Evaluation and maintenance of online courses on artificial intelligence

The content and instructional design of online courses have to be revised, renewed and expanded continuously to keep up with current developments in content and didactics. Such quality maintenance is particularly challenging in the field of artificial intelligence due to rapid developments and new findings. This paper presents an iterative maintenance criteria grid, which has been piloted for online courses on the AI Campus digital learning platform. One important criterion is evaluation by the learners. Analysis of course surveys conducted at the beginning (N = 2,259) and the end (N = 455) of courses provides initial insight into the characteristics of learners and their evaluations of the courses.