Add pure correction and pedagogy logic with full test coverage

scripts/correction/: AnswerValidator (multiple choice, sentence
correction via tap-the-faulty-word + retype) and DictationAnalyzer
build the CorrectionResult structure from cahier des charges §6.
Dictation analysis aligns words with WordAligner (Wagner-Fischer edit
distance) before any character comparison, so an omitted or added
word doesn't cascade into false errors on every following word.
TextNormalizer handles non-breaking spaces, typographic apostrophes,
and decomposed-vs-composed French accented characters via an
explicit table (GDScript has no built-in NFC/NFD normalization).
Error classification follows the data annotations only (rule_id
present -> grammatical, absent -> unclassified), never a runtime
linguistic guess.

scripts/pedagogy/: DifficultyManager (per-skill difficulty from
recent results), AttemptFlow (3-attempt graduated aid: hint, then
explanation, then reveal, matching exercise-lifecycle.md's second
gap), and ReviewScheduler (the five mastery states from §9, with
session-counted spaced review intervals [1, 3, 6, 12] rather than
wall-clock dates, since a family device's clock isn't trustworthy).

All of it is pure: no scene tree, no clock or RNG read directly,
every effectful input (session number, attempt outcome) is a
parameter. 65 headless tests across both layers, including the
word-omission-doesn't-cascade regression and the full
decouverte -> acquise -> a_reviser -> acquise path.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
Denis Defolie
2026-10-11 17:03:14 +02:00
parent d057c8ee77
commit 2fe455f5d1
36 changed files with 1111 additions and 28 deletions
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class_name AnswerValidator
extends RefCounted
## Valide une reponse de choix multiple ou de correction de phrase et produit
## la structure de correction du §6 (voir CorrectionResult). Code pur : aucune
## dependance a l'arbre de scenes, aucune horloge, aucun hasard.
static func validate_multiple_choice(
exercise: Dictionary, selected_answer: int
) -> CorrectionResult:
var correct_answer: int = exercise["correct_answer"]
if selected_answer == correct_answer:
return CorrectionResult.correct(exercise["explanation"])
var answers: Array = exercise["answers"]
var found := ""
if selected_answer >= 0 and selected_answer < answers.size():
found = answers[selected_answer]
var expected: String = answers[correct_answer]
var error := {
"position": 0,
"error_type": "grammatical",
"rule_id": exercise["rule_id"],
"found": found,
"expected": expected,
}
return CorrectionResult.incorrect(
[error], exercise["explanation"], exercise["hint"], [expected]
)
## selected_indices : index des tokens que l'enfant a touches comme fautifs.
## corrections : correction saisie pour chaque token touche (cle = index du
## token, valeur = texte saisi).
static func validate_sentence_correction(
exercise: Dictionary, selected_indices: Array[int], corrections: Dictionary
) -> CorrectionResult:
var tokens: Array = exercise["tokens"]
var errors: Array[Dictionary] = []
for i in tokens.size():
var token: Dictionary = tokens[i]
var is_faulty: bool = token.get("correct", true) == false
var was_selected: bool = selected_indices.has(i)
if is_faulty and not was_selected:
errors.append(_missed_error(i, token, exercise))
elif is_faulty and was_selected:
var submitted: String = corrections.get(i, "")
if submitted != token["expected"]:
errors.append(_wrong_correction_error(i, submitted, token, exercise))
elif not is_faulty and was_selected:
errors.append(_false_positive_error(i, token, exercise))
if errors.is_empty():
return CorrectionResult.correct(exercise["explanation"])
var remediation: Array[String] = []
for token: Dictionary in tokens:
if token.get("correct", true) == false:
remediation.append(token["expected"])
return CorrectionResult.incorrect(
errors, exercise["explanation"], exercise["hint"], remediation
)
static func _missed_error(index: int, token: Dictionary, exercise: Dictionary) -> Dictionary:
return {
"position": index,
"error_type": "grammatical",
"rule_id": token.get("rule_id", exercise["rule_id"]),
"found": token["text"],
"expected": token["expected"],
}
static func _wrong_correction_error(
index: int, submitted: String, token: Dictionary, exercise: Dictionary
) -> Dictionary:
return {
"position": index,
"error_type": "grammatical",
"rule_id": token.get("rule_id", exercise["rule_id"]),
"found": submitted,
"expected": token["expected"],
}
static func _false_positive_error(
index: int, token: Dictionary, exercise: Dictionary
) -> Dictionary:
return {
"position": index,
"error_type": "unclassified",
"rule_id": exercise["rule_id"],
"found": token["text"],
"expected": token["text"],
}