Research and Scholarship
What happens to professional judgment when the work that built it is delegated?
That question sits underneath everything else here: how capability develops, what conditions produce it, and whether workflow governance can replace an apprenticeship that AI has quietly absorbed.
01 · The agenda
What the programme is trying to find out.
The work asks how the conditions for professional judgment are designed, what happens to those conditions when AI absorbs the work that used to build them, and whether workflow-level governance can substitute for what has been lost.
02 · The central question
One question, stated plainly.
If judgment was historically a by-product of work that is now delegable, what has to be deliberately designed to replace the mechanism?
03 · Research clusters
Three clusters.
Learning conditions and transfer
- Which conditions predict judgment transfer rather than satisfaction?
- How does productive difficulty behave when it is cheap to remove?
- What does the community of inquiry literature predict here?
Human–AI workflow governance
- Can workflow governance substitute for apprenticeship?
- What makes an escalation control actually fire?
- How is reasoning preserved across a handoff?
Measuring capability responsibly
- Can capability be described developmentally without implying rank?
- What are the measurement properties of a developmental profile?
- What disclosure prevents over-reading a developmental result?
04 · Current stage
An honest statement of stage.
Current stage. The capability and workflow-governance strand is at an early, largely conceptual stage. There is no confirmatory study, no established measurement model and no population data. The online learning and community of inquiry strand has a peer-reviewed output, listed below. No finding about any Edney Learn product’s effectiveness has been established, and none is claimed anywhere on this site.
05 · Publication record
Peer-reviewed publication.
Moderating effects of student heterogeneity on community of inquiry affective outcomes: a multigroup analysis
Computers and Education Open (2025). doi:10.1016/j.caeo.2025.100276
Peer-reviewed. Relates to online learning and community of inquiry rather than to any commercial instrument.
Only verified publications are listed. Nothing is included as forthcoming, under review or in preparation unless it can be verified.
06 · Where research meets a commercial instrument
One statement, and a full disclosure page.
Instrument ownership, data control, scientific leadership and publication authorship are assigned separately in every study and named in the agreement. I hold a commercial interest in Edney Learn, which owns the instruments, and disclose it in agreements and publications. Service delivery and research are separate purposes: being a customer, participant, employee or student is never consent to research participation.
07 · Collaboration
What I am looking for.
Good fits. Faculties and research centres with a real question about capability, judgment or professional formation. Doctoral candidates working on adjacent ground. Institutions willing to have an answer come out inconvenient.
How I can contribute. Co-design and analysis, scientific leadership where agreed, supervision and examining, replication and critique, including of the frameworks on this site.
What makes a first email useful. The question, the institution, the intended design, the timeline, and whether an Edney Learn instrument or dataset would be involved.
Propose a research collaboration.
Research and scholarly enquiries come directly to me. Anything involving diagnostics, pilots or customer data goes to Edney Learn.