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>

scripts/correction/word_aligner.gd

@@ -0,0 +1,55 @@
+class_name WordAligner
+extends RefCounted
+## Alignement mot a mot entre le texte cible et la production de l'enfant
+## (distance d'edition, algorithme de Wagner-Fischer), avant toute comparaison
+## caractere par caractere : sans cela, un mot omis ou ajoute decale tous les
+## mots suivants et les transforme en erreurs (voir "Points durs" du prompt de
+## lancement).
+
+
+## Chaque operation : {"op": "match" | "substitute" | "delete" | "insert",
+## "target_index": int (-1 si insert), "submitted_index": int (-1 si delete)}.
+## "delete" = mot du texte cible absent de la production ; "insert" = mot
+## ajoute par l'enfant, absent du texte cible.
+static func align(target_words: Array[String], submitted_words: Array[String]) -> Array[Dictionary]:
+    var n := target_words.size()
+    var m := submitted_words.size()
+
+    var cost: Array = []
+    for i in n + 1:
+        var row: Array[int] = []
+        for _j in m + 1:
+            row.append(0)
+        cost.append(row)
+    for i in n + 1:
+        cost[i][0] = i
+    for j in m + 1:
+        cost[0][j] = j
+
+    for i in range(1, n + 1):
+        for j in range(1, m + 1):
+            if target_words[i - 1] == submitted_words[j - 1]:
+                cost[i][j] = cost[i - 1][j - 1]
+            else:
+                cost[i][j] = 1 + mini(mini(cost[i - 1][j], cost[i][j - 1]), cost[i - 1][j - 1])
+
+    var ops: Array[Dictionary] = []
+    var i := n
+    var j := m
+    while i > 0 or j > 0:
+        if i > 0 and j > 0 and target_words[i - 1] == submitted_words[j - 1]:
+            ops.append({"op": "match", "target_index": i - 1, "submitted_index": j - 1})
+            i -= 1
+            j -= 1
+        elif i > 0 and j > 0 and cost[i][j] == cost[i - 1][j - 1] + 1:
+            ops.append({"op": "substitute", "target_index": i - 1, "submitted_index": j - 1})
+            i -= 1
+            j -= 1
+        elif i > 0 and cost[i][j] == cost[i - 1][j] + 1:
+            ops.append({"op": "delete", "target_index": i - 1, "submitted_index": -1})
+            i -= 1
+        else:
+            ops.append({"op": "insert", "target_index": -1, "submitted_index": j - 1})
+            j -= 1
+    ops.reverse()
+    return ops