Validity means ensuring that assessments genuinely measure the learning outcomes they’re intended to. In a GenAI -enabled environment, valid assessment tasks focus on students’ ability to apply knowledge, think critically, and demonstrate understanding in context — not just recall information. Valid assessment is not about eliminating GenAI use, but designing tasks that remain meaningful even when GenAI tools are accessible.

For example, using a secure OSCE to assess a student’s clinical skill is valid when direct supervision is needed. Conversely, asking students to create an evidence-informed resource using GenAI — and justify its development — is also valid when the outcome involves research, synthesis, and communication. Because no single task can guarantee validity on its own, multiple, well-aligned assessments across a course — supported by clear criteria and scaffolding — are essential to making trustworthy, defensible judgments about student achievement.

Constructive alignment ensures that learning outcomes, teaching activities, and assessments all work together in a coherent, purposeful way. When assessments are clearly linked to what students are expected to learn and how they are taught, students are more likely to engage meaningfully — and less likely to breach academic integrity.

In a GenAI context, alignment also means being explicit about when and how GenAI use is appropriate, and ensuring that its use is directly connected to the skills or knowledge being assessed. For example, if a learning outcome involves evaluating digital tools or ethical practice, GenAI use should be part of the assessment design — not excluded from it.

Aligned assessments make expectations transparent, help students track their learning, and provide a defensible foundation for making fair and consistent academic judgments.

Inclusive and equitable assessment ensures that all students — regardless of background, ability, or access to technology — have a fair opportunity to demonstrate their learning. This means designing assessments that are accessible, transparent, and flexible from the outset, not retrofitted after problems arise.

Using Universal Design for Learning (UDL) principles, educators can provide multiple ways for students to engage with tasks, represent their knowledge, and express their understanding. For example, offering a choice between a written report, a video, or a presentation empowers students to demonstrate learning in ways that suit their strengths.

Equity also means setting clear expectations, providing scaffolding and exemplars, and ensuring students understand academic integrity — including what ethical GenAI use looks like in different contexts.

Assessments are most effective when students see their relevance to their discipline, future profession, and the real world. When tasks feel meaningful, students are more engaged, more motivated, and less likely to take shortcuts, including inappropriate use of GenAI.

Designing authentic assessments—such as case studies, projects, portfolios, or client-based tasks—helps students connect their learning to practice. It also encourages them to develop critical thinking, ethical judgment, and discipline-specific capabilities that extend beyond university.

Relevant assessments not only measure what matters — they show students why it matters.

Good assessments don’t just evaluate learning — they help develop it. Effective assessment design includes scaffolding, feedback, and opportunities for students to reflect, revise, and build confidence over time.

This means structuring tasks as part of a learning journey, not isolated events. Multi-stage tasks, formative checkpoints, peer review, and embedded feedback all help students deepen their understanding and avoid last-minute, surface-level work — including overreliance on GenAI. In fact, GenAI might be effectively used to support student learning through purpose-built agents like intelligent tutors or helpful chatbots.

When assessments support learning, including assessments that encourage the responsible use of GenAI, students are more likely to stay engaged, act with integrity, and develop the skills we want our graduates to carry forward.

Scaffolded assessment design breaks complex tasks into manageable stages, helping students build the skills, knowledge, and confidence they need to succeed — and reducing pressure that can lead to misconduct.

Scaffolding might include staged submissions, formative feedback, practice opportunities, or structured planning activities. In GenAI-enabled contexts, it also means teaching students how to use tools ethically and critically, and designing tasks that focus on process as well as product.

By making the steps to success visible and supported, scaffolded assessments promote learning, reduce anxiety, and strengthen academic integrity.

Assessment at ACU is supported by a clear framework of principles, policies, and review processes to ensure quality, consistency, and fairness across courses and disciplines.

Quality assurance involves using validated rubrics, moderation procedures, mapping assessments to learning outcomes and graduate capabilities, and aligning with professional accreditation standards where required. It also means designing assessments that remain valid and robust in the face of GenAI and other emerging tools, as well as integrating such technologies into assessments where necessary.

Ongoing review and peer moderation ensure that assessment practices are transparent, defensible, and contribute to trustworthy judgments about student achievement.