Learning Analytics
Artemis measures how a course is going: how many students are active, how much they submit, and how they score against the average. Students see their own position in the cohort; instructors see the cohort.
Figures on the Course Page
The course page in the course management carries the headline figures, below the quick actions: Total Assessments as a fraction of the submissions waiting, Total Complaints and More Feedback Requests with how many have been answered, Average Student Score in both points and percent, and Total LLM Cost where AI features are in use. Beside them, Active students plots participation week by week over the last four weeks, the last eight, or the whole course.
Each of those figures is a link, so a number that looks wrong leads straight to the page that explains it.
Course Statistics
Statistics in the course management opens the full set: the average score of each exercise, submissions, active students, and more, one chart under another.
The Average Score chart ranks the exercises by their average and colors them in three groups: the lowest third of exercises red, the middle third grey, the best third green. It is a comparison between exercises, not a statement about how the students divide up, so an exercise that is out of line with the rest of the course is visible without reading the numbers. Filter limits the chart to particular exercise types.
Every other chart on the page is drawn over a period you choose with Day, Week, Month, Quarter and Year; Week is what the page opens on, and the arrows either side step through the periods. Active students counts the students who submitted at least once in the week concerned, so a fall in that line is a fall in participation rather than in marks.
Exercise Statistics
Each exercise has the same treatment on its own scale: Average Score, Participation Rate, Resolved Posts, and the distribution of scores across the cohort. Click one of the average-score bars on the course statistics, or Statistics on the exercise itself.
The score distribution is worth reading before you set the next exercise. It shows where the cohort clustered, how wide the spread is, and whether anyone is stranded at either end — but only that. What a cluster or a gap means is not in the chart: read some of the submissions behind it before concluding anything about what was understood.
Related
Competencies turn these measurements into something a student can act on. See Adaptive Learning for how competencies are defined and linked to material.