Stop trawling through repositories manually. One grading run gives you everything you need to assess, report, and improve — across your entire cohort, every milestone.
What You Can Generate
Every output is produced automatically at the end of each run — nothing to configure separately, nothing to export manually.
Every student, every criterion, in one view. Sort by score, filter by band, identify who is at risk before the deadline passes.
Run a grading pass at any milestone and compare results across time. See whether your cohort is improving, plateauing, or regressing.
Drill into any student: commit timeline, branch usage, PR engagement, CI pass rate, code quality metrics, and milestone completion — all in one report.
JPlag cross-repo analysis runs automatically across the full cohort at every grading pass. Flagged pairs surface with highlighted matching code — evidence-ready for formal escalation.
One-click CSV formatted for direct Moodle import. Criterion scores, overall band, and structured feedback in one file — no reformatting required.
Which criteria is your cohort consistently failing? Which are too easy? Aggregate data across students and milestones to inform rubric calibration and curriculum design.
Workflow
No new tooling for students. Works with the infrastructure you already have.
Point the platform at your unit group. All student repositories are discovered automatically — no per-team configuration.
Adjust criterion weights to match your learning outcomes. Configure per unit, per milestone. The rubric is yours to define.
All repos are assessed in parallel — GitLab API, static analysis, LLM scoring, and similarity detection. Typically under 30 minutes for 60 repositories.
Browse the cohort dashboard, drill into individuals, download the Moodle CSV, and review similarity flags — all from one place.
Dashboard Insights
Whether you have 30 students or 300, the cohort view gives you the signal you need without drowning you in noise.
Students with low commit frequency or no CI activity in the past week are flagged automatically — before the deadline, when there is still time to intervene.
See at a glance which criteria the cohort is struggling with. One failing criterion across 80% of the cohort is a teaching signal, not a grading problem.
In team projects, per-student metrics separate individual contribution from team output. No one coasts undetected.
Did the cohort improve after your Week 6 lecture on CI/CD? Milestone-over-milestone trends give you evidence that your teaching is (or is not) landing.
See your own course data through a professional engineering lens. 30 minutes, no commitment.
Book a 30-min Demo