I have been using the R exams package to create exams for my introductory statistics course this semester. It is really a great tool! I've been able to create several questions from scratch & import them to canvas without issue. However, there are some questions that give me problems when I try to import them (e.g., the anova and boxplot examples that are included in the package). I can successfully import if I use:
R> library("exams")
R> set.seed(1)
R> exams2canvas("anova.Rmd")
However, I sometimes run into problems when trying to create many versions of the same question:
R> library("exams")
R> exams2canvas("anova.Rmd", n=50)
The source of the problems are multiple-choice exercises with no correct alternative. These are not supported by learning management systems like Canvas or Moodle and hence exercises for these systems must assure at least one correct alternative and one wrong alternative.
Some of the demo exercises in R/exams did not restrict the number of correct/wrong alternatives to a minimum of one. So from time to time it could happen that no alternative is correct. Up to version 2.3-6 of R/exams this affects the following exercises: anova, automaton, boxplots, cholesky, relfreq, scatterplot. All of these have been adapted in version 2.4-0 (which was the development version of the package at the time of writing this answer).
Multiple-choice exercises without correct alternatives are straightforward to handle without partial credits when the entire answer pattern must be fully correct. However, when using partial credits, no positive points can be obtained when there are no correct alternatives.
When we created the demo exercises in R/exams we adapted exercises from an environment where we did not use partial credits. But learning management systems like Moodle or Canvas expect at least one correct (and typically also one wrong) alternative for scoring it correctly with partial credits.