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Commit Graph

5 Commits

Author SHA1 Message Date
c4cb3307fa Update README and saltire docs to current behavior
The README now documents the daily workflow (working date, live mode
vs printed lists, regenerate semantics, full day-editor editability),
describes cycle mode's rolling rotation accurately, repairs the
custom-parameters section, and points to the saltire testing guide,
which gains resume-after-a-break instructions.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-31 19:16:54 -07:00
46f7f55633 Phase 6: participation grading, gradebook passback, opt-out integrity
Ports the timing-neutral foregone-participation grading scheme from
participation_grades.R: answer quality (per-course level points) minus
a deduction for participation foregone through unavailability,
estimated by Monte Carlo simulation of the actual weighted draw and
averaged over when absences fall, plus a small form-filing incentive
for drawn-while-absent-without-opt-out days. Reason-blind and
luck-protected; zero-answer students floor to 0. Parameters
(allowance in SD units, passing line, form penalty, simulation
size/seed) are course settings. Verified against the R engine's
rendered 2026q2 reports via the new import-legacy command: quality and
availability match exactly, finals within Monte Carlo noise; dropped
students import as inactive enrollments and are excluded identically.

Grades are computed on demand into stored GradeRun snapshots and
reviewed on a grades page with CSV export and per-student reports
(also served to students via a publish toggle). Display scales map
points to UW 4.0, a threshold table (one-click import of the Canvas
course grading scheme), or raw points. Gradebook passback via AGS
sits behind a settings toggle with a review-then-push flow.

Opt-out withdrawals are now soft-deletes with a withdrawn_at audit
trail, and close when class begins (class days gained optional start
times), so availability records cannot be rewritten after the fact.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-31 18:38:22 -07:00
7ec1be5dc6 Phase 5: reporting, exports, pronouns, and roster freshness
Instructor participation report: per-student histograms, outcome mix
by class day, and a sortable table including the fairness ratio
(answered calls over questions present for, with opt-out days out of
the denominator), plus CSV exports of students, calls, and opt-outs.

Assessment scales are now per-course data: ordered levels with labels
and points out of 100 (defaults carry the old R grading values), with
calls referencing levels by id so renames follow through to history.
Renaming, re-pointing, reordering, and adding levels are always
allowed; deleting a level in use by recorded calls is blocked.

Pronouns and course term dates come from Canvas custom variable
substitutions, at launch and roster-wide via rlid-scoped NRPS; the
student page notes that names/pronouns are Canvas-sourced. Rosters
can also be refreshed outside launches: a "Sync roster now" button
and a sync-rosters CLI command for an hourly cron job, skipping ended
courses. Alembic now runs SQLite-compatible batch migrations with a
constraint naming convention.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-31 17:05:34 -07:00
52afc57ebd Phase 2: LTI plumbing, roster sync, and fake-launch dev mode
OIDC login, launch, and JWKS endpoints built on pylti1p3next's Flask
adapter, with launch-claim processing split into a testable module.
Instructor launches refresh the roster through NRPS; the sync code is
source-agnostic and also drives the dev-mode fake roster. Dev mode
(COLDCALL_DEV_MODE=1) provides fake instructor and student personas
that set up the same session state as a real launch, so the rest of
the app can be developed before a Canvas Developer Key exists.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-31 16:33:08 -07:00
8d8a463f81 Phase 1: scaffold, data models, selection logic, tests
Flask application skeleton with SQLAlchemy models for courses (including
per-course settings), students, enrollments, opt-outs, and calls; the
weighted and cycle selection logic ported from the manual coldcall
scripts; alembic migrations; and a pytest suite covering selection
behavior and the model query helpers.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-31 16:27:09 -07:00