feat(bisaya): enhance situational response exercises with keyword hints and minimum match requirements

backend/migrations-active/20260825000000-repair-lesson-39-situational-response.cjs

@@ -0,0 +1,50 @@
+'use strict';
+
+const OLD_QUESTION = 'Erzähle einen Tagesplan mit drei Schritten und einem Wunsch.';
+const REPAIRED_QUESTION = 'Schreibe vier kurze Sätze auf Bisaya. Verwende dabei alle diese Bausteine: Una, Pagkahuman, Unya und Gusto ko nga.';
+const KEYWORDS = ['una', 'pagkahuman', 'unya', 'gusto ko nga'];
+const MODEL_ANSWER = 'Una, moadto ko sa merkado. Pagkahuman, kuhaon nako ang bata. Unya, mouli mi sa balay. Gusto ko nga magkita ta ugma.';
+
+module.exports = {
+  async up(queryInterface) {
+    await queryInterface.sequelize.transaction(async (transaction) => {
+      // This was an open-ended production prompt, but the checker required four
+      // hidden words. Make both the expected language and the four criteria
+      // explicit, while still accepting every answer that fulfils them.
+      await queryInterface.sequelize.query(`
+        UPDATE community.vocab_grammar_exercise AS exercise
+        SET question_data = JSONB_SET(
+              JSONB_SET(
+                JSONB_SET(exercise.question_data, '{question}', TO_JSONB(CAST(:repairedQuestion AS text))),
+                '{keywords}', CAST(:keywords AS jsonb)
+              ),
+              '{minKeywordMatches}', '4'::jsonb
+            ),
+            answer_data = JSONB_SET(
+              JSONB_SET(
+                JSONB_SET(COALESCE(exercise.answer_data, '{}'::jsonb), '{modelAnswer}', TO_JSONB(CAST(:modelAnswer AS text))),
+                '{keywords}', CAST(:keywords AS jsonb)
+              ),
+              '{minKeywordMatches}', '4'::jsonb
+            )
+        FROM community.vocab_course_lesson AS lesson
+        WHERE exercise.lesson_id = lesson.id
+          AND (lesson.id = 39 OR (lesson.course_id = 1 AND lesson.lesson_number = 39))
+          AND exercise.question_data->>'type' = 'situational_response'
+          AND exercise.question_data->>'question' = :oldQuestion;
+      `, {
+        replacements: {
+          oldQuestion: OLD_QUESTION,
+          repairedQuestion: REPAIRED_QUESTION,
+          keywords: JSON.stringify(KEYWORDS),
+          modelAnswer: MODEL_ANSWER
+        },
+        transaction
+      });
+    });
+  },
+
+  async down() {
+    // Keep the unambiguous exercise wording once deployed.
+  }
+};

backend/scripts/create-bisaya-course-content.js

@@ -761,18 +761,24 @@ function buildSituationalExercise(lessonTitle, didactics, fallbackPattern) {
     .split(' ')
     .filter((token) => token.length >= 4)
     .slice(0, 4);
+  const requiredParts = keywords.length > 0 ? keywords : [modelAnswer];
+  const question = speakingPrompt?.prompt
+    ? `${speakingPrompt.prompt} Schreibe auf Bisaya und verwende diese Bausteine: ${requiredParts.join(', ')}.`
+    : `Reagiere passend mit einem Ausdruck aus der Lektion „${lessonTitle}“. Verwende: ${requiredParts.join(', ')}.`;
 
   return withTypeName('situational_response', {
     title: `${lessonTitle}: Situativ reagieren`,
-    instruction: 'Antworte kurz und passend auf die Situation.',
+    instruction: 'Antworte auf Bisaya. Die angezeigten Bausteine müssen in deiner Antwort vorkommen.',
     questionData: {
       type: 'situational_response',
-      question: speakingPrompt?.prompt || `Reagiere passend mit einem Ausdruck aus der Lektion "${lessonTitle}".`,
-      keywords
+      question,
+      keywords: requiredParts,
+      minKeywordMatches: requiredParts.length
     },
     answerData: {
       modelAnswer,
-      keywords
+      keywords: requiredParts,
+      minKeywordMatches: requiredParts.length
     },
     explanation: `Das Kernmuster "${modelAnswer}" passt natürlich zu dieser Situation.`
   });

backend/services/vocabService.js

@@ -4593,7 +4593,17 @@ export default class VocabService {
         const keywords = parsedQuestionData.keywords || parsedAnswerData.keywords || [];
         if (keywords.length > 0) {
           const normalizedUser = this._normalizeTextAnswer(userAnswer);
-          return keywords.every((keyword) => normalizedUser.includes(this._normalizeTextAnswer(keyword)));
+          const matches = keywords.filter((keyword) => (
+            normalizedUser.includes(this._normalizeTextAnswer(keyword))
+          )).length;
+          const configuredMinimum = Number(
+            parsedQuestionData.minKeywordMatches ?? parsedAnswerData.minKeywordMatches
+          );
+          const requiredMatches = Number.isInteger(configuredMinimum)
+            && configuredMinimum > 0
+            ? Math.min(configuredMinimum, keywords.length)
+            : keywords.length;
+          return matches >= requiredMatches;
         }
       }
 

frontend/src/views/social/VocabLessonView.vue

@@ -784,6 +784,10 @@
 
           <div v-else-if="getExerciseType(exercise) === 'situational_response'" class="situational-response-exercise">
             <p v-if="getVisibleQuestionText(exercise)" class="exercise-question">{{ getVisibleQuestionText(exercise) }}</p>
+            <div v-if="getQuestionData(exercise)?.keywords?.length" class="keywords-hint">
+              <strong>{{ $t('socialnetwork.vocab.courses.keywords') }}:</strong>
+              <span v-for="(keyword, idx) in getQuestionData(exercise).keywords" :key="idx" class="keyword-tag">{{ keyword }}</span>
+            </div>
             <textarea
               v-model="exerciseAnswers[exercise.id]"
               :placeholder="$t('socialnetwork.vocab.courses.situationalResponsePlaceholder')"