This podcast explores the pressing need for a transformation in higher education assessment practices, particularly given the impact of generative AI. Professor Elkington argues that traditional, high-stakes assessments fail to prepare students adequately for modern careers, advocating instead for a learning-centered approach that values process, feedback, and evaluative skills.

Key Themes and Insights:

Assessment’s Evolving Role: Current assessments often impose high stakes with limited relevance to future career demands. The narrow range of formats limits student expression. Generative AI challenges traditional assessments, prompting a reassessment of academic integrity and a renewed focus on distinctly human skills.“The high-risk nature of many of our established assessment practices. We’re weighting assessments at 100, so students have a single opportunity to demonstrate their learning. That’s high-risk and high-stress.”
Three Purposes of Assessment:
- Assessment of Learning: Summative, focused on final grades.
- Assessment for Learning: Formative, guiding through feedback.
- Assessment as Learning: Engaging students with real-world issues and metacognitive skill-building.
“Assessment as learning focuses on authentic problems, issues, challenges, and projects.”
Principles for Effective Assessment:
- Alignment with Learning Outcomes: Ensuring assessments reflect key skills.
- Engaging Tasks: Encouraging active, relevant learning.
- Timely Feedback: Providing actionable insights for immediate and future improvement.
- Building Evaluative Expertise: Guiding students to recognize quality work.
“When it comes to assessment, you get what you model for.”
Flexible Assessment at Teesside University: Teesside emphasizes inclusivity and transparency in its assessment design, offering students choice and promoting autonomy.“Flexible assessment is inclusive, learning-focused, and transparent.”
Broadening the Assessment Lens: Recognizing students’ entire learning journey fosters coherence. Elkington calls for “assessment practice with an S” (processes) alongside “assessment practice with a C” (outcomes) to enable a more holistic and progressive approach.“We need to embed assessment practice with an S [processes] and assessment practice with a C [outcomes].”
Assessment in an AI-Driven Era: Embracing flexible, multimodal assessment formats is crucial. Offering diverse submission options and setting negotiated criteria encourages authentic, skill-based learning for graduates in an AI-influenced world.
Practical Strategies for Modern Assessment:
- Employer Engagement: Align assessments with authentic, industry-related tasks.
- Student Agency: Promote self-regulation and ownership.
- Collaboration: Prepare students for teamwork with collaborative projects.
- Adaptability: Shift towards flexible, personalized assessments.

Analogies:

Swiss Cheese Paradox: Layering multiple assessment types to minimize learning gaps.
Mass-Produced vs. Crafted Chairs: Choosing between standardization and personalized, creative skill demonstration.