In preparation
Methodology
A framework for assessing graduate AI readiness
The conceptual basis for the proposed capability domains, and the reasoning behind a task-based rather than attitudinal approach.
FutureMeasure
Research & insights
Work in progress, published as it is ready.
This is the publication record of a new research initiative. Nothing has been published yet. As methodology papers, design notes and benchmark studies are completed, they will appear here — including the parts that did not work.
- 0 publications to date
- Inaugural cycle in development
- Peer review welcomed
Forthcoming
Listed items are planned work
Not yet available for citation
In preparation
Design note
Designing assessment tasks that resist model assistance
Practical questions that arise when an assessment must measure judgement in an environment where a model can attempt the task for the student.
FutureMeasure
Planned
Domain review
Critical evaluation and verification as a graduate capability
A review of what verification actually requires in professional practice, and why it is poorly captured by confidence measures.
FutureMeasure
Planned
Sector briefing
What universities are being asked to evidence
An outline of the external expectations — employer, accreditor and council — that graduate readiness evidence is beginning to answer.
FutureMeasure
Reference base
Every figure we cite is dated and linked.
7 published studies sit behind the claims on this site. Select an entry to read what it found.
Publication year → publisher → finding
Each marker opens the original publication.
FutureMeasure is independent of these organisations. References identify the published evidence base, not endorsement.
Editorial position
We will publish what the evidence supports, and say what it does not.
A benchmark is a claim about the world, and claims deserve scrutiny. Every publication from FutureMeasure will state its method, its sample, its limitations and the inferences it does not license.
Where results are provisional, they will be labelled as provisional. Where an instrument behaved unexpectedly, we intend to report that too — it is usually the most useful thing a reader learns.
Collaboration
Contribute to the inaugural research programme.
We are seeking academic collaborators and institutional research partners for the first cycle, including reviewers and pilot sites.