Course Management

This guide covers administrative operations for course management, including course reset and course archiving functionality. These operations are only available to system administrators.

Course Reset

The Course Reset operation allows administrators to clear all student data from a course while preserving the course structure. This is useful for:

• Data privacy compliance (e.g., GDPR) - removing student data after a semester ends
• Reusing course templates - preparing a course for a new cohort of students
• Testing purposes - resetting a test course to its initial state

warning

The course reset operation cannot be undone. Before performing a reset, consider archiving the course to preserve student data for future reference.

What is Preserved vs Deleted

The following tables show exactly what data is affected by a course reset:

Data that is PRESERVED (kept after reset)

Category	Data Type	Description
Course Structure	Course settings	Title, description, dates, groups, all configuration
	Exercises	All exercise definitions (programming, text, modeling, quiz, file upload)
	Exercise materials	Problem statements, grading criteria, example solutions
	Programming exercise repos	Template, solution, and test repositories
	Exams	Exam definitions, exercise groups, registered students list structure
	Lectures	Lecture content, attachments, units
	Competencies	Competency definitions and relations
	Tutorial groups	Tutorial group definitions and schedules (but not student registrations)
Communication	Channels/Conversations	Channel and conversation structure (but not messages)
Staff	Instructors	All instructor assignments

Data that is DELETED (removed during reset)

Category	Data Type	Description
Exercise Data	Participations	All student exercise participations
	Submissions	All student submissions (code, text, models, files)
	Results	All assessment results and scores
	Feedbacks	All manual and automatic feedback
	Build results	Programming exercise build logs and results
	Plagiarism cases	All plagiarism detection results
Exam Data	Student exams	All student exam instances
	Exam participations	All exam exercise participations
	Exam submissions	All exam submissions and results
	Exam grades	All exam grading data
Learning Analytics	Competency progress	Student progress on competencies
	Learner profiles	Course-specific learner profile data
	Participant scores	Cached scores for exercises
Communication	Posts	All posts in channels and conversations
	Answer posts	All replies to posts
	Reactions	All reactions to posts and answers
	Notifications	All course notifications
	Notification settings	User notification preferences for the course
AI Features	Iris chat sessions	All AI tutor conversation history
	LLM token usage	Records of AI model usage and costs
Tutorial Groups	Registrations	All student registrations to tutorial groups
Enrollment	Students	Removed from student group
	Tutors	Removed from tutor group
	Editors	Removed from editor group

Course Archive

The Course Archive operation creates a ZIP file containing course data for long-term storage. The archive is useful for:

• Record keeping - Maintaining evidence of student work and assessments
• Compliance - Meeting data retention requirements
• Backup - Preserving course data before deletion or reset

Archive Contents

The course archive is structured as follows:

course-archive.zip
├── course-exercises/
│   └── [exercise exports with submissions...]
├── exams/
│   └── [exam exports with student exams...]
├── student-data/
│   ├── course-scores.csv
│   ├── course-grade-distribution.csv
│   ├── exam-scores-{examId}-{examTitle}.csv
│   ├── exam-{examId}-{examTitle}-grade-distribution.csv
│   ├── participation-results.csv
│   ├── posts.csv
│   ├── competency-progress.csv
│   ├── learner-profiles.csv
│   ├── tutorial-group-registrations.csv
│   ├── iris-sessions.json
│   └── llm-token-usage.csv
├── report.csv
└── exportErrors.txt

Every repository of a programming exercise is stored as its own ZIP inside the exercise export. The template, solution, test and auxiliary repositories keep their full Git history, including every branch and tag, so extracting one of them yields a usable repository. Student repositories are archived as a snapshot of the submitted working tree without a .git directory, matching what students and tutors get when they download a single repository from Artemis.

What is Included vs Not Included

Data that is INCLUDED in the archive

Category	File/Folder	Contents
Exercises	course-exercises/	All course exercises with student submissions
	Programming exercises	One ZIP per repository (template, solution, test, auxiliary and student repos)
	Text exercises	Submissions with assessments and feedback
	Modeling exercises	Model submissions with assessments
	File upload exercises	Uploaded files with assessments
	Quiz exercises	Quiz submissions and answers
Exams	exams/	All exams with student exam data
	Student exams	Individual student exam instances
	Exam exercises	All exam exercise submissions
Scores	student-data/course-scores.csv	Aggregated student scores for all course exercises
	student-data/exam-scores-*.csv	Aggregated student scores per exam (one file per exam)
	student-data/course-grade-distribution.csv, student-data/exam-*-grade-distribution.csv	Grade and score interval distribution of the course and of each exam (only if a grading scale exists)
Student Data	student-data/participation-results.csv	Latest submission and result per participation with feedback
	student-data/posts.csv	All posts and answer posts from conversations
	student-data/competency-progress.csv	Student competency progress records
	student-data/learner-profiles.csv	Course learner profile data
	student-data/tutorial-group-registrations.csv	Student registrations to tutorial groups
	student-data/iris-sessions.json	Iris AI tutor chat sessions (if Iris enabled)
	student-data/llm-token-usage.csv	LLM token usage traces (if Iris enabled)
Reports	report.csv	Export statistics per exercise
	exportErrors.txt	Any errors encountered during export

Data that is NOT INCLUDED in the archive

Category	Data Type	Reason
Course Structure	Course settings	Can be recreated; not student data
	Exercise definitions	Embedded in exercise exports
	Lecture content	Not part of archival scope
	Competency definitions	Can be recreated; only progress is archived
	Tutorial group definitions	Can be recreated; only registrations are archived
Communication	Reactions	Derived from posts; not separately archived
	Private messages	Privacy considerations
System Data	Notifications	Ephemeral; not needed for records
	Notification settings	User preferences; not student work
	Audit logs	Managed separately by system
User Data	User accounts	Managed at system level
	Group memberships	Can be derived from participation data

Student Data Export Files

course-scores.csv

Contains aggregated course scores with one row per student, followed by summary rows (maximum, average, median, standard deviation and the number of participants). Uses the same calculation as the course statistics UI. The columns are:

Column	Description
Name, Username, Email, RegistrationNumber	The student
<exercise title> Points, <exercise title> Score	Two columns for every exercise that counts towards the overall score
Presentation Score	Only if presentation points are configured for the course
Overall Points, Overall Score, Max Points	Total points, percentage score and maximum achievable points
Grade, Passed	Only if the course has a grading scale

exam-scores-{examId}-{examTitle}.csv

Contains aggregated exam scores for each exam (one file per exam) with one row per student, followed by summary rows. Uses the same calculation as the exam statistics UI. The columns are:

Column	Description
Name, Username, Email, RegistrationNumber, Submitted	The student and whether they submitted
<exercise group title> Exercise, ... Points, ... Score	Three columns for every exercise group
Overall Points, Overall Score, Max Points	Total points, percentage score and maximum achievable points
Grade, Passed	Only if grades are available
First Correction Points, First Correction Grade	Only if a second correction has started
Bonus Source Points, Bonus Grade, Final Grade	Only if a bonus is configured
Plagiarism Verdict	The plagiarism verdict of the student, if any

participation-results.csv

Contains the latest submission and result for each student participation:

Column	Description
ExerciseId	Unique identifier of the exercise
ExerciseTitle	Name of the exercise
ParticipantLogin	Student's login username
ParticipantName	Student's display name
ParticipationType	RATED (before due date) or PRACTICE (after due date)
SubmissionDate	When the submission was made
Score	Achieved score (percentage)
Rated	Whether the result counts for grading
Successful	Whether the submission passed (for programming exercises)
FeedbackCount	Number of feedback items
FeedbackDetails	Concatenated feedback text with points

posts.csv

Contains all posts and answer posts from course conversations:

Column	Description
Type	POST or ANSWER
Id	Unique post identifier
AuthorLogin	Username of the post author
CreationDate	When the post was created
Content	Text content of the post
ConversationId	ID of the containing conversation (for posts)
ParentPostId	ID of the parent post (for answers)

competency-progress.csv

Contains student progress on course competencies:

Column	Description
CompetencyId	Unique identifier of the competency
CompetencyTitle	Name of the competency
UserLogin	Student's login username
Progress	Progress value (0.0 to 1.0)
Confidence	Confidence value (0.0 to 1.0)
LastModified	When the progress was last updated

learner-profiles.csv

Contains course-specific learner profile data:

Column	Description
UserLogin	Student's login username
AimForGradeOrBonus	Student's grade/bonus goal setting
TimeInvestment	Planned time investment level
RepetitionIntensity	Preferred repetition intensity

tutorial-group-registrations.csv

Contains student registrations to tutorial groups:

Column	Description
TutorialGroupId	Unique identifier of the tutorial group
TutorialGroupTitle	Name of the tutorial group
StudentLogin	Student's login username
StudentName	Student's display name
RegistrationType	Type of registration (e.g., STUDENT)

iris-sessions.json

Contains Iris AI tutor chat sessions (JSON format):

[
  {
    "id": 123,
    "userId": 456,
    "creationDate": "2024-01-15T10:30:00Z",
    "messages": [
      {
        "id": 789,
        "sentAt": "2024-01-15T10:30:05Z",
        "sender": "USER",
        "content": "How do I implement a binary search?",
        "helpful": true
      }
    ]
  }
]

llm-token-usage.csv

Contains LLM token usage records for AI features:

Column	Description
TraceId	Unique trace identifier
ServiceType	Type of AI service (e.g., IRIS)
UserId	User who triggered the request
ExerciseId	Associated exercise (if applicable)
Time	When the request was made
Model	AI model used
Pipeline	Service pipeline identifier
NumInputTokens	Number of input tokens
NumOutputTokens	Number of output tokens
CostPerMillionInputTokens	Cost rate for input tokens
CostPerMillionOutputTokens	Cost rate for output tokens
NumCachedInputTokens	Number of cached input tokens
CostPerMillionCachedInputTokens	Cost rate for cached input tokens
NumCacheWriteInputTokens	Number of input tokens written to the cache
CostPerMillionCacheWriteInputTokens	Cost rate for cache write tokens

Best Practices

Before Resetting a Course

1. Create an archive - Always archive the course before resetting to preserve student data
2. Notify stakeholders - Inform instructors about the reset
3. Verify the course - Double-check you are resetting the correct course
4. Check data retention policies - Ensure you comply with institutional requirements

After Archiving a Course

1. Verify the archive - Check the ZIP file can be extracted and contains expected data
2. Store securely - Move the archive to secure, backed-up storage
3. Document location - Record where the archive is stored for future reference
4. Set retention period - Note when the archive can be deleted per policy