Programmatic Assessment and AI Review (PAAIR)

To ensure the calibration of our courses for contemporary contexts and as part of addressing the plan set out in the Tertiary Education Quality and Standards Agency (TEQSA) 2024 Request for Information (RFI) on AI in education, Monash is undertaking a thorough review and programmatic adjustment of all Monash coursework courses.

The Programmatic Assessment and AI Review (PAAIR) project is part of a suite of assessment advancement activities planned to span across two years. It requires collaboration between faculties and the PAAIR Project Team from Monash Learning and Teaching to advance assessment by strategically integrating AI and secure assessments as needed, within a coordinated set of diverse programmatic assessment activities that are carefully scaffolded through courses to prepare students and disciplines to operate in the Age of AI.

For Monash students, this means richer, more meaningful assessments that capture their true capabilities. This diverse approach won't just measure their academic progress - it will ensure they graduate ready for an AI-enabled professional world. Through PAAIR, we ultimately aim to establish Monash as a pioneer of AI-powered learning and assessment, and the blueprint for universities around the world.

Shaping the future of assessment at Monash University

Watch the following video to find out more about the PAAIR project and its goals to shape the future of assessment at Monash University.

Our goals and actions to achieve them

The PAAIR Project Team asks faculties to achieve the following goals through their participation in the PAAIR process. As they progress, faculties are encouraged to build on these goals, developing additional faculty-specific objectives within their program strategies. Throughout and beyond the process, the PAAIR Project Team will observe progress and invite PAAIR leaders to share their achievements.

Actions to achieve this goal
- Respond to Tertiary Education Quality and Standards Agency (TEQSA) 2024 Request for Information (RFI) on AI in education.
- Undertake a thorough review and programmatic adjustment of all Monash coursework courses.
- Produce educator-focused resources and make them available on Teach HQ.
Actions to achieve this goal
- All coursework courses undertake the PAAIR process. Define programmatic assessment and AI integration at a university-level by Academic Leads.
- Align programmatic assessment and AI integration with discipline, qualification, major and/or specialisation at a Faculty-level.
- Map, review and refine courses where required, resulting in changes being reflected in university systems, which are then approved by cross-faculty review panels.
- Reformulate policy to support the enactment of programmatic assessment and principles of AI use.
- Support PAAIR leaders with resources and capability training as they complete the PAAIR process.
Actions to achieve this goal
- Assessments appropriately selected and clearly identified where demonstration of individual human knowledge and skills are required and where collaboration with multiple intelligences is needed and are designed to support responsible AI use preparing students for their futures.
- Advance assessments to facilitate a mixture of AI assistance and assessments without assistance as relevant to the discipline and professional accreditation requirements
- Indicate use of AI and clear security measures for restriction of AI within the Assessment Regimes per procedures.
- Support PAAIR leaders with resources and capability training as they complete the PAAIR process.
Actions to achieve this goal
- Update Assessment policy and procedure concerning hurdles.
- Support the removal of hurdles.
- Provide advice on best use of competency hurdles.
Actions to achieve this goal
- Increase the mix of assessment types that sample different forms of learning.
- Develop student feedback literacy, through longitudinal dialogue and reflection.
Actions to achieve this goal
- Design and enact capability-building strategies through creation of resources and delivery of education interventions such as masterclasses, modules, events - with consideration to an appropriate spread per stakeholder group.
- Support PAAIR leaders in undertaking capability analysis and deliver additional faculty-level support, as required.
Actions to achieve this goal
- Define program lead and team responsible for leading PAAIR structures.
- Embed processes that contribute to greater collaboration and improvement to outcomes.
- Provide scheduled reporting on the status of embedded structures/processes.
- Compile and communicate scheduled reports for noting at the University Education Committee (UEC).

Timeline

The following timeline provides indicative dates for the stages of PAAIR project activities. Each faculty has created a bespoke engagement timeline based on their faculty PAAIR project plans. This is to ensure that project work is contextualised for the faculty and aligns with faculty strategic goals. View PDF version

2025 Timeline for PAAIR activities

The stages of PAAIR

Learn more about each stage of the PAAIR process, including the schedule for completion and the key tasks involved.

In Semester 2, 2024 three faculties (MADA, MNHS and BusEco) completed the PAAIR process as a pilot. The goal was for faculty participants to explore, design and reflect back to the wider university, ideas, structures and modalities for how we can achieve the goals of PAAIR - visit the PAAIR project background to learn more.
In Stage 0 (Semester 1, 2025), PAAIR leaders and Senior Educational Designers participated in a series of events to co-design and plan their:
- Faculty PAAIR Project Strategy, considering the university direction and PAAIR goals, with faculty-specific goals and disciplinary variations;
- timeline of engagement for which courses/ units go into PAAIR at what time;
- and implementation plan, making the scope very clear for decision-making.
Leaders will then bring their newly enabled Course leaders into the program design phase so that these people can support educators to commence PAAIR.
During this stage, the PAAIR Project Team focused on supporting PAAIR leaders, Course leaders and Senior Educational Designers with strategies, implementation plans, stakeholder management and building new collaborative processes, and more.
The university recognises that every faculty, school or area within Monash is unique and may have a different starting point when engaging in the PAAIR process. This planning time afforded the opportunity for Faculties and the PAAIR Project team to uncover new insights and review processes to develop solutions to emerging challenges. This included creating resources and providing support for the greater university to engage with PAAIR in Stage 1.
Watch Claire Palmero and Tim Fawns discuss programmatic assessment and explore the differences between designing assessments at the unit and program level, emphasising well-structured learning outcomes, strategic task selection, and meaningful feedback, and more.
Stage 1 (Semester 2, 2025) is when the first set of courses undertake the PAAIR process. PAAIR leaders, Course Leaders, Chief Examiners and Senior Educational Designers collaborate to:
- map the current state of the course curriculum
- update the course learning outcomes and unit learning outcomes.
- design an assessment regime that demonstrates a programmatic approach to assessment and appropriate integration of Artificial Intelligence (AI).
Throughout this stage, the PAAIR Project Team will track course readiness for the PAAIR process as well while supporting Course leaders and Senior Educational Designers with strategies, facilitated cluster meetings and access to capability-building resources.
The Portfolio of the Deputy Vice-Chancellor (Education) will review policy and procedure along with PAAIR leaders to remove any barriers from achieving the PAAIR goals.
Stage 2 (2026) builds on insights from the previous stage, PAAIR leaders, Course leaders and Senior Educational Designers will concentrate on refining the PAAIR process while planning and embedding the faculty’s strategy. The next tranche of courses will begin the PAAIR process whilst courses from last year will be implementing the new course learning outcomes and assessment regimes.
The PAAIR Project Team will offer guidance to help faculties refine their strategies, alongside ongoing facilitated cluster meetings and access to capability-building resources.
Building on insights and analysis of previous stages, Stage 3 (Semester 1, 2027) PAAIR leaders, Course leaders and Senior Educational Designers will focus on refining program design, addressing governance needs and embedding the PAAIR process as the new standard. The final tranche of courses will begin the PAAIR process whilst courses from last year/semester will be implementing the new course learning outcomes and assessment regimes.
Early analysis of SETU (Student Evaluation of Teaching and Units) data will be reviewed by the PAAIR Project Team to assess the benefits and impacts of the PAAIR process on students.
Consultations with Faculties, Governance and Monash Learning and Teaching will occur to build processes and supports to ensure sustainability of the PAAIR goals post 2026, enabling a new standard of assessment at Monash.

Completing the PAAIR process

Select the blue button to learn more about the PAAIR process.

Completing the PAAIR process

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Further information

Contact the PAAIR project team via paair@monash.edu

PAAIR stories

Browse the PAAIR stories to learn how Monash educators are navigating their PAAIR journey in practice. Each story highlights real examples which explore approaches to programmatic assessment, integration of artificial intelligence, and more.

PAAIR in Practice: Transforming Paramedicine Education

Alice shares her reflections on undertaking the PAAIR process with colleagues from the Bachelor of Paramedicine within the Faculty of Medicine, Nursing and Health Sciences (MNHS).

What's news with PAAIR? With Claire Palermo

Professor Claire Palermo provides an overview of the PAAIR Project.

Be Inspired: Transforming assessment approaches in nutrition and dietetics

The Nutrition and Dietetics team developed and implemented a world-first model for programmatic assessment to prepare students to be work-ready graduates.

Blog: Making evidence of learning visible at Monash: Beyond detection and invigilation

In contrast to AI detectors and tightened invigilation, Monash focuses on evidence of learning and programmatic assessment. A/Prof Tim Fawns, Prof Ari Seligmann, and Prof Claire Palermo explore the University’s current approach to AI in education.

Be Inspired: Using GenAI to develop a feedback bank

Dana Bui used Generative AI to assist in the process of creating pre-written comments that can be used repeatedly when giving feedback on student work.

Blog: PAAIR challenge space conversation: How do learning outcomes work in programmatic assessment?

Liesbeth Baartman (from Utrecht University of Applied Sciences and Maastricht University, School of Health Professions Education) chats with Tim Fawns, Claire Palermo, Ari Seligmann and about programmatic approaches to assessment.

MEA module: Fundamentals to programmatic approaches to assessment

Rethink your assessments and explore how they can support student learning across the course. Design with purpose, strengthen curriculum links, and foster student development over time.

PAAIR

MADA's PAAIR approach

Brendan Boniface provides an overview of MADA’s PAAIR approach, using Fink’s Taxonomy to align cognitive and affective learning. Through visual mapping, scaffolding, and collaboration, the model ensures coherent, significant learning experiences.

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Learning and Teaching: Teach HQ

Learning and Teaching: Teach HQ

Programmatic Assessment and AI Review (PAAIR)

Shaping the future of assessment at Monash University

Our goals and actions to achieve them

Timeline

The stages of PAAIR

Completing the PAAIR process

Further information

PAAIR stories

PAAIR in Practice: Transforming Paramedicine Education

What's news with PAAIR? With Claire Palermo

Be Inspired: Transforming assessment approaches in nutrition and dietetics

Blog: Making evidence of learning visible at Monash: Beyond detection and invigilation

Be Inspired: Using GenAI to develop a feedback bank

Blog: PAAIR challenge space conversation: How do learning outcomes work in programmatic assessment?

MEA module: Fundamentals to programmatic approaches to assessment

MADA's PAAIR approach

Your feedback matters