Attendance — last 4 weeks
Per session, by subject, including self-directed Cornerstone blocks · DfE-code compatibleWk2 Wed afternoon partial — parent-reported (unwell, 12:40), same-day mentor contact, acknowledged in the mentor 1:1; flagged monitoring; loop closed. No unexplained absences this term; no DSL action.
Attendance over time — weekly
Referral baseline: ~40% at the sending school. Weekly view shows recent dips and recoveries that a single 4-week figure can mask.
How attendance is recorded and coded
NEO records attendance per session, by subject, then maps it to the DfE attendance codes (August 2024 framework) — so the sending school's statutory register transposes directly: / \ present · L late before close of register · I illness · M medical or dental appointment · N reason not yet established (resolved within 5 working days). Maya's Wk2 Wed reads: present a.m. (/) · illness p.m. (I), parent-reported. NEO is not a DfE-registered school, so the statutory register remains with the sending school or LA; how NEO sessions appear there (typically B or K) is agreed at commissioning. NEO supplies the code-compatible, per-session evidence beneath it.
Engagement
Across all enrolled coursesAssignments — last 14 days
14 set · 12 submitted on time · 1 submitted late · 1 with reasonable adjustment (extended deadline)
86% on time · 7% late · 7% adjusted
On-time trend by week: 78% → 84% → 86% (Wk4 in progress). By subject: English 92% · Maths 88% · Science 79% — Science dip matches the Wk2 Wed illness absence, not disengagement.
Live participation
Camera-optional. Voice / chat / mic preferences per pen-portrait.
- English — chat-led participation, increasing voice in small-group breakouts
- Science — written follow-up rather than live verbal recap
- Maths — answers via Classroom, hand-up via reaction
Progress by subject
Mastery scale 1–4 (developing → mastering)| Subject | Baseline | Current | Target | Note |
|---|
Scale: 1 developing · 2 securing · 3 embedding · 4 mastering — defined against the unit objectives in the curriculum vault, so "3" means the same thing in every subject.
How these judgements are generated
Teacher judgement, assessment-informed: each rating is made by the qualified subject teacher from marked Classroom work and low-stakes checks, moderated at the half-termly review (next: w/c 19 Oct). AI never generates or adjusts a progress judgement — under NEO's Diamond AI Policy every reported judgement is made and signed by a named human. Expected pace is agreed per learner at placement start against their referral baseline, not against a national cohort — most NEO learners arrive after significant time out of education, so cohort benchmarks would mislead; IGCSE outcomes provide the external benchmark at qualification level.