I am in the middle of my 2nd version of an Open Data Science MOOC and I just told the students about the grading system of this course.
There are ca. 100, mainly doctoral students from all campuses and Faculties of University of Helsinki, though mostly focusing on (computational) Social Sciences and (digital) Humanities. Also some Master's, some Bachelor's and Exchange students are present, some from other Unis like Aalto, UEF, and St. Petersburg, which is awesome and shows that the course is quickly expanding. Perhaps in the future we will have thousands of students, who knows? We are ready, and the course is ready to be scaled, no worries.
In addition, there are Post Doc researchers and staff, including Professors, which is very nice. The course got positive attention for example in the recent Summit of HELDIG and elsewhere.
I am working with my super team of 5 excellent students from Data Science/Digital Humanities/Statistics/Computer Science/etc. The course was built last winter as a project by our Master's students Tuomo Nieminen and Emma Kämäräinen, with whom we did the "legendary" presentation video found on the course page above. :)
I thought that you (friends of Survo) might be interested in seeing my ideas and working with the grading system (based on the 1st run of the course), as it is full of Survo usage and useful (common) Survo tricks.
So here it is, attached to this msg as a PDF file (see below). Have fun! :)
(Some issues have already been simplified as we run this 2nd version, and will be further simplified, as soon as I get the final analytics data after the course. Anyway, you will get the overall idea from this.)
Of couse, I am happy to answer any questions that may arise - both substantial and technical. You are also welcome to participate in the course on the MOOC platform.