tutorizeR

tutorizeR is an R package for converting existing R Markdown (.Rmd) or Quarto (.qmd) teaching material into interactive tutorials for learnr or quarto-live. It lets instructors keep one primary lesson source while generating exercises, solutions, multiple-choice questions, and conversion reports.

CRAN version: 0.4.5, published on June 11, 2026.

CRAN GitHub Getting started CRAN vignettes

Visual preview

These illustrations summarize the package workflow: one teaching source is converted into interactive tutorials and accompanied by an auditable conversion report.

Usage example

The code below follows the package quick start. It copies the installed example module, loads a question bank, and converts a Quarto lesson into a learnr tutorial.

# Load library
library(tutorizeR)

# Locate the installed example module
example_dir <- system.file(
  "examples",
  "example_course_module",
  package = "tutorizeR"
)

# Copy the lesson and data to a temporary working directory
work_dir <- file.path(tempdir(), "tutorizeR-example")
dir.create(work_dir, recursive = TRUE, showWarnings = FALSE)

file.copy(
  from = file.path(example_dir, "lesson-source.qmd"),
  to = work_dir,
  overwrite = TRUE
)

file.copy(
  from = file.path(example_dir, "student_activity.csv"),
  to = work_dir,
  overwrite = TRUE
)

# Load the reusable question bank
question_bank <- load_question_bank(
  file.path(example_dir, "question-bank")
)

# Convert the lesson to an interactive tutorial
report <- tutorize(
  input = file.path(work_dir, "lesson-source.qmd"),
  output_dir = work_dir,
  format = "learnr",
  assessment = "both",
  question_bank = question_bank,
  mcq_source = "mixed",
  overwrite = TRUE,
  verbose = FALSE
)

# Inspect the conversion report
print(report)

What is tutorizeR for?

• converting .Rmd or .qmd lessons into interactive tutorials;
• turning existing code chunks into exercises, solutions, and feedback;
• integrating inline multiple-choice questions or YAML/JSON question banks;
• writing JSON or YAML conversion reports for review and reproducibility;
• processing a folder of lessons with a consistent conversion policy.