What are open assessments?

Open assessments are designed to reflect the way knowledge and skills are applied in real-world contexts. These tasks intentionally allow students to use a wide range of tools and supports - including generative GenAI, research materials, collaboration, and digital resources - in iterative, self-paced ways because this mirrors the complexity and practices of the worlds they'll enter upon graduation.

Open assessments focus on:

  • Process as well as the final product - how students find, evaluate, synthesise and communicate information.
  • Learning for and as practice - not just demonstrating content knowledge, but engaging with tasks that resemble real-world challenges.
  • Developing ethical, critical, and strategic approaches, including how such approaches extend to the use of GenAI tools.

Open assessments do not compromise academic standards. Instead, they help students learn how to work effectively, ethically and creatively in information-rich, GenAI -enabled environments.

Why use open assessments?

Open assessments are vital in today's world where tools like GenAI, collaboration platforms, and digital resources are part of everyday work and life. They:

  • Support development of graduate capabilities, such as problem solving, communication, and digital literacy.
  • Provide space for deeper, sustained learning - integrating research, analysis, and reflection.
  • Encourage authentic engagement, motivation, and critical thinking.
  • Allow students to demonstrate learning in complex, contextualised ways, not just under time-pressured conditions.

Open ≠ Unimportant

Open assessments are not "less serious" or "unimportant" - they simply reflect a different set of learning goals. They require careful design and teaching, especially when GenAI is in play.

To promote academic integrity in open tasks:

  • Be clear about expectations of acceptable tool use and recommend ways certain tools might support learning.
  • Include reflective or explanatory components that show student reasoning and decision-making.
  • Scaffold GenAI skills throughout the unit and course - don't assume students know how to use tools well or ethically.
  • Use assessments that are personalised, contextualised, or multi-stage to deter over-reliance on GenAI.

When should open assessments be used?

Open assessments are best used when the aim is to:

  • Promote critical and applied thinking, rather than memorisation or summative knowledge or skills.
  • Assess complex or multi-step tasks where the process is as important as the outcome.
  • Explore how students work with tools like GenAI to extend their knowledge and skills.
  • Provide low-stakes or formative opportunities for students to test and improve their knowledge and skills that will be assessed later in a secure assessment.

Importantly, open assessments complement secure assessments. Together, these two modes ensure that:

  • Learning outcomes are assessed from multiple angles.
  • Students are prepared both to work independently and collaboratively.
  • Graduates are equipped to engage with GenAI and digital tools ethically and effectively.

Open assessments in the curriculum

At the course level, open assessments should be intentionally mapped alongside secure assessments to ensure comprehensive coverage of learning outcomes. For some disciplines, open assessments will dominate. For others, they will appear less frequently.

Educators could consider:

  • How open assessments contribute to graduate capability development.
  • Where and when students will be explicitly taught GenAI skills.
  • Which tasks allow for collaboration, creativity, or problem-solving.
  • How to ensure equity of access to tools and resources.
  • When to discuss ethical and responsible use of GenAI.

Designing open assessments

Design open assessments with the same rigour and intention as secure assessments - just with different assumptions about the approaches students might take to completing the task.

Open assessment tasks:

  • Are clearly aligned to intended unit learning outcomes.
  • Include transparent recommendations about how to approach the task (e.g. GenAI use, group work, source material).
  • Provide scaffolding and support to help students learn how to demonstrate their learning, including where relevant the use of GenAI and other digital tools.
  • Are assessed based on students' ability to interpret, apply, and communicate knowledge and skills.
  • Include opportunities for reflection or meta-cognition, especially when GenAI use is involved.

Tip sheets for open assessment types

Below are tip sheets regarding some of the more popular forms of open assessment tasks. These tip sheets include information about the type of assessment, the learning outcomes they best serve, the learning design considerations associated with them, and how GenAI could be integrated.

Chan, C.K.Y., Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, 43). https://doi.org/10.1186/s41239-023-00411-8

Cui, Y., Meng, Y., Qian, X., & Tang, L. (2025). Developing a college student feedback literacy scale for the GenAI context. Assessment & Evaluation in Higher Education, 1-14. https://doi.org/10.1080/02602938.2025.2495048

Foung, D., Lin, L., & Chen, J. (2024). Reinventing assessments with ChatGPT and other online tools: Opportunities for GenAI-empowered assessment practices. Computers and Education: Artificial Intelligence, 6, 100250. https://doi.org/10.1016/j.caeai.2024.100250

Page last updated on 11/07/2025

Service Central

Visit Service Central to access Corporate Services.


Other service contacts


Learning and Teaching
Library
Request Something

Make a request for services provided by Corporate Services.


Request something
Knowledge base

Find answers to frequently asked questions 24/7.


See Knowledge Base