phase: Launched
Deakin Genie is an AI agent developed in 2017 to help students throughout their academic journey, including answering questions about courses, keeping on top of their assignments and planning what to study. It employs advanced natural language processing and machine learning techniques to engage in more natural, context-aware conversations with students. This allows Deakin Genie to understand and respond to complex queries, maintain context throughout interactions, and provide personalised assistance based on individual student needs.
Four years later, Deakin University piloted a new AI automated feedback tool created by FeedbackFruits with students from the Faculty of Sciences and Built Environments. These students were able to upload draft assignments to the tool and get personalised feedback on how well their grammar, structure and referencing aligned with the assessment criteria. For example, if they used the correct tense or abbreviated scientific names accurately. By 2022, the tool had been adopted by 15 courses across multiple faculties and was available to 3800 students.
Relevance for us:
Key person(s): Unknown
Country: Australia
Phase: Launched
Launched in 2022, Wesmigo is a custom-built generative AI chatbot powered by ChatGPT for international baccalaureate (IB) students at Wesley College. The College wanted to create a safe environment for their students to use AI as a coach for brainstorming and help with assignments, monitored from their existing learning management system. By developing this custom agent, they were able to tailor the responses to be age appropriate, safe for children, have knowledge of the school and the IB curriculum. They also created a companion guide to sit alongside the chatbot, to support students to critically evaluate the chatbot's outputs and understand the limitations of generative AI.
Relevance for us:
Key person(s): Unknown
Country: New Zealand
Phase: Launched
Future Makers are currently working with educators and schools in New Zealand to trial SchoolJoy’s AI simulation agent, ‘NIMO’. Teachers can use NIMO to practice engaging in challenging conversations. For example, talking with parents who are worried about their child’s progress or a student struggling with interpersonal relationships. The teacher’s communication is then assessed against several competencies. At the end of the simulation, NIMO generates a full transcript of the conversation, provides an analysis of the key moments, and gives recommendations on areas where the teacher could improve. NIMO also has applications outside of education with industry-specific simulations for people working in tech (who want to practice communicating their products to non-technical stakeholders), healthcare workers (who want to practice interacting with patients as a hospice nurse) and those in financial services (giving bankers the confidence to handle difficult conversations with clients).
Relevance to us:
Key person(s): Derek Wenmoth and Ian Zhu
Country: New Zealand
Phase: In development
ConCOVE is currently developing a proof of concept using LLM with Epic Learning, to develop assessments from unit of skill standards, which can then in turn be contextualised to a particular industry, or learner needs. This is aimed at improving the resource development process in terms of time, quality, consistency, and relevance. A key part of this project for the ConCOVE is exploring how the wider education system responds to this technology, including in terms of moderation.
Relevance to us:
Key person(s): Eve Price
Country: Australia
Phase: Launched
Epic Learning used LLM to overlay state-specific legislation and construction compliance on assessments, to ensure that questions were legally relevant and contextualised to each state's laws and regulations. Note that it does not interact with the learner itself, with the learner still completing the assessment in a traditional format (e.g., written assessment).
Relevance for us:
Key person(s): Karl Hartley
Country: Australia
Phase: Launched
In 2021, the University of Adelaide piloted the AI marking assessor Gradescope with computer science students undertaking coding exams. Gradescope automatically marked programming code and grouped similar answers together. Tutors were then able to review the answers, look at those groups and rearrange them, then apply the same mark or feedback to multiple assessments. A second pilot a year later, looked at how this tool could be used for hand-drawn and symbol-based assignments.
Relevance to us:
Key person(s): Unknown
Country: New Zealand
Phase: In development
The NZQA have just finished piloting a generative AI tool that provides preliminary grades on students’ written NCEA exams. It was trialled on year 10 literacy and numeracy assessments.
Relevance to us:
Key person(s): Unknown
Country: New Zealand
Phase: In development
The Food and Fibre Centre of Vocational Excellence has recently funded Scarlatti (the authors of this article) to develop and pilot an AI agent for learner oral assessment. The intention is to offer students an alternative to traditional written assessments, and providers an alternative to costly one-on-one oral assessments, potentially enabling them to spend more of their time on delivery or pastoral care. The difference between other AI agents in this article is that this one generates questions, converses with the learner (i.e., voice-based), and grades their responses.
Key person(s): Phoebe Gill, Sam Cormack, Adam Barker
Country: New Zealand
Phase: In development
NZQA already have a chatbot that answers and manages incoming calls from students. Their next steps are to explore turning this into generative AI so that it can be more conversational.
Relevance to us:
Key person(s): Unknown
Country: Australia
Phase: Mature
The academic success monitor (ASM) is a digital companion for students, academics and support teams that aims to detect students at risk of failing a class early enough to act. It uses data to provide insights into a student’s academic progress, identify a possible risk and offer personalised AI recommendations to the student for targeted support at the right time. If risk of failing continues to escalate, the system alerts the education provider to intervene. ASM has recently won Gold for AI in Education in Oceania.
Relevance to us:
Key person(s): Unknown
Across Oceania, we are seeing a rapid growth of AI projects – although these are largely in development. Many are being undertaken with the use of the University of Sydney’s ‘Cogniti’, but a smaller number are being built from scratch. Some are undertaking a singular role (e.g., tutor) while others are undertaking a combination (e.g., tutor, administrative support, quiz generator).
Despite all the advancements, there are very few projects exploring AI for assessment. This gap is even more apparent in the VET space in Oceania, where we were only able to find one other product (ConCOVE’s AI generated assessment agent) being developed (other than our own) for use in assessments.
Questions that we are asking for our own AI agent:
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Mollick, E. R., & Mollick, L. (2023). Assigning AI: Seven Approaches for Students, with Prompts. The Wharton School Research Paper. http://dx.doi.org/10.2139/ssrn.4475995
