Are we assessing learning – or just grading production?
THIS IS RELEVANT TO YOU BECAUSE:
- You’re navigating a rapidly shifting assessment landscape where generative AI is challenging universities to rethink what academic work truly measures.
- You’re noticing a growing gap between the work students submit and what they actually understand, and you want to explore how deep that disconnect goes.
- You’re aware that traditional assessment formats may unintentionally encourage surface‑level performance instead of genuine learning.
- You’re seeking clearer insight into how assessment design, institutional policy, and student behaviour should evolve to protect learning integrity in an AI‑driven era
A FIRST LOOK AT WHAT'S INSIDE...
Are today’s assessments measuring what students truly understand, or simply rewarding their ability to produce polished outputs? This white paper dives into one of the most pressing questions facing higher education: how learning, assessment design, and AI‑driven student behaviour are reshaping each other in real time.
Drawing on new research, student perspectives, and long‑standing pedagogical theory, the report explores why many students feel disconnected from the knowledge they’re graded on, and why generative AI is accelerating that disconnect. Instead of treating AI as a threat, the paper looks at what its rise reveals about long‑standing weaknesses in assessment design, and how those weaknesses shape student motivation, strategy, and confidence.
Inside, you’ll follow the emerging tension between what universities intend assessments to measure and what students believe they’re being asked to do. You’ll see how policy, ambiguity, and assessment structure influence student behaviour in ways educators don’t always anticipate, and how these choices affect equity, learning depth, and student trust. The paper also highlights the growing role of accountability moments, clarity of expectations, and the wider learning environment in shaping how students use AI: as a shortcut, as a support, or as a genuine learning tool.
Rather than offering quick fixes, the white paper maps the underlying dynamics that institutions must understand before designing meaningful solutions. It surfaces the deeper questions universities need to confront if they want assessment to align with learning outcomes in an AI‑enabled era. If you want to understand how assessment really shapes student behaviour, what AI exposes about current practices, and where institutions need to focus next, this report provides the essential foundation.