The main aim is to further facilitate the creation of exercises based on the package 'exams' 
    by Grün, B., and Zeileis, A. (2009) <doi:10.18637/jss.v029.i10>. Creating effective student exercises 
    involves challenges such as creating appropriate data sets and ensuring access to intermediate values 
    for accurate explanation of solutions. The functionality includes the generation of univariate and 
    bivariate data including simple time series, functions for theoretical distributions and their approximation, 
    statistical and mathematical calculations for tasks in basic statistics courses as well as general tasks 
    such as string manipulation, LaTeX/HTML formatting and the editing of XML task files for 'Moodle'.

Provides a small collection of datasets supporting Pearson correlation 
    and linear regression analysis. It includes the precomputed dataset 'sos100', 
    with integer values summing to zero and squared sum equal to 100. For other 
    values of 'n' and user-defined parameters, the 'sos()' function from the 
    'exams.forge' package can be used to generate datasets on the fly. In addition, 
    the package contains around 500 R Markdown exercises that illustrate the usage 
    of 'exams.forge' commands.

Randomized multiple-select and single-select
  question generation for the 'MyLearn' teaching and learning
  platform. Question templates
  in the form of the R/exams package (see <http://www.r-exams.org/>)
  are transformed into XML format required by 'MyLearn'.

Automatic generation of quizzes or individual questions as (interactive) forms within 'rmarkdown' or 'quarto' documents based on 'R/exams' exercises.

Automatic generation of quizzes or individual questions for 'learnr' tutorials based on 'R/exams' exercises.

Automatic Generation of Exams in R for 'Sakai'.
  Question templates in the form of the 'exams' package (see <https://www.r-exams.org/>)
  are transformed into XML format required by 'Sakai'.

Provides methods for constructing confidence or credible regions
    for exceedance sets and contour lines.