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

[JohannesStoehr]

Checklist

General

• I tested all changes and their related features with all corresponding user types on a test server.
• I chose a title conforming to the naming conventions for pull requests.

Server

• Important: I implemented the changes with a very good performance and prevented too many (unnecessary) and too complex database calls.
• I strictly followed the principle of data economy for all database calls.
• I strictly followed the server coding and design guidelines.
• I added multiple integration tests (Spring) related to the features (with a high test coverage).
• I documented the Java code using JavaDoc style.

Motivation and Context

#8758

Description

Adapted scheduling of exercises in the learning path to respect the preferences regarding the inclusion of graded exercises.

This PR does not add any UI!

Steps for Testing

Prerequisites:

• 1 Instructor
• 1 Student

1. Log in to Artemis
2. Create or find a course with a few competencies and linked exercises and lecture units
3. Participate as student in the learning path and check that no errors occur

Testserver States

Note

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Review Progress

Performance Review

• I (as a reviewer) confirm that the client changes (in particular related to REST calls and UI responsiveness) are implemented with a very good performance even for very large courses with more than 2000 students.
• I (as a reviewer) confirm that the server changes (in particular related to database calls) are implemented with a very good performance even for very large courses with more than 2000 students.

Code Review

• Code Review 1
• Code Review 2

Manual Tests

• Test 1
• Test 2

Performance Tests

• Test 1
• Test 2

Test Coverage

Class/File	Line Coverage	Confirmation (assert/expect)
LearningPathRecommendationService.java	95%	✅
LearningPathService.java	88%	✅

Summary by CodeRabbit

Summary by CodeRabbit

• New Features

  • Introduced a preference scale enum for learner profiles.
  • Enhanced learning path recommendation system with personalized exercise selection.
  • Added support for course learner profiles and user profile management.

• Improvements

  • Updated learning path retrieval to include learner profiles.
  • Refined exercise recommendation logic based on user preferences.
  • Improved data fetching methods in repositories.

• Technical Updates

  • Added new repository and service methods for learner profile management.
  • Updated integration and unit tests to support new profile-related functionality.
  • Modified caching strategy for course learner profiles in the learner profile class.

[ardakaraman0]

Re-approval

[raffifasaro]

re-approve

[ufukygmr]

LGTM 🚀

[Cathy0123456789]

Re-tested on TS1. Everything works great, the former problem does not occur anymore

[N0W0RK]

retestet on TS1. All works as expected.

[zagemello]

Re-approved

[MaximilianAnzinger]

Maintainer approved