  Detailed feedback on courses and lecture content is essential for their
improvement and also serves as a tool for reflection. However, feedback methods
are often only used sporadically, especially in mass courses, because
collecting and analyzing feedback in a timely manner is often a challenge for
teachers. Moreover, the current situation of the students or the changing
workload during the semester are usually not taken into account either. For a
holistic investigation, the article used a digital survey format as formative
feedback which attempts to measure student stress in a quantitative part and to
address the participants' reflection in a qualitative part, as well as to
collect general suggestions for improvement (based on the so-called One-Minute
Paper) at two educational institutions. The feedback during the semester is
evaluated qualitatively and discussed on a meta-level and special features
(e.g. reflections on student work ethic or other courses) are addressed. The
results show a low, but constant rate of feedback. Responses mostly cover
topics of the lecture content or organizational aspects and were intensively
used to report issues within the lecture. In addition, artificial intelligence
(AI) support in the form of a large language model was tested and showed
promising results in summarizing the open-ended responses for the teacher.
Finally, the experiences from the lecturers are reflected upon and the results
as well as possibilities for improvement are discussed.
