Analytics Alpha Data Dictionary

Time Commitment: Minutes Per Enrolled School Day

Learning Report panel: timeCommitment

Question: Is the school-day denominator available, and if so how many active minutes per enrolled school day did this student average?

Table: alpha.analytics_school_day_minutes

API Path

GET /alpha/analytics/v1/school-day-minutes?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&startDate=2026-01-01&endDate=2026-06-01

Raw DB Path

select active_minutes, enrolled_school_day_count, excluded_school_day_count, minutes_per_enrolled_school_day, school_day_policy_ref, quality_status, null_reason from alpha.analytics_school_day_minutes where tenant_id = :tenant_id and student_id = :student_id and subject_id = 'math' and window_start = date '2026-01-01' and window_end = date '2026-06-01' and quality_status in ('ok','corrected') and null_reason = 'none' and superseded_at is null and source_deleted_at is null;

Render these fields: active_minutes enrolled_school_day_count excluded_school_day_count minutes_per_enrolled_school_day school_day_policy_ref quality_status null_reason

XP: Earned, Goal Availability, And Uncapped Percent

Learning Report panel: xpGoals

Question: How much XP was earned, and are the goal, remaining, and uncapped percent fields available under the shared school-day denominator?

Table: alpha.analytics_xp_rollup

API Path

GET /alpha/analytics/v1/xp-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&windowKind=term&startDate=2026-01-01&endDate=2026-06-01

Raw DB Path

select xp_total, daily_xp_goal, enrolled_school_day_count, xp_goal, xp_remaining, xp_goal_percent, on_track, positive_xp, negative_xp, award_count, reversal_count, source_import_id, policy_ref, null_reason from alpha.analytics_xp_rollup where tenant_id = :tenant_id and student_id = :student_id and subject_id = 'math' and window_kind = 'term' and window_start = date '2026-01-01' and window_end = date '2026-06-01' and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null;

Render these fields: xp_total daily_xp_goal enrolled_school_day_count xp_goal xp_remaining xp_goal_percent on_track positive_xp negative_xp award_count reversal_count source_import_id policy_ref null_reason

Accuracy (P7): Correct Questions Over Total Questions

Learning Report panel: accuracy

Question: What accuracy percent should the Learning Report show for this student and subject?

Table: alpha.analytics_accuracy

API Path

GET /alpha/analytics/v1/accuracy-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&windowKind=term&startDate=2026-01-01&endDate=2026-06-01

Raw DB Path

select correct_question_count, total_question_count, incorrect_question_count, accuracy_percent, source_import_id, policy_ref, quality_status, null_reason from alpha.analytics_accuracy where tenant_id = :tenant_id and student_id = :student_id and subject_id = 'math' and window_kind = 'term' and window_start = date '2026-01-01' and window_end = date '2026-06-01' and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null;

Render these fields: correct_question_count total_question_count incorrect_question_count accuracy_percent source_import_id policy_ref quality_status null_reason

Example Report JSON

{
  "id": "aac_01HT8ACC_2026_SPRING_MATH",
  "student_id": "student_01HT7G3YZV7QB5N4YKQ1K0Z9A9",
  "subject_id": "math",
  "window_kind": "term",
  "window_start": "2026-01-01",
  "window_end": "2026-06-01",
  "correct_question_count": 480,
  "total_question_count": 600,
  "incorrect_question_count": 120,
  "accuracy_percent": 80,
  "policy_ref": "alpha.policy.analytics.accuracy.v2026-06-12",
  "source_import_id": "imp_01HT8XPTIME_2026_SPRING",
  "quality_status": "ok",
  "null_reason": "none"
}

Mastery: KC Changes During A Date Range

Learning Report panel: masteryTransitions

Question: Which Knowledge Components changed mastery state for this student?

Table: alpha.analytics_mastery_delta

API Path

GET /alpha/analytics/v1/mastery-deltas?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&startDate=2026-05-01&endDate=2026-06-01&stateDimension=durable_mastery

Raw DB Path

select kc_id, state_dimension, effective_at, previous_value, new_value, delta_value, transition_kind, policy_ref from alpha.analytics_mastery_delta where tenant_id = :tenant_id and student_id = :student_id and state_dimension = 'durable_mastery' and effective_at >= timestamptz '2026-05-01T00:00:00Z' and effective_at < timestamptz '2026-06-01T00:00:00Z' and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null order by effective_at, kc_id;

Render these fields: kc_id state_dimension effective_at previous_value new_value delta_value transition_kind

MAP Results: RIT And Growth X

Learning Report panel: mapResults

Question: What RIT and Growth X should the Learning Report show for this term?

Table: alpha.analytics_map_growth_rollup

API Path

GET /alpha/analytics/v1/map-growth-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&termId=term_2026_winter&growthWindow=winter_to_winter&normsSet=2025

Raw DB Path

select rit_score, achievement_percentile, growth_percentile, observed_growth, projected_growth, typical_growth, growth_x, growth_x_target, on_track, sitting_count, retake_count, source_import_id from alpha.analytics_map_growth_rollup where tenant_id = :tenant_id and student_id = :student_id and subject_id = 'math' and canonical_term_id = 'term_2026_winter' and growth_window = 'winter_to_winter' and norms_set = '2025' and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null;

Render these fields: rit_score achievement_percentile growth_percentile observed_growth projected_growth typical_growth growth_x growth_x_target on_track sitting_count retake_count norms_set growth_window source_import_id

GOALS: Percentile To RIT And RIT To R90

Learning Report panel: goalsScaleTranslation

Question: What RIT is a target percentile, and what grade/R90 does a RIT map to?

Tables: alpha.analytics_norms_achievement alpha.analytics_r90_table

Assembly Steps

1. Use the norms table_version pinned in the report and the current R90 table_version analytics.rit_to_grade.powerpath.v2026-06-15 unless the report explicitly asks to reproduce a historical R90 answer. HTTP responses are no-store; the version string is the cache key.
2. For percentile-to-RIT, read mean_rit and sd_rit from the achievement norms row and apply the documented normal-model translation, or call /norms/rit.
3. For RIT-to-R90, filter the current R90 table version and choose the PowerPath row whose rit_score equals the requested score. Exact matches return exact; missing rows return source_missing.

API Path

GET /alpha/analytics/v1/norms/rit?subjectId=math&gradeLevel=5&termName=winter&percentile=90&normsSet=2025
GET /alpha/analytics/v1/r90?subjectId=math&rit=239&normsSet=2025

Raw DB Path

with
norms_row as (
  select mean_rit, sd_rit, table_version
  from alpha.analytics_norms_achievement
  where tenant_id is null
    and norms_set = :norms_set
    and table_version = :norms_table_version
    and subject_id = :subject_id
    and role = :role
    and grade_key = :grade_key
    and season = :season
    and quality_status = 'ok'
  limit 1
),
percentile_to_rit as (
  select
    mean_rit + (sd_rit * :z_score_for_requested_percentile) as rit_score,
    mean_rit,
    sd_rit,
    table_version
  from norms_row
),
r90 as (
  select
    r90_grade,
    effective_grade,
    r90_grade_level,
    r90_percent_complete,
    'exact' as source_point_kind,
    table_version,
    rit_score as table_rit_score
  from alpha.analytics_r90_table
  where tenant_id is null
    and norms_set = :norms_set
    and table_version = 'analytics.rit_to_grade.powerpath.v2026-06-15'
    and table_subject_id = :subject_id
    and rit_score = :input_rit
    and quality_status = 'ok'
  limit 1
)
select jsonb_build_object(
  'percentileToRit', (select to_jsonb(percentile_to_rit) from percentile_to_rit),
  'ritToR90', (select to_jsonb(r90) from r90)
) as scale_translation;

Render these fields: percentileToRit.rit_score percentileToRit.mean_rit percentileToRit.sd_rit ritToR90.r90_grade ritToR90.effective_grade ritToR90.r90_grade_level ritToR90.rit90_grade_band_percent ritToR90.r90_percent_complete ritToR90.source_point_kind ritToR90.table_rit_score ritToR90.table_version

Example Report JSON

{
  "percentileToRit": {
    "norms_set": "2025",
    "table_version": "analytics.norms.achievement.v2026-06-12",
    "calculator_version": "analytics.norms.translation.v2026-06-12",
    "subject_id": "math",
    "grade_key": "5",
    "season": "winter",
    "role": "student",
    "percentile": 90,
    "mean_rit": 214.2,
    "sd_rit": 14.1,
    "rit_score": 232.3
  },
  "ritToR90": {
    "norms_set": "2025",
    "table_version": "analytics.rit_to_grade.powerpath.v2026-06-15",
    "table_subject_id": "math",
    "input_rit": 239,
    "table_rit_score": 239,
    "r90_grade": 4.8,
    "effective_grade": 5,
    "r90_grade_level": 4,
    "rit90_grade_band_percent": 80,
    "r90_percent_complete": 80,
    "extend_kind": "alpha_extrapolation",
    "source_point_kind": "exact"
  }
}

GOALS: School Days Remaining And Target-Date Effort

Learning Report panel: goalsTargetDate

Question: How many instructional days remain, and what daily effort is needed to finish by a target date?

Tables: analytics.school_days_remaining alpha.school_calendar alpha.analytics_xp_rollup

Assembly Steps

1. Resolve the student school by effective-dated People and Orgs enrollment, or pass a schoolId when the caller already has the governed school id.
2. Count only alpha.school_calendar rows that are instructional under alpha.policy.school_day inside the half-open [asOf, endDate) window; asOf is included and endDate is excluded.
3. Use alpha.policy.analytics.xp_expected_minute.v2026-06-14: 1 XP = 1 expected minute, 60 XP = 1 expected hour. Do not keep XP_PER_HOUR or weekday math in GOALS.
4. Render the returned fields. If the window has no instructional days, instructional_days_remaining is 0 and target-date effort fields that divide by days are null instead of guessed.

API Path

GET /alpha/analytics/v1/school-days-remaining?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&asOf=2026-06-14&endDate=2026-07-24&xpRemaining=600&hoursPerSchoolDay=1.5&targetDate=2026-07-24

Raw DB Path

with
student_school as (
  select :school_id as school_id
  -- If schoolId is omitted, resolve this from People and Orgs effective-dated enrollment
  -- where begin_date is not null and :as_of falls inside [begin_date, end_date].
),
instructional_dates as (
  select calendar_date
  from alpha.school_calendar
  where school_id = (select school_id from student_school)
    and calendar_date >= :as_of::date
    and calendar_date < :end_date::date
    and is_school_day = true
    and reason = 'instructional'
    and policy_ref = 'alpha.policy.school_day.v2026-06-10'
  order by calendar_date
),
effort as (
  select
    :xp_remaining::numeric as xp_remaining,
    (:xp_remaining::numeric / 1.0) as expected_minutes_remaining,
    (:xp_remaining::numeric / 60.0) as hours_remaining,
    :hours_per_school_day::numeric as hours_per_school_day
),
target_window as (
  select count(*)::integer as school_days_until_target_date
  from instructional_dates
  where calendar_date < :target_date::date
)
select jsonb_build_object(
  'object', 'analytics.school_days_remaining',
  'student_id', :student_id,
  'school_id', (select school_id from student_school),
  'as_of', :as_of,
  'end_date', :end_date,
  'school_day_policy_ref', 'alpha.policy.school_day.v2026-06-10',
  'instructional_days_remaining', (select count(*) from instructional_dates),
  'calendar_ref_count', (
    select count(*) from alpha.school_calendar
    where school_id = (select school_id from student_school)
      and calendar_date >= :as_of::date
      and calendar_date < :end_date::date
  ),
  'first_instructional_date', (select min(calendar_date) from instructional_dates),
  'last_instructional_date', (select max(calendar_date) from instructional_dates),
  'instructional_dates', (select jsonb_agg(calendar_date order by calendar_date) from instructional_dates),
  'xp_unit', jsonb_build_object(
    'policy_ref', 'alpha.policy.analytics.xp_expected_minute.v2026-06-14',
    'xp_per_expected_minute', 1,
    'xp_per_hour', 60,
    'meaning', '1 XP = 1 expected minute; 60 XP = 1 expected hour.'
  ),
  'effort', jsonb_build_object(
    'xp_remaining', (select xp_remaining from effort),
    'expected_minutes_remaining', (select expected_minutes_remaining from effort),
    'hours_remaining', (select hours_remaining from effort),
    'target_date', :target_date,
    'school_days_until_target_date', (select school_days_until_target_date from target_window),
    'required_hours_per_school_day_to_target_date',
      case when (select school_days_until_target_date from target_window) > 0
        then (select hours_remaining from effort) / (select school_days_until_target_date from target_window)
        else null end,
    'hours_per_school_day', (select hours_per_school_day from effort),
    'school_days_needed_at_hours_per_school_day',
      case when (select hours_per_school_day from effort) > 0
        then ceil((select hours_remaining from effort) / (select hours_per_school_day from effort))
        else null end
  )
) as school_days_remaining;

Render these fields: instructional_days_remaining calendar_ref_count first_instructional_date last_instructional_date instructional_dates[] xp_unit.policy_ref xp_unit.xp_per_expected_minute xp_unit.xp_per_hour effort.xp_remaining effort.expected_minutes_remaining effort.hours_remaining effort.school_days_until_target_date effort.required_hours_per_school_day_to_target_date effort.school_days_needed_at_hours_per_school_day effort.target_date_at_hours_per_school_day effort.can_finish_by_end_date_at_hours_per_school_day

Example Report JSON

{
  "object": "analytics.school_days_remaining",
  "student_id": "student_01HT7G3YZV7QB5N4YKQ1K0Z9A9",
  "school_id": "school_alpha_austin",
  "as_of": "2026-06-14",
  "end_date": "2026-07-24",
  "school_day_policy_ref": "alpha.policy.school_day.v2026-06-10",
  "instructional_days_remaining": 29,
  "calendar_ref_count": 40,
  "first_instructional_date": "2026-06-15",
  "last_instructional_date": "2026-07-23",
  "instructional_dates": [
    "2026-06-15",
    "2026-06-16",
    "2026-06-17"
  ],
  "xp_unit": {
    "policy_ref": "alpha.policy.analytics.xp_expected_minute.v2026-06-14",
    "xp_per_expected_minute": 1,
    "xp_per_hour": 60,
    "meaning": "1 XP = 1 expected minute; 60 XP = 1 expected hour."
  },
  "effort": {
    "xp_remaining": 600,
    "expected_minutes_remaining": 600,
    "hours_remaining": 10,
    "target_date": "2026-07-24",
    "school_days_until_target_date": 29,
    "required_hours_per_school_day_to_target_date": 0.345,
    "hours_per_school_day": 1.5,
    "school_days_needed_at_hours_per_school_day": 7,
    "target_date_at_hours_per_school_day": "2026-06-23",
    "can_finish_by_end_date_at_hours_per_school_day": true
  }
}

GOALS: Working And Mastered Age-Grade Status

Learning Report panel: goalsAgeGradeStatus

Question: Is the student working above, at, or behind their school-assigned age grade, and is strict mastery above, at, or behind age grade?

Table: analytics.grade_level_status

Assembly Steps

1. Read age_grade from People and Orgs alpha.age_grade_history for the requested asOfDate. Do not infer it from birthdays, prior-year close, MAP/RIT, working grade, HMG, or course placement.
2. Read working_grade and highest_mastered_grade from Results. Results owns the working-grade resolver; Analytics only compares returned grade positions.
3. Return exactly two named comparisons: working_age_grade_status = working_grade - age_grade and mastered_age_grade_status = highest_mastered_grade - age_grade. Old generic status names, if present, are compatibility aliases only.

API Path

GET /alpha/analytics/v1/grade-level-status?studentId=b6fa7128-f641-4efd-9075-375411fd6c39&subject=math&asOfDate=2026-05-20

Raw DB Path

with
age_grade as (
  select age_grade, begin_date, end_date
  from alpha.age_grade_history
  where tenant_id = :people_and_orgs_tenant_id
    and person_id = :student_id
    and is_time_locatable is true
    and begin_date <= :as_of_date::date
    and (end_date is null or :as_of_date::date < end_date)
    and deleted_at is null
  order by begin_date desc
  limit 1
),
results_grade as (
  select working_grade, highest_mastered_grade
  from results.student_track_state
  where tenant_id = :results_tenant_id
    and student_id = :student_id
    and subject_id = :subject_id
    and as_of_date <= :as_of_date::date
  order by as_of_date desc
  limit 1
)
select jsonb_build_object(
  'object', 'analytics.grade_level_status',
  'student_id', :student_id,
  'subject_id', :subject_id,
  'as_of_date', :as_of_date,
  'age_grade', (select age_grade from age_grade),
  'working_grade', (select working_grade from results_grade),
  'highest_mastered_grade', (select highest_mastered_grade from results_grade),
  'working_age_grade_delta', (select working_grade from results_grade) - (select age_grade from age_grade),
  'mastered_age_grade_delta', (select highest_mastered_grade from results_grade) - (select age_grade from age_grade)
) as grade_level_status;

Render these fields: age_grade working_grade highest_mastered_grade working_age_grade_status mastered_age_grade_status working_age_grade_delta mastered_age_grade_delta source_refs

Example Report JSON

{
  "object": "analytics.grade_level_status",
  "student_id": "b6fa7128-f641-4efd-9075-375411fd6c39",
  "subject_id": "math",
  "as_of_date": "2026-05-20",
  "age_grade": 5,
  "working_grade": 6,
  "highest_mastered_grade": 5,
  "working_age_grade_delta": 1,
  "working_age_grade_status": "working_above_age_grade",
  "mastered_age_grade_delta": 0,
  "mastered_age_grade_status": "mastered_at_age_grade",
  "source_refs": {
    "age_grade": "people_and_orgs.alpha.age_grade_history",
    "working_grade": "results.student_track_state.working_grade",
    "highest_mastered_grade": "results.highest_mastered_grade"
  },
  "deprecated_aliases": {
    "instructional_level_status": "working_age_grade_status",
    "strict_mastery_status": "mastered_age_grade_status"
  }
}

Course Progress Evidence: Completion Percent

Learning Report panel: courseCompletion

Question: What completion evidence did Analytics materialize for this course?

Table: alpha.analytics_completion_rollup

API Path

GET /alpha/analytics/v1/completion-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&completionScope=course&scopeId=course_math_grade_4_powerpath

Raw DB Path

select xp_earned, xp_remaining, completion_percent, denominator_policy_ref, source_import_id, null_reason from alpha.analytics_completion_rollup where tenant_id = :tenant_id and student_id = :student_id and completion_scope = 'course' and scope_id = 'course_math_grade_4_powerpath' and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null;

Render these fields: xp_earned xp_remaining completion_percent denominator_policy_ref source_import_id null_reason

End-To-End Learning Report Assembly

Learning Report panel: fullLearningReport

Question: How does one studentId + term become the Learning Report panels, including Accuracy?

Tables: alpha.analytics_school_day_minutes alpha.analytics_xp_rollup alpha.analytics_accuracy alpha.analytics_mastery_delta alpha.analytics_map_growth_rollup alpha.analytics_completion_rollup

Assembly Steps

1. Resolve studentId, subjectId, canonicalTermId, term_start, term_end, normsSet, growthWindow=winter_to_winter for the "vs 1yr ago" MAP panel, completionScope, and scopeId from the report route or upstream Alpha surfaces.
2. Read the six Analytics tables/endpoints at their documented grains with the ordinary current-row filters.
3. Place returned fields into report panels. If a time-commitment row or XP goal row has null_reason=source_missing, it is a repair state and the report is incomplete until the source is fixed/replayed; do not substitute active dates, attendance days, or calendar-day counts. The only client work is shaping JSON for display; no minutes, XP, accuracy, mastery, MAP, or completion math runs in the report.

API Path

GET /alpha/analytics/v1/school-day-minutes?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&startDate=2026-01-01&endDate=2026-06-01
GET /alpha/analytics/v1/xp-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&windowKind=term&startDate=2026-01-01&endDate=2026-06-01
GET /alpha/analytics/v1/accuracy-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&windowKind=term&startDate=2026-01-01&endDate=2026-06-01
GET /alpha/analytics/v1/mastery-deltas?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&startDate=2026-01-01&endDate=2026-06-01
GET /alpha/analytics/v1/map-growth-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&subjectId=math&termId=term_2026_winter&growthWindow=winter_to_winter&normsSet=2025
GET /alpha/analytics/v1/completion-rollups?studentId=student_01HT7G3YZV7QB5N4YKQ1K0Z9A9&completionScope=course&scopeId=course_math_grade_4_powerpath

Raw DB Path

with
time_commitment as (
  select active_minutes, enrolled_school_day_count, excluded_school_day_count, minutes_per_enrolled_school_day, quality_status, null_reason
  from alpha.analytics_school_day_minutes
  where tenant_id = :tenant_id and student_id = :student_id and subject_id = :subject_id
    and window_start = :term_start and window_end = :term_end
    and quality_status in ('ok','corrected') and null_reason = 'none' and superseded_at is null and source_deleted_at is null
),
xp as (
  select xp_total, net_xp, daily_xp_goal, enrolled_school_day_count, xp_goal, xp_remaining, xp_goal_percent, xp_completion_percent, on_track, positive_xp, negative_xp, award_count, reversal_count, source_import_id, null_reason
  from alpha.analytics_xp_rollup
  where tenant_id = :tenant_id and student_id = :student_id and subject_id = :subject_id
    and window_kind = 'term' and window_start = :term_start and window_end = :term_end
    and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null
),
accuracy as (
  select correct_question_count, total_question_count, incorrect_question_count, accuracy_percent, source_import_id, null_reason
  from alpha.analytics_accuracy
  where tenant_id = :tenant_id and student_id = :student_id and subject_id = :subject_id
    and window_kind = 'term' and window_start = :term_start and window_end = :term_end
    and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null
),
mastery as (
  select jsonb_agg(jsonb_build_object(
    'kcId', kc_id,
    'stateDimension', state_dimension,
    'transition', transition_kind,
    'previousValue', previous_value,
    'newValue', new_value,
    'effectiveAt', effective_at
  ) order by effective_at desc) as deltas
  from alpha.analytics_mastery_delta
  where tenant_id = :tenant_id and student_id = :student_id
    and effective_at >= :term_start::timestamptz and effective_at < :term_end::timestamptz
    and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null
),
map as (
  select rit_score, achievement_percentile, growth_percentile, observed_growth, projected_growth, typical_growth, growth_x, growth_x_target, on_track,
         sitting_count, retake_count, norms_set, growth_window, source_import_id
  from alpha.analytics_map_growth_rollup
  where tenant_id = :tenant_id and student_id = :student_id and subject_id = :subject_id
    and canonical_term_id = :canonical_term_id and growth_window = :growth_window and norms_set = :norms_set
    and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null
),
completion as (
  select completion_scope, scope_id, xp_earned, xp_remaining, completion_percent, null_reason, source_import_id
  from alpha.analytics_completion_rollup
  where tenant_id = :tenant_id and student_id = :student_id
    and completion_scope = :completion_scope and scope_id = :scope_id
    and quality_status in ('ok','corrected') and superseded_at is null and source_deleted_at is null
)
select jsonb_build_object(
  'studentId', :student_id,
  'termId', :canonical_term_id,
  'panels', jsonb_build_object(
    'timeCommitment', (select to_jsonb(time_commitment) from time_commitment),
    'xpGoals', (select to_jsonb(xp) from xp),
    'accuracy', (select to_jsonb(accuracy) from accuracy),
    'masteryTransitions', coalesce((select deltas from mastery), '[]'::jsonb),
    'mapResults', (select to_jsonb(map) from map),
    'courseCompletion', (select to_jsonb(completion) from completion)
  )
) as learning_report_json;

Render these fields: panels.timeCommitment.active_minutes panels.timeCommitment.enrolled_school_day_count panels.timeCommitment.excluded_school_day_count panels.timeCommitment.minutes_per_enrolled_school_day panels.timeCommitment.null_reason panels.xpGoals.xp_total panels.xpGoals.net_xp panels.xpGoals.daily_xp_goal panels.xpGoals.enrolled_school_day_count panels.xpGoals.xp_remaining panels.xpGoals.xp_goal_percent panels.xpGoals.xp_completion_percent panels.xpGoals.source_import_id panels.xpGoals.null_reason panels.accuracy.correct_question_count panels.accuracy.total_question_count panels.accuracy.accuracy_percent panels.accuracy.source_import_id panels.masteryTransitions[] panels.mapResults.rit_score panels.mapResults.achievement_percentile panels.mapResults.growth_percentile panels.mapResults.observed_growth panels.mapResults.projected_growth panels.mapResults.typical_growth panels.mapResults.growth_x panels.mapResults.growth_x_target panels.mapResults.on_track panels.mapResults.sitting_count panels.mapResults.retake_count panels.mapResults.norms_set panels.mapResults.growth_window panels.mapResults.source_import_id panels.courseCompletion.completion_percent

Example Report JSON

{
  "studentId": "student_01HT7G3YZV7QB5N4YKQ1K0Z9A9",
  "termId": "term_2026_winter",
  "panels": {
    "timeCommitment": {
      "active_minutes": 4860,
      "enrolled_school_day_count": 90,
      "excluded_school_day_count": 61,
      "minutes_per_enrolled_school_day": 54,
      "quality_status": "ok",
      "null_reason": "none"
    },
    "xpGoals": {
      "xp_total": 11800,
      "positive_xp": 11850,
      "negative_xp": -50,
      "net_xp": 11800,
      "daily_xp_goal": 100,
      "enrolled_school_day_count": 90,
      "xp_goal": 9000,
      "xp_remaining": 0,
      "xp_goal_percent": 131.111,
      "xp_completion_percent": 131.111,
      "on_track": true,
      "source_import_id": "imp_01HT8XPTIME_2026_SPRING",
      "null_reason": "none",
      "award_count": 24,
      "reversal_count": 1
    },
    "accuracy": {
      "correct_question_count": 480,
      "total_question_count": 600,
      "incorrect_question_count": 120,
      "accuracy_percent": 80,
      "source_import_id": "imp_01HT8XPTIME_2026_SPRING",
      "null_reason": "none"
    },
    "masteryTransitions": [
      {
        "kcId": "kc_math_fraction_addition_unlike_denominators",
        "stateDimension": "durable_mastery",
        "transition": "acquired",
        "previousValue": {
          "value": 0.82
        },
        "newValue": {
          "value": 0.91
        },
        "effectiveAt": "2026-05-14T18:45:00Z"
      }
    ],
    "mapResults": {
      "rit_score": 239,
      "achievement_percentile": 91,
      "growth_percentile": 43,
      "observed_growth": 6,
      "typical_growth": 2,
      "projected_growth": 7,
      "growth_x": 0.8571,
      "growth_x_target": 2,
      "on_track": false,
      "sitting_count": 2,
      "retake_count": 1,
      "norms_set": "2025",
      "growth_window": "winter_to_winter",
      "source_import_id": "imp_01HT8MAP_2026_WINTER"
    },
    "courseCompletion": {
      "completion_scope": "course",
      "scope_id": "course_math_grade_4_powerpath",
      "xp_earned": 900,
      "xp_remaining": 300,
      "completion_percent": 75,
      "null_reason": "none"
    }
  }
}