The First and Further Year Experience (FFYE) community and grants program is designed to support student transition into higher education study and through to their future careers.
In 2025, the FFYE grant program focuses on Assessment in the age of GenAI, with projects that address at least one of the following two questions, drawn from Mitigating the risks of artificial intelligence and harnessing its potential through assessment reform and course transformation (2024), UTS‘s response to TEQSA:
- How can we be confident that our students are graduating with the skills and knowledge that we claim they have, ie that students have developed these skills and knowledge through the course and the CILOs have been assured?
- How can we prepare our students to engage ethically and critically in a world where GenAI is increasingly integrated into professional and personal life?
The following grants were selected for the 2025 round.
Building business-ready GenAI capabilities: a scaffolded assessment framework for first-year core Business subjects
Grant team: Amir Armanious (lead), Simone Faulkner, Troy Sarina, Suying Zhao, Richard Ingold, Alex Sloane
Students lack consistent guidelines on the ethical use of GenAI in their academic work, leading to uncertainty about ethical engagement versus academic misconduct and how to leverage AI tools for genuine learning and skill development.
This project establishes foundational GenAI capabilities in first-year core subjects, scaffolding throughout key areas in the Bachelor of Business. By coordinating across Finance, Accounting, Economics, Marketing, and Management, we develop students’ abilities to critically evaluate GenAI outputs, understand use cases and apply ethical frameworks. These skills are further built upon in majors through discipline-specific applications, preparing graduates for a GenAI-enabled business environment while maintaining integrity of their learning journey. The coordinated approach ensures consistent GenAI messaging across subjects and real-world business practice.
Interactive Oral Assessment in MBA: a Whole-of-Course approach to enhancing assessment authenticity and security, as well as student engagement and communication
Grant team: James Wakefield and Joseph Yeo (leads), Walter Jarvis, John Gaspar
In the MBA program, professional communication skills are assessed across the course. In 2025, the program team will utilise Interactive Oral Assessments (IOA), an authentic assessment type to simulate a two-way scenario-based conversation between an assessor and a student. Alongside, a set of GenAI resources with be developed for inclusion in subjects (e.g. activities to develop and refine students’ skills writing GenAI prompts, to ethically use GenAI to brainstorm/research for ideas, to critique GenAI-produced writing, to provide feedback on presentation scripts and presentations) to raise staff and student confidence and capability with this assessment approach.
Supporting student learning with Generative AI as a visual communication tool in Architecture and Interior subjects
Grant team: Michael Ford, Samantha Donnelly and Emily Edwards (leads), Michael Ford, Samantha Donnelly, Christina Deluchi
GenAI is increasingly used by designers in industry and therefore needs to be integrated as a skill within subjects to support future design practitioners. Given the AI focus on text-based outputs, there is a need for discipline-specific strategies to integrate visual GenAI in design-based subjects and raise students’ awareness of critical thinking, analysis, and data protection when using GenAI in their practice.
In this project the team will focus on a third-year Interior architecture subject linking workplace transition practice to visual GenAI and two second-year subjects (architecture and interior architecture) in which some of the skills for visual GenAI use and critical analysis can be carefully scaffolded during the assessment preparation process. As part of the project outcomes, the team will make recommendations for the integration of foundational skills in first-year subject assessments and develop support material for sessional academics teaching in related subjects.
Shaping tomorrow’s IT professionals: a scaffolded approach to GenAI integration and portfolios in first-year BIS courses
Grant team: Amara Atif (lead), Morteza Saberi, Mahira M. Mowjoon, Fabian Roth, Ghassan Beydoun, Krzysztof Komsta, Olivia Rajit
The rapid integration of GenAI in higher education challenges traditional assessments, which struggle to validate students’ skills. Without appropriate frameworks, students risk relying on AI-generated content without developing critical evaluation and ethical competencies. This gap threatens academic rigour and preparedness for an AI-driven world.
This project introduces scaffolded assessments and portfolio-based learning to integrate GenAI tools fostering students’ technical and ethical competencies while aligning with CILOs. Embedded in two large first-year Bachelor of Information Systems (BIS) core subjects (2,700+ students) and reinforced in later years, these assessments develop evaluative judgment. A whole-of-course approach ensures continuous AI literacy, while a scalable framework supports ethical and professional skill development, preparing graduates to critically engage with AI-generated content.
Advancing authentic learning through forward-thinking assessment in the GenAI era
Grant team: Stanley Chen and Kai Wu (leads), Ming Li, Tyler Dayan, Andre Pearce, Mingfei Tong, Ashwin Rajesh, Shaman Dutt
The increasing use of GenAI tools presents significant challenges for secure assessments in subjects such as Mobile Networking and Internet of Things. AI-generated responses can undermine students’ genuine learning, hinder critical thinking, and obscure authentic learning.
This project will develop real-world case studies and practical group activities to foster active learning, critical thinking, and technical proficiency. By embedding culturally relevant case studies, it promotes inclusivity and supports diverse student cohorts, including those from LSES backgrounds and Indigenous communities. Ultimately, this initiative will strengthen students’ academic and professional readiness, ensuring meaningful learning in an AI-driven world.
Enhancing problem-solving skills with GenAI for empowering transition of First-Year Civil Engineering students
Grant team: Lam Dinh Nguyen (lead), Dee Wu, Trung Ngo, Sangharsha Bhandari, Fan Wu
First-Year Civil Engineering students are challenged when navigating the complexity of assessment tasks that involve complex mathematical formulas and calculations. They struggle to arrive at correct answers due to insufficient understanding of the topics, incorrect adopted parameters and calculation errors, leading to incorrect answers and often incomplete submissions. Often they rely on online sources or GenAI to derive answers which are accepted without scrutiny.
This project aims to develop students’ learning and confidence in problem-solving and their use of GenAI tools, by intentionally developing students’ skills in using GenAI to evaluate, refine, and verify calculations. This approach reinforces theoretical concepts by assessing the reliability of outcomes, creating a shared academic purpose and strengthening their identity as aspiring civil engineers.
Enhancing assessment practices through chatbot-driven rubric guidance
Grant team: Sonia Matiuk (lead), Amanda Wilson, Carmen Axisa, Tran Dinh-Le, Stacy Blythe, Tamar Al-Ghraiybah, Caroline Havery, Antonette Shibani, Lisa-Angelique Lim
A major challenge in large online, asynchronous, accelerated UTS postgraduate cohorts is to consistently provide personalised actionable feedback across markers within tight timelines.
This project utilises AI chatbots to support markers in consistently providing personalised feedback to students that is actionable, timely and in alignment with the marking criteria. This approach not only ensures quality tailored feedback/forward for students to improve their learning and achievement of academic goals, it also provides both students and academics an opportunity to engage with and practice using AI in their professional lives.
AI-enhanced virtual case study
Grant team: Tran Dinh-Le (lead), Amanda Wilson, Sybil Cayetuna, Elizabeth Brogan, Amelia Di Paolo, Marko Antic, Caroline Havery, Ann Wilson
Assessing communication and critical thinking skills in a large cohort of undergraduate nursing students is challenging, especially with budget constraints. AI chatbots offer a solution to ensure authentic assessments.
This project will pilot a UTS AI chatbot to enhance second and third year Bachelor of Nursing students’ skills in conducting health assessments and making clinical decisions. By interacting with the virtual patient, students will develop therapeutic communication skills in a safe environment and gather necessary information for clinical decisions. The target group includes approximately 585 students enrolled in core clinical subjects in Autumn and Spring 2025.
Advancing evidence-based medicine with GenAI
Grant team: Bronwyn O’Brien (lead), Sarah Su, Dimity Wehr, David Yeats, Poppy Watson, Beata Francis
This project builds from a 2024 FFYE grant, which investigated two obstacles that students have in their medical science degree for workplace transition – naivete to the innate employability value of the curriculum, and limited skills to engage with GenAI ethically, responsibly and efficiently. The outcome of the study showed for the whole cohort, students’ collective understandings of both employability and GenAI improved.
The 2025 grant project focuses on individual changes in the student transition goals through curriculum changes in the summative assessment tasks. Each student will be able to self-nominate the employability skills that they seek to develop, and they will capture examples of best practice and evidence of having developed specific employability skills developed throughout their entire course, thereby increasing confidence that these medical science students will graduate with assured CILOs.
From crime scene to court: student-led Insights on AI-assisted decision making
Grant team: Paula Tarttelin Hernandez and Alicia Haines (leads), Teneil Hanna, Vincent Mousseau
Pertinent to the fields of forensic science, security, and intelligence, students need to acquire knowledge and proficiency in the ethical and professional use of GenAI (Copilot).
This project, designed for a 2nd-year core UG Forensic Science subject, guides students through the ethical use of GenAI in hands-on practical group and written assessment tasks. Students will create portfolio entries engaging in critical reflections on the value or constraints of using GenAI to aid various aspects of their investigative journeys, from crime scene to court. Students will learn how to use GenAI ethically, such that no case-sensitive, personal, or confidential information is inputted into their prompts, they will explore time efficiencies, discern between AI-generated hallucinations and evidence-based information, and will improve their communication skills when generation a court report.