⭐️ A Team4Tech Article by Jody Britten
Recently, the Australian government’s Tertiary Education Quality Standards Agency released its latest guiding document, Assessment Reform for the Age of Artificial Intelligence. This document addresses the challenges that generative artificial intelligence (AI) brings to assessment practices. While the authors focus on higher education, the report highlights key points relevant to any teacher or policymaker who serves any learner at any age.
Here are some key points from Australia’s latest contribution to the international discussion around AI that we wanted to share:
- AI, especially generative AI, can be a catalyst for change. One area where generative AI will challenge long-held beliefs is how we assess and evaluate student learning.
- Learning experiences must equip students to participate ethically and actively in a society where AI is ubiquitous. We need to continuously model the responsible use of AI tools and the implications of that use for learners.
- Assessments should encourage critical analysis of AI’s role in various fields, fostering responsible and ethical use of AI aligned with the discipline and authentic to the task. Learners need authentic engagement with AI tools, and demonstrating learning can be a critical and worthwhile part of this engagement.
- In the age of AI, forming trustworthy judgments about student learning requires diverse, inclusive, and contextualized assessment approaches. As no single type of assessment can address all potential uses and misuses of AI, we need to think about multiple assessment types, especially those that rely on our unique human capacities.
- Educators should take a systematic approach to assessment by integrating multiple methods and continuous feedback to support judgments about student progress and attainment.
- AI can model and visualize assessment data to help inform the continuous improvement of teaching and the design and delivery of learning experiences for learners.
- Assessment tasks should focus on the learning process, emphasizing competencies and qualities like critical thinking, ethical decision-making, and reflection, which are less likely to be simulated by AI.
- Assessment designs should offer opportunities for students to collaborate effectively with each other and with AI, articulating clear boundaries for acceptable AI use in collaborative work. Students also need guidelines for exploring the bias and limitations of AI through their assessments.
This new report collectively emphasizes a forward-thinking approach to educational assessment. At a time when advanced AI can truly change how we approach our work with all learners, the field of assessment must embrace these new opportunities and advance with intellect, innovation, commitment to equity, and evidence that we use daily to improve the outcomes of learners. Emerging research has called attention to significant challenges and great opportunities for artificial intelligence to accelerate assessment. Among those is the needed attention to inclusivity, collaboration, and continuous adaptation of assessment design to improve the global modeling, use, and scale of quality educational assessments.
We know that generative AI has opened new avenues for teaching and learning. As our initial use of AI at Team4Tech demonstrates, the capacity of these tools to reshape our workflows and processes is unprecedented. However, we must be intentional in our approach to using them. We should proceed with thoughtful experimentation with a component of reflection and evidence as we think about how we can use AI tools to advance quality education, including assessment.
We are thrilled to be part of the important work led by Fab Inc and Fab Data that explores the implications, opportunities, and needs for AI to impact assessment for learners in under-resourced communities. Learn more about this work and stay informed on the progress of our teams by visiting AI-for-Education.org.
