Digital Learning Passport: Learner-Controlled Skill Evidence from Learning Management Systems

A university learning management system records years of evidence about how a student actually learns: assessment attempts, late submissions, resource access patterns, shifts in engagement over time. None of it follows the graduate out the door. What follows them is a transcript, a grade average that discards the evidence behind it, owned by the institution rather than the person who generated it. Access ends at graduation. Recruiters, meanwhile, repeat competency checks the education system has already performed, against CVs nobody verified.

The Digital Learning Passport inverts the ownership. LMS records are aggregated inside institutional infrastructure and converted into a skill vector across six competency dimensions. The learner holds the result and decides what to share: a consent-scoped snapshot, encoded as a QR payload that can include or exclude evidence classes, verifiable offline by a recruiter without granting anyone database access. The recruiter-facing interface computes a match score against a role requirement vector, shows a ranked gap map, and keeps institution-issued evidence visually distinct from anything the student added themselves. Institution as issuer, student as controller, recruiter as verifier.

The research contribution is a working Design Science Research artifact evaluated on real learning data rather than a conceptual model. Applied to the Open University Learning Analytics Dataset, the pipeline constructs 29,228 complete registration-level profiles from 32,593 registrations, an 89.7% coverage rate. Aggregate gap severity correlates negatively with held-out academic outcomes at Pearson r = −0.767, and severity-ranked screening identifies at-risk outcomes with an F1 of 0.881 on 8,769 held-out registrations. A structured recruitment process model maps where verified evidence displaces manual work, with the largest reductions falling at CV screening and first-stage competency checks.

The Digital Learning Passport extends the same thesis running through EdgeTal and SemanticGuard: where data cannot be protected in transit, do not transmit it. Here the constraint is architectural rather than cryptographic. Raw student records never leave institutional infrastructure, and what travels is a signed assertion the learner chose to release.