Adaptive learning: Add implementation for grade or bonus goal in learner profile

src/main/java/de/tum/cit/aet/artemis/atlas/domain/profile/PreferenceScale.java

@@ -0,0 +1,19 @@
+package de.tum.cit.aet.artemis.atlas.domain.profile;
+
+/**
+ * Enum for the preferences as lickert-scale regarding settings in the (course) learner profile, see {@link CourseLearnerProfile} and {@link LearnerProfile}.
+ */
+public enum PreferenceScale {
+
+    LOW(1), MEDIUM_LOW(2), MEDIUM(3), MEDIUM_HIGH(4), HIGH(5);
+
+    private final int value;
+
+    PreferenceScale(int value) {
+        this.value = value;
+    }
+
+    public int getValue() {
+        return value;
+    }
+}

src/main/java/de/tum/cit/aet/artemis/atlas/repository/CourseLearnerProfileRepository.java

@@ -28,5 +28,5 @@ public interface CourseLearnerProfileRepository extends ArtemisJpaRepository<Cou
 
     @Transactional // ok because of delete
     @Modifying
-    void deleteAllByCourse(Course couese);
+    void deleteAllByCourse(Course course);
 }

src/main/java/de/tum/cit/aet/artemis/atlas/repository/LearningPathRepository.java

@@ -36,6 +36,13 @@ default LearningPath findWithEagerUserByIdElseThrow(long learningPathId) {
     @EntityGraph(type = LOAD, attributePaths = { "competencies" })
     Optional<LearningPath> findWithEagerCompetenciesByCourseIdAndUserId(long courseId, long userId);
 
+    @EntityGraph(type = LOAD, attributePaths = { "course" })
+    Optional<LearningPath> findWithEagerCourseById(long learningPathId);
+
+    default LearningPath findWithEagerCourseByIdElseThrow(long learningPathId) {
+        return getValueElseThrow(findWithEagerCourseById(learningPathId), learningPathId);
+    }
+
     @EntityGraph(type = LOAD, attributePaths = { "course", "competencies" })
     Optional<LearningPath> findWithEagerCourseAndCompetenciesById(long learningPathId);
 
@@ -63,11 +70,23 @@ SELECT COUNT (learningPath)
             """)
     long countLearningPathsOfEnrolledStudentsInCourse(@Param("courseId") long courseId);
 
-    @EntityGraph(type = LOAD, attributePaths = { "competencies", "competencies.lectureUnitLinks", "competencies.lectureUnitLinks.lectureUnit", "competencies.exerciseLinks",
-            "competencies.exerciseLinks.exercise" })
-    Optional<LearningPath> findWithCompetenciesAndLectureUnitsAndExercisesById(long learningPathId);
+    @Query("""
+            SELECT l
+            FROM LearningPath l
+            LEFT JOIN FETCH l.competencies c
+            LEFT JOIN FETCH c.lectureUnitLinks lul
+            LEFT JOIN FETCH lul.lectureUnit
+            LEFT JOIN FETCH c.exerciseLinks el
+            LEFT JOIN FETCH el.exercise
+            LEFT JOIN FETCH l.user u
+            LEFT JOIN FETCH u.learnerProfile lp
+            LEFT JOIN FETCH lp.courseLearnerProfiles clp
+            WHERE l.id = :learningPathId
+                AND clp.course.id = l.course.id
+            """)
+    Optional<LearningPath> findWithCompetenciesAndLectureUnitsAndExercisesAndLearnerProfileById(@Param("learningPathId") long learningPathId);
 
-    default LearningPath findWithCompetenciesAndLectureUnitsAndExercisesByIdElseThrow(long learningPathId) {
-        return getValueElseThrow(findWithCompetenciesAndLectureUnitsAndExercisesById(learningPathId), learningPathId);
+    default LearningPath findWithCompetenciesAndLectureUnitsAndExercisesAndLearnerProfileByIdElseThrow(long learningPathId) {
+        return getValueElseThrow(findWithCompetenciesAndLectureUnitsAndExercisesAndLearnerProfileById(learningPathId), learningPathId);
     }
 }

src/main/java/de/tum/cit/aet/artemis/atlas/service/learningpath/LearningPathRecommendationService.java

@@ -1,6 +1,10 @@
 package de.tum.cit.aet.artemis.atlas.service.learningpath;
 
+import static de.tum.cit.aet.artemis.atlas.domain.profile.PreferenceScale.HIGH;
+import static de.tum.cit.aet.artemis.atlas.domain.profile.PreferenceScale.MEDIUM_HIGH;
 import static de.tum.cit.aet.artemis.core.config.Constants.PROFILE_CORE;
+import static de.tum.cit.aet.artemis.exercise.domain.IncludedInOverallScore.INCLUDED_AS_BONUS;
+import static de.tum.cit.aet.artemis.exercise.domain.IncludedInOverallScore.INCLUDED_COMPLETELY;
 
 import java.time.ZonedDateTime;
 import java.time.temporal.ChronoUnit;
@@ -14,6 +18,7 @@
 import java.util.Optional;
 import java.util.Set;
 import java.util.function.Function;
+import java.util.function.Predicate;
 import java.util.stream.Collectors;
 import java.util.stream.Stream;
 
@@ -31,6 +36,7 @@
 import de.tum.cit.aet.artemis.atlas.domain.competency.LearningPath;
 import de.tum.cit.aet.artemis.atlas.domain.competency.Prerequisite;
 import de.tum.cit.aet.artemis.atlas.domain.competency.RelationType;
+import de.tum.cit.aet.artemis.atlas.domain.profile.CourseLearnerProfile;
 import de.tum.cit.aet.artemis.atlas.repository.CompetencyProgressRepository;
 import de.tum.cit.aet.artemis.atlas.repository.CompetencyRelationRepository;
 import de.tum.cit.aet.artemis.atlas.repository.CourseCompetencyRepository;
@@ -39,6 +45,7 @@
 import de.tum.cit.aet.artemis.exercise.domain.BaseExercise;
 import de.tum.cit.aet.artemis.exercise.domain.DifficultyLevel;
 import de.tum.cit.aet.artemis.exercise.domain.Exercise;
+import de.tum.cit.aet.artemis.exercise.domain.IncludedInOverallScore;
 import de.tum.cit.aet.artemis.lecture.domain.LectureUnit;
 import de.tum.cit.aet.artemis.lecture.service.LearningObjectService;
 
@@ -98,6 +105,8 @@ public class LearningPathRecommendationService {
     private static final double[][] EXERCISE_DIFFICULTY_DISTRIBUTION_LUT = new double[][] { { 0.87, 0.12, 0.01 }, { 0.80, 0.18, 0.02 }, { 0.72, 0.25, 0.03 }, { 0.61, 0.33, 0.06 },
             { 0.50, 0.40, 0.10 }, { 0.39, 0.45, 0.16 }, { 0.28, 0.48, 0.24 }, { 0.20, 0.47, 0.33 }, { 0.13, 0.43, 0.44 }, { 0.08, 0.37, 0.55 }, { 0.04, 0.29, 0.67 }, };
 
+    private static final double COMPETENCY_LINK_WEIGHT_TO_GRADE_AIM_RATIO = 2;
+
     protected LearningPathRecommendationService(CompetencyRelationRepository competencyRelationRepository, LearningObjectService learningObjectService,
             ParticipantScoreService participantScoreService, CompetencyProgressRepository competencyProgressRepository, CourseCompetencyRepository courseCompetencyRepository) {
         this.competencyRelationRepository = competencyRelationRepository;
@@ -476,6 +485,9 @@ public List<LearningObject> getRecommendedOrderOfLearningObjects(User user, Cour
      * @return the recommended ordering of learning objects
      */
     public List<LearningObject> getRecommendedOrderOfLearningObjects(User user, CourseCompetency competency, double combinedPriorConfidence) {
+        var learnerProfile = user.getLearnerProfile();
+        var courseLearnerProfile = learnerProfile.getCourseLearnerProfiles().stream().findFirst().orElse(new CourseLearnerProfile());
+
         var pendingLectureUnits = competency.getLectureUnitLinks().stream().map(CompetencyLectureUnitLink::getLectureUnit).filter(lectureUnit -> !lectureUnit.isCompletedFor(user))
                 .toList();
         List<LearningObject> recommendedOrder = new ArrayList<>(pendingLectureUnits);
@@ -492,8 +504,7 @@ public List<LearningObject> getRecommendedOrderOfLearningObjects(User user, Cour
 
         // First sort exercises based on title to ensure consistent ordering over multiple calls then prefer higher weighted exercises
         final var pendingExercises = competency.getExerciseLinks().stream().filter(link -> !learningObjectService.isCompletedByUser(link.getExercise(), user))
-                .sorted(Comparator.comparing(link -> link.getExercise().getTitle())).sorted(Comparator.comparingDouble(CompetencyExerciseLink::getWeight).reversed())
-                .map(CompetencyExerciseLink::getExercise).toList();
+                .sorted(getExerciseOrderComparator(courseLearnerProfile.getAimForGradeOrBonus())).map(CompetencyExerciseLink::getExercise).toList();
 
         final var pendingExercisePoints = pendingExercises.stream().mapToDouble(BaseExercise::getMaxPoints).sum();
 
@@ -504,7 +515,7 @@ public List<LearningObject> getRecommendedOrderOfLearningObjects(User user, Cour
         }
         final var recommendedExerciseDistribution = getRecommendedExercisePointDistribution(numberOfRequiredExercisePointsToMaster, weightedConfidence);
 
-        scheduleExercisesByDistribution(recommendedOrder, recommendedExerciseDistribution, difficultyLevelMap);
+        scheduleExercisesByDistribution(recommendedOrder, recommendedExerciseDistribution, difficultyLevelMap, courseLearnerProfile);
         return recommendedOrder;
     }
 
@@ -528,30 +539,30 @@ private void scheduleAllExercises(List<LearningObject> recommendedOrder, Map<Dif
      * @param difficultyMap                        a map from difficulty level to a set of corresponding exercises
      */
     private void scheduleExercisesByDistribution(List<LearningObject> recommendedOrder, double[] recommendedExercisePointDistribution,
-            Map<DifficultyLevel, List<Exercise>> difficultyMap) {
+            Map<DifficultyLevel, List<Exercise>> difficultyMap, CourseLearnerProfile courseLearnerProfile) {
         final var easyExercises = new ArrayList<Exercise>();
         final var mediumExercises = new ArrayList<Exercise>();
         final var hardExercises = new ArrayList<Exercise>();
 
         // choose as many exercises from the correct difficulty level as possible
-        final var missingEasy = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.EASY, recommendedExercisePointDistribution[0], easyExercises);
-        final var missingHard = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.HARD, recommendedExercisePointDistribution[2], hardExercises);
+        final var missingEasy = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.EASY, recommendedExercisePointDistribution[0], easyExercises, courseLearnerProfile);
+        final var missingHard = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.HARD, recommendedExercisePointDistribution[2], hardExercises, courseLearnerProfile);
 
         // if there are not sufficiently many exercises per difficulty level, prefer medium difficulty
         // case 1: no medium exercises available/medium exercises missing: continue to fill with easy/hard exercises
         // case 2: medium exercises available: no medium exercises missing -> missing exercises must be easy/hard -> in both scenarios medium is the closest difficulty level
         double mediumExercisePoints = recommendedExercisePointDistribution[1] + missingEasy + missingHard;
-        double numberOfMissingExercisePoints = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.MEDIUM, mediumExercisePoints, mediumExercises);
+        double numberOfMissingExercisePoints = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.MEDIUM, mediumExercisePoints, mediumExercises, courseLearnerProfile);
 
         // if there are still not sufficiently many medium exercises, choose easy difficulty
         // prefer easy to hard exercises to avoid student overload
         if (numberOfMissingExercisePoints > 0 && !difficultyMap.get(DifficultyLevel.EASY).isEmpty()) {
-            numberOfMissingExercisePoints = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.EASY, numberOfMissingExercisePoints, easyExercises);
+            numberOfMissingExercisePoints = selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.EASY, numberOfMissingExercisePoints, easyExercises, courseLearnerProfile);
         }
 
         // fill remaining slots with hard difficulty
         if (numberOfMissingExercisePoints > 0 && !difficultyMap.get(DifficultyLevel.HARD).isEmpty()) {
-            selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.HARD, numberOfMissingExercisePoints, hardExercises);
+            selectExercisesWithDifficulty(difficultyMap, DifficultyLevel.HARD, numberOfMissingExercisePoints, hardExercises, courseLearnerProfile);
         }
 
         recommendedOrder.addAll(easyExercises);
@@ -571,15 +582,62 @@ private void scheduleExercisesByDistribution(List<LearningObject> recommendedOrd
      * @return amount of points that are missing, if negative the amount of points that are selected too much
      */
     private static double selectExercisesWithDifficulty(Map<DifficultyLevel, List<Exercise>> difficultyMap, DifficultyLevel difficulty, double exercisePoints,
-            List<Exercise> exercises) {
+            List<Exercise> exercises, CourseLearnerProfile courseLearnerProfile) {
         var remainingExercisePoints = new AtomicDouble(exercisePoints);
-        var selectedExercises = difficultyMap.get(difficulty).stream().takeWhile(exercise -> remainingExercisePoints.getAndAdd(-exercise.getMaxPoints()) >= 0)
-                .collect(Collectors.toSet());
+
+        Predicate<Exercise> exercisePredicate = getExerciseSelectionPredicate(courseLearnerProfile.getAimForGradeOrBonus(), remainingExercisePoints);
+
+        var selectedExercises = difficultyMap.get(difficulty).stream().takeWhile(exercisePredicate).toList();
+
         exercises.addAll(selectedExercises);
         difficultyMap.get(difficulty).removeAll(selectedExercises);
         return remainingExercisePoints.get();
     }
 
+    private static int getIncludeInOverallScoreWeight(IncludedInOverallScore includedInOverallScore) {
+        return switch (includedInOverallScore) {
+            case INCLUDED_COMPLETELY -> 0;
+            case INCLUDED_AS_BONUS -> 1;
+            case NOT_INCLUDED -> 2;
+        };
+    }
+
+    /**
+     * Creates a comparator that orders exercises based on the aim for grade or bonus, the link weight for the current competency and as a tiebreaker the lexicographic order of
+     * the exercise title. The higher the aim for the grade bonus is, the higher this metric is weighted compared to the link weight.
+     *
+     * @param aimForGradeOrBonus the aim for grade or bonus
+     * @return the comparator that orders the exercise based on the preference
+     */
+    private static Comparator<CompetencyExerciseLink> getExerciseOrderComparator(int aimForGradeOrBonus) {
+        Comparator<CompetencyExerciseLink> exerciseComparator = Comparator.comparingDouble(exerciseLink -> (COMPETENCY_LINK_WEIGHT_TO_GRADE_AIM_RATIO * exerciseLink.getWeight())
+                + aimForGradeOrBonus * getIncludeInOverallScoreWeight(exerciseLink.getExercise().getIncludedInOverallScore()));
+        exerciseComparator = exerciseComparator.reversed();
+
+        exerciseComparator = exerciseComparator.thenComparing(exerciseLink -> exerciseLink.getExercise().getTitle());
+        return exerciseComparator;
+    }
+
+    /**
+     * Creates a predicate that selects exercises based on the aim for grade or bonus and the remaining exercise points.
+     *
+     * @param aimForGradeOrBonus      the aim for grade or bonus
+     * @param remainingExercisePoints the remaining exercise points that should be scheduled
+     * @return the predicate until when exercises should be selected based on the preference
+     */
+    private static Predicate<Exercise> getExerciseSelectionPredicate(int aimForGradeOrBonus, AtomicDouble remainingExercisePoints) {
+        Predicate<Exercise> exercisePredicate = exercise -> remainingExercisePoints.getAndAdd(-exercise.getMaxPoints()) >= 0;
+        if (aimForGradeOrBonus == HIGH.getValue()) {
+            exercisePredicate = exercisePredicate
+                    .or(exercise -> exercise.getIncludedInOverallScore() == INCLUDED_COMPLETELY || exercise.getIncludedInOverallScore() == INCLUDED_AS_BONUS);
+        }
+        else if (aimForGradeOrBonus == MEDIUM_HIGH.getValue()) {
+            exercisePredicate = exercisePredicate.or(exercise -> exercise.getIncludedInOverallScore() == INCLUDED_COMPLETELY);
+        }
+
+        return exercisePredicate;
+    }
+
     /**
      * Computes the average confidence of all prior competencies.
      *

src/main/java/de/tum/cit/aet/artemis/atlas/service/learningpath/LearningPathService.java

@@ -132,6 +132,7 @@ public void enableLearningPathsForCourse(@NotNull Course course) {
      */
     public void generateLearningPaths(@NotNull Course course) {
         var students = userRepository.getStudentsWithLearnerProfile(course);
+        courseLearnerProfileService.createCourseLearnerProfiles(course, students);
         generateLearningPaths(course, students);
     }
 
@@ -401,7 +402,7 @@ public LearningPathCompetencyGraphDTO generateLearningPathCompetencyInstructorGr
      * @return the navigation overview
      */
     public LearningPathNavigationOverviewDTO getLearningPathNavigationOverview(long learningPathId) {
-        var learningPath = findWithCompetenciesAndReleasedLearningObjectsAndCompletedUsersById(learningPathId);
+        var learningPath = findWithCompetenciesAndReleasedLearningObjectsAndCompletedUsersAndLearnerProfileById(learningPathId);
         if (!userRepository.getUser().equals(learningPath.getUser())) {
             throw new AccessForbiddenException("You are not allowed to access this learning path");
         }
@@ -417,8 +418,17 @@ public LearningPathNavigationOverviewDTO getLearningPathNavigationOverview(long
      * @param learningPathId the id of the learning path to fetch
      * @return the learning path with fetched data
      */
-    public LearningPath findWithCompetenciesAndReleasedLearningObjectsAndCompletedUsersById(long learningPathId) {
-        LearningPath learningPath = learningPathRepository.findWithCompetenciesAndLectureUnitsAndExercisesByIdElseThrow(learningPathId);
+    public LearningPath findWithCompetenciesAndReleasedLearningObjectsAndCompletedUsersAndLearnerProfileById(long learningPathId) {
+        Optional<LearningPath> optionalLearningPath = learningPathRepository.findWithCompetenciesAndLectureUnitsAndExercisesAndLearnerProfileById(learningPathId);
+        LearningPath learningPath;
+        if (optionalLearningPath.isEmpty()) {
+            LearningPath learningPathWithCourse = learningPathRepository.findWithEagerCourseByIdElseThrow(learningPathId);
+            courseLearnerProfileService.createCourseLearnerProfile(learningPathWithCourse.getCourse(), learningPathWithCourse.getUser());
+            learningPath = learningPathRepository.findWithCompetenciesAndLectureUnitsAndExercisesAndLearnerProfileByIdElseThrow(learningPathId);
+        }
+        else {
+            learningPath = optionalLearningPath.get();
+        }
 
         // Remove exercises that are not visible to students
         learningPath.getCompetencies().forEach(competency -> competency