Modeling exercises: Add preliminary AI feedback requests for students

[LeonWehrhahn]

Checklist

General

• I tested all changes and their related features with all corresponding user types on a test server.
• Language: I followed the guidelines for inclusive, diversity-sensitive, and appreciative language.
• 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 added pre-authorization annotations according to the guidelines and checked the course groups for all new REST Calls (security).
• I documented the Java code using JavaDoc style.

Client

• Important: I implemented the changes with a very good performance, prevented too many (unnecessary) REST calls and made sure the UI is responsive, even with large data (e.g. using paging).
• I strictly followed the principle of data economy for all client-server REST calls.
• I strictly followed the client coding and design guidelines.
• I added multiple integration tests (Jest) related to the features (with a high test coverage), while following the test guidelines.
• I added authorities to all new routes and checked the course groups for displaying navigation elements (links, buttons).
• I documented the TypeScript code using JSDoc style.
• I added multiple screenshots/screencasts of my UI changes.

Motivation and Context

Currently, students cannot receive feedback on modeling exercises, except by asking tutors. This PR aims to change that by enabling the option for students to request AI feedback on their modeling exercises.

Description

This PR does not focus on the quality of the feedback generation, other Athena PRs, e.g. #340 address this

This PR builds upon Enea's Text exercises Preliminary AI Feedback and also introduces AI-generated feedback for Modeling Exercises.

In Modeling Exercises, a new option now allows students to request AI-generated feedback, with a predefined limit on the number of requests per student. Once requested, the feedback is automatically saved and attached to the relevant submission. Students can request feedback once for each submission.

Previously, modeling exercises operated with a single, continuously updated submission. Now, if Athena feedback is attached to an existing submission, a new submission will be created when a student resubmits their work.

Additionally, tutor assessments have been updated to ignore Athena feedback and retrieve the latest submission, rather than defaulting to the initial one as was previously the case.

Steps for Testing

Only Deploy to TS1

1. Instructor Setup:

• Create a new modeling exercise with the AI feedback option enabled.
• Optionally, include grading instructions to guide the assessment.

2. Student Participation:

• Log in as a student, submit a solution for the modeling exercise, and request AI feedback (up to 10 times). To request AI feedback click on the "Request AI feedback" button

Check:

• Each AI feedback request should create a new submission and return feedback.
• The student should be able to continue modifying the submission even after receiving feedback.
• AI feedback results must be visible before the due date and assessment due date.
• Results should appear as GRADED and tagged as PRELIMINARY in the detailed view.

3. Instructor Assessment:

• Log in as the instructor and begin the assessment process.

Check:

• Confirm that the latest student submission is retrieved (verify in the participations or scores tab).
• Ensure that the assessment process works as expected, with the student seeing the final result.
• Verify that complaint and complaint assessment functionalities continue to work as usual.

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

Exam Mode Test

• Test 1
• Test 2

Performance Tests

• Test 1
• Test 2

Test Coverage

Screenshots

Feedback View

Submission History View

Screencast of Feedback Generation Flow

Bildschirmaufnahme.2024-09-12.um.23.28.36.mov

Summary by CodeRabbit

Summary by CodeRabbit

Release Notes

• New Features

  • Expanded feedback request support for modeling exercises, allowing students to receive feedback for both text and modeling exercises.
  • Introduced a new service for handling feedback requests specifically for modeling exercises, utilizing AI-generated suggestions.
  • Enhanced result display logic to filter results for both TEXT and MODELING exercises based on success criteria.
  • Enabled preliminary feedback for modeling exercises before the assessment due date.
  • Improved dynamic feature availability checks based on exercise type in the user interface.

• Bug Fixes

  • Improved logic to prevent runtime errors related to feedback assignment in the modeling assessment editor.

• Tests

  • Added new test cases to ensure proper functionality for feedback requests and result handling in modeling exercises.

[coolchock]

re-approve after bug fix

[EneaGore]

re-approve after bug fix

[eceeeren]

Re-approve after bug fix

[pzdr7]

Reapprove

[maximiliansoelch]

Code