Script for Creating Multiple Choice Exams

examBulder.R

# Workflow for Creating Multiple Choice Exams

# This process creates a pseudo-random sample of correct answers, and then generates
# an exam based on a specified number of questions assigned to different sections of
# the course.

# Install Dependencies
# install.packages(c("dplyr", "purrr", "readr", "rlang"))

# Create 
questions <- cp_create_questions(n = 45)

# Check to make sure distribution of answers is relatively proportional
table(questions$correct)

# Randomly assign questions to different sections
exam <- cp_create_exam(questions, 
                      c("lecture1", "5"), 
                      c("lecture2", "5"),
                      c("lecture3", "5"),
                      c("week3", "10"),
                      c("methods", "10"),
                      c("week4", "10"))

# check exam
exam

# save
readr::write_csv(exam, "exam.csv")

# primary function one - create table of randomly assigned answers a through d
cp_create_questions <- function(n){
  
  correct = NULL
  
  # create data frame
  key <- data.frame(
    question = c(1:n),
    correct = sample.int(4, n, replace = TRUE)
  )
  
  # convert values to letters
  key %>%
    dplyr::mutate(correct = as.character(correct)) %>%
    dplyr::mutate(correct = dplyr::case_when(
      correct == "1" ~ "a",
      correct == "2" ~ "b",
      correct == "3" ~ "c",
      correct == "4" ~ "d"
    )) %>%
    dplyr::as_tibble() -> out
  
  # return output
  return(out)
  
}

# primary function two - assign sections to answers
cp_create_exam <- function(.data, ...){
  
  output <- NULL
  
  # convert questions to test bank
  bank <- .data
  
  # store dots as list
  list <- rlang::list2(...)
  
  # iterate over test sections
  for (i in seq_along(list)){
    
    # store section input
    item <- list[i][[1]]
    
    # draw questions from test bank
    sample <- exam_section(bank, n = as.numeric(item[2]))
    
    # add section name to each question
    sample <- dplyr::mutate(sample, section = as.character(item[1]))
    
    # update test bank to remove drawn questions
    bank <- exam_update(bank, sample)
    
    # store section tibble in list
    output[[i]] <- dplyr::as_tibble(sample)
    
  }
  
  # reduce section list to single table, arrange
  purrr::reduce(output, dplyr::bind_rows) %>%
    dplyr::arrange(question) -> out
  
  # return output
  return(out)
  
}

# sub-function for cp_create_exam - draw from test bank to create section
exam_section <- function(.data, n){
  
  # randomly sample from test bank
  out <- dplyr::sample_n(.data, size = n)
  
  # return output
  return(out)
  
}

# sub-function for cp_create_exam - update test bank to remove section questions
exam_update <- function(.data, section){
  
  # store question numbers
  x <- section$question
  
  # remove questions in new test section
  out <- dplyr::filter(.data, (question %in% x) == FALSE)
  
  # return output
  return(out)
  
}