Confirm and coordinate learning outcomes

Key Question: Given student access to generative AI (Gen AI) to assist with aspects of the task, does my assessment in its current form still provide valid evidence of learning?

Review learning outcomes to ensure they describe what a student will be able to do in a demonstrable and measurable way.

Consider if the current learning outcomes are current, sustainable and future oriented.
Consider where you require students to learn about and demonstrate the responsible use of AI technologies.

Coordinate where foundational knowledge and skills are taught in the course to minimise duplication and identify gaps in the student learning journey. Then consider where and how those foundations are developed into more complex knowledge and skills across the curriculum including when and where contemporary tools and approaches will be incorporated.

Open the accordions for more detail.

It may now be necessary to target forms of knowledge and expression that are more difficult for generative AI technologies to easily accomplish, such as critical thinking, evaluation or creativity.
Select the plus icons for a definition of each term

Integrate AI into learning outcomes

Consider where AI technologies fit in your course and unit learning outcomes. Knowledge and skills relating to emerging technologies can be integrated in either an explicit or implicit way. Consider:

Does the discipline require a specific learning outcome related to emerging technologies?
How sustainable or future oriented are the learning outcomes?

Examples of explicit and implicit framing.

Explicit example 1: Demonstrate broad knowledge and technical skills in [discipline], including the use of digital technologies and techniques, to provide solutions relevant to diverse stakeholders in dynamic environments

Explicit example 2: Apply relevant knowledge, skills, critical thinking and curiosity to effectively address discipline challenges using current and emerging tools and adapting solutions to be context-sensitive and suitable for the intended audience.

Implicit example 1: Collaborate with others to create meaningful solutions to [discipline]] challenges.

Implicit example 2: Demonstrate advanced professionalism through a commitment to lifelong learning, ethical practice and advocacy for the [discipline].

Next, consider whether the course or unit learning outcomes should be achieved individually or collectively. Is there scope and space for outcomes to be achieved:

in collaboration with other students
with AI assistance or
to intentionally exclude AI assistance and peers to demonstrate individual human skill?

Examples of individual and team learning outcome framing.

Individual example: Communicate effectively and efficiently.

Ambiguous example: Conduct research and be skilled at accessing, critically appraising and applying the best available evidence to practice.

Team example: Work collaboratively in a range of settings.

As with all learning outcomes you should map and coordinate where foundational knowledge and skills are taught in the course to minimise duplication and identify gaps. Then consider where and how those foundations can be developed into more complex knowledge and skills across the curriculum.

Refer to Learning outcomes - integrate AI into learning outcomes for a discussion between Professor Ari Seligmann and Associate Professor Tim Fawns about adapting learning outcomes at both a unit and course level. As well as more guidance about designing learning outcomes that align with taxonomies to describe the desired performance or behaviours that you want to observe as evidence of learning.

Learning and Teaching: Teach HQ

Learning and Teaching: Teach HQ

Confirm and coordinate learning outcomes