As we continue to consider how to navigate teaching and learning in the age of Generative AI one of the greatest challenges remains front of mind for many educators - How do ‘I’ ensure that my students exhibit the learning required for a graduate within my specific discipline?
While this is a complex challenge, some scholars argue the need to refocus towards looking for evidence of learning rather than evidence of cheating (Ellis & Lodge, 2024). This includes shifting focus to the process of learning rather than just the product. Ellis and Lodge (2024) state that students need to be given multiple opportunities to showcase their learning in environments where the “obligation [is] for students to put in the work” (p. 1). They argue that educators should focus their time on finding evidence that learning has occurred, or not. They discuss the need to move away from the idea of a student ‘sitting a test’, towards the idea of the educator ‘testing’ the student. This requires a shift in thinking and educational practice and is not necessarily easily achieved.
Tertiary Education Quality and Standards Agency’s (TEQSA) paper The evolving risk to academic integrity posed by generative artificial intelligence: Options for immediate action (Lodge, 2024) provides guidance in this space. This paper was written to support institutions and learning leaders in taking immediate actions to help mitigate the risk that Generative Artificial Intelligence (GenAI) poses to student attainment of course learning outcomes in higher education.
It is important to note that this document was published in August, 2024 and since then the GenAI landscape has continued to evolve. However, these principles are still valid and recommendations have been expanded upon. Given our move towards a Programmatic Approach and Artificial Intelligence Review (PAAIR) of all our courses, we have included the addition of ‘What this might mean for us now’, in the summary below.
What TEQSA says:
Focus on the most urgent priorities. Review the program and locate the areas that require urgent attention to ensure our students have met the required outcomes.
What this might mean for us now:
Consider how your students show evidence of learning at key points in the program. As we move through PAAIR, we should ask ourselves ‘how can our students show evidence of learning for all of the course learning outcomes across the program’? Consider the key moments in the program and enable students to showcase their learning. Ensure those moments are authentic, valid, reliable and credible.
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What TEQSA says:
Know your students. It is important to get to know your students and understand their individual learning journeys in order to identify whether work that has been submitted is congruent to their prior work.
What this might mean for us now:
Focus on learning as a longitudinal and individual process. Focus on the longitudinal learning journey of our students rather than one summative assessment in one unit. Once again, as we move through PAAIR we can identify how that might work in our context - perhaps through identifying multiple data points and having holistic discussions at key progression points.
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What TEQSA says:
Be transparent about AI use. Clear guidance must be provided for students, including what Gen AI use is allowable in specific assessment tasks.
What this might mean for us now:
Provide clarity around expectations and support digital literacies. Follow the guidance that is available at Monash via TeachHQ to ensure that assessment task requirements are clear and easy to comprehend for students. Alongside, supporting digital literacies within your disciplinary context to create graduates that are critical users of emerging technologies. PAAIR is a good way to consider what this should look like across your program.
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4. What TEQSA says:
Ask students to show their working. Ask students to provide evidence of how they used Gen AI in their assessment task/s to both deter inappropriate use and develop essential AI skills in students.
What this might mean for us now:
Consider different ways for students to showcase their learning process. Implement various ways for students to showcase their process of learning; shifting the sole focus away from a learning product. This can be done in a number of ways, including the collection of artefacts through ePortfolios, assessment appendices, interactive orals, etc...
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5. What TEQSA says:
Engage in conversations with students as assessment. Engaging in conversations with students provides insight into their understanding and learning processes in ways that other assessments cannot, especially in the context of Gen AI.
What this might mean for us:
Explore use of different assessment types such as Viva voces and interactive orals. Look at how we can implement conversational assessment tasks such as viva voces and/ or interactive orals. Get students to engage with authentic assessments and discuss their knowledge and skills in order to show evidence of their learning.
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6. What TEQSA says:
Learn from and collaborate with others. Ongoing collaboration will assist in developing long-lasting and effective solutions to the issues of ensuring evidence of learning in the age of Gen AI.
What this might mean for us now:
Engage with the Learning and Teaching community to share challenges and successes. Engage with teaching and learning communities and recent literature to share your experience, get ideas, and discuss challenges in this space. This could be by attending conferences, webinars, or workshops, engaging and collaborating with your colleagues, and engaging with the broader discussion.
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The challenge for educators is to look for evidence of learning, not cheating. Integrating some of the guidance provided by TEQSA can help us navigate this challenge. However, as this space continues to evolve, we encourage you to join the conversation as it is a challenge that will be best addressed through the collaborative effort of the education community.
Do you have a comment or suggestion for gaining evidence of learning? Use the FMNHS PAAIR FAQ Padlet to share your thoughts with colleagues
Carmen Sapsed - Educational designer, Faculty of Medicine, Nursing & Health Science
References:
Ellis, C. & Lodge, J. (2024). Stop looking for evidence of cheating with AI and start looking for evidence of learning. LinkedIn. https://www.linkedin.com/pulse/stop-looking-evidence-cheating-ai-start-learning-cath-ellis-h0zzc/
Lodge, J., Howard, S., Bearman, M., Dawson. P., et al. (2023). Assessment reform for the age of artificial intelligence. Tertiary Education Quality and Standards Agency. https://www.teqsa.gov.au/sites/default/files/2023-09/assessment-reform-age-artificial-intelligence-discussion-paper.pdf
Lodge, J. (2024). The evolving risk to academic integrity posed by generative artificial intelligence: Options for immediate action. Tertiary Education Quality and Standards Agency. https://www.teqsa.gov.au/sites/default/files/2024-08/evolving-risk-to-academic-integrity-posed-by-generative-artificial-intelligence.pdf