Type: Package
Title: Defining 'Moodle' Elements from R
Version: 1.2.0
Description: The main objective of this package is to support the definition of 'Moodle' elements taking advantage of the power that R offers. In this first version, it allows the definition of quizzes to be included in the question bank.
License: MIT + file LICENSE
URL: https://josesamos.github.io/moodef/, https://github.com/josesamos/moodef
BugReports: https://github.com/josesamos/moodef/issues
Imports: blastula, dplyr, glue, magick, readr, readxl, snakecase, tibble, tidyr, tools, xlsx, xml2
Suggests: knitr, pander, rmarkdown, testthat (≥ 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.3.2
Depends: R (≥ 3.5)
NeedsCompilation: no
Packaged: 2025-01-26 12:48:14 UTC; jsamos
Author: Jose Samos ORCID iD [aut, cre], Universidad de Granada [cph]
Maintainer: Jose Samos <jsamos@ugr.es>
Repository: CRAN
Date/Publication: 2025-01-26 13:10:02 UTC

Resize and Center an Image

Description

Resizes an image to fit within the specified dimensions, centering it on a blank canvas.

Usage

adapt_image(image_file, width = 800, height = 600)

Arguments

image_file

character Path to the image file to be resized.

width

integer, default 800 Desired width of the output image.

height

integer, default 600 Desired height of the output image.

Value

A string representing the path to the new resized image file.

Allowed Question Types

Description

A vector of allowed question types for validation in the package.

Usage

allowed_types

Format

A character vector with 12 elements, including:

"numerical"

Numerical questions

"multichoice"

Multiple-choice questions

"ordering"

Ordering questions

"ordering<|>h"

Horizontal ordering questions

"ordering<|>v"

Vertical ordering questions

"ddwtos"

Drag-and-drop words into sentences

"gapselect"

Gap select questions

"matching"

Matching questions

"essay"

Essay questions

"truefalse"

True/False questions

"shortanswer"

Short-answer questions

"ddmarker"

Drag-and-drop markers

Define the category of questions

Description

Define the category of questions

Usage

category_question(category, questions)

Arguments

category

A string, category name.

questions

A string, formatted questions.

Value

A string.

Create a question data frame common to normal and extended questions.

Description

Create a question data frame common to normal and extended questions.

Usage

create_common_question_df()

Create a question data frame common to normal and extended questions with default values.

Description

Create a question data frame common to normal and extended questions with default values.

Usage

create_default_value_question_df()

Create a question csv file

Description

Creates an empty question csv file.

Usage

create_question_csv(file, sep = ",", extended = FALSE)

Arguments

file

A string, name of a text file.

sep

Column separator character.

extended

A Boolean, use extended question definition.

Value

A string.

See Also

Other support functions: create_question_data_frame(), create_question_excel(), read_question_csv(), read_question_excel(), vector_to_string()

Examples


file <- create_question_csv(file = tempfile(fileext = '.csv'))

Create a question data frame

Description

Creates an empty question data frame.

Usage

create_question_data_frame(extended = FALSE)

Arguments

extended

A Boolean, use extended question definition.

Value

A data frame.

See Also

Other support functions: create_question_csv(), create_question_excel(), read_question_csv(), read_question_excel(), vector_to_string()

Examples


df <- create_question_data_frame()

Create a question Excel file

Description

Creates an empty question Excel file.

Usage

create_question_excel(file, extended = FALSE)

Arguments

file

A string, name of a text file.

extended

A Boolean, use extended question definition.

Value

A string.

See Also

Other support functions: create_question_csv(), create_question_data_frame(), read_question_csv(), read_question_excel(), vector_to_string()

Examples



file <- create_question_excel(file = tempfile(fileext = '.xlsx'))

Define an extended question

Description

This function allows users to define an extended question, including metadata, feedback and optional image data.

Usage

define_extended_question(
  qc,
  category,
  type,
  fraction,
  id,
  name,
  author,
  fb_general,
  fb_correct,
  fb_partially,
  fb_incorrect,
  question,
  image,
  image_alt,
  answer,
  a_1,
  a_2,
  a_3,
  a_4,
  a_5,
  a_6,
  a_7,
  fb_answer,
  fb_a_1,
  fb_a_2,
  fb_a_3,
  fb_a_4,
  fb_a_5,
  fb_a_6,
  fb_a_7,
  tag_1,
  tag_2,
  tag_3,
  tag_4,
  tag_5,
  tag_6,
  tag_7,
  tag_8,
  tag_9
)

## S3 method for class 'question_category'
define_extended_question(
  qc,
  category = "",
  type = "",
  fraction = 0,
  id = "",
  name = "",
  author = "",
  fb_general = "",
  fb_correct = "",
  fb_partially = "",
  fb_incorrect = "",
  question = "",
  image = "",
  image_alt = "",
  answer = "",
  a_1 = "",
  a_2 = "",
  a_3 = "",
  a_4 = "",
  a_5 = "",
  a_6 = "",
  a_7 = "",
  fb_answer = "",
  fb_a_1 = "",
  fb_a_2 = "",
  fb_a_3 = "",
  fb_a_4 = "",
  fb_a_5 = "",
  fb_a_6 = "",
  fb_a_7 = "",
  tag_1 = "",
  tag_2 = "",
  tag_3 = "",
  tag_4 = "",
  tag_5 = "",
  tag_6 = "",
  tag_7 = "",
  tag_8 = "",
  tag_9 = ""
)

Arguments

qc

A question category object. It should have a questions data frame where new questions will be added.

category

A character string specifying the category of the question.

type

A character string indicating the type of the question.

fraction

A number between 0 and 1.

id

A unique identifier for the question.

name

A character string representing the name of the question.

author

The name of the author of the question.

fb_general

General feedback for the question.

fb_correct

Feedback displayed when the correct answer is selected.

fb_partially

Feedback displayed for partially correct answers.

fb_incorrect

Feedback displayed for incorrect answers.

question

The text of the question.

image

Path to an image file associated with the question.

image_alt

Alternative text describing the image for accessibility. Required if an image is provided.

answer

The correct answer to the question.

a_1

Additional possible answer.

a_2

Additional possible answer.

a_3

Additional possible answer.

a_4

Additional possible answer.

a_5

Additional possible answer.

a_6

Additional possible answer.

a_7

Additional possible answer.

fb_answer

Feedback for the correct answer.

fb_a_1

Feedback for additional answer.

fb_a_2

Feedback for additional answer.

fb_a_3

Feedback for additional answer.

fb_a_4

Feedback for additional answer.

fb_a_5

Feedback for additional answer.

fb_a_6

Feedback for additional answer.

fb_a_7

Feedback for additional answer.

tag_1

Tag to categorize the question.

tag_2

Tag to categorize the question.

tag_3

Tag to categorize the question.

tag_4

Tag to categorize the question.

tag_5

Tag to categorize the question.

tag_6

Tag to categorize the question.

tag_7

Tag to categorize the question.

tag_8

Tag to categorize the question.

tag_9

Tag to categorize the question.

Details

Parameter values that are not defined are taken from the category definition, if they are defined there.

The fraction attribute is used in various question types to determine how a specific answer impacts the question's score. Specifically, for incorrect answers in the multichoice and truefalse types, the value calculated by dividing fraction by the number of incorrect answers available is considered as the amount deducted in case of an incorrect response.

In the example provided, we have intentionally used the same structure as in the define_question() function to demonstrate that any parameters not needed do not need to be explicitly defined.

Value

Returns the updated question category object.

See Also

Other question definition functions: define_question(), define_questions_from_csv(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml(), generate_xml_file(), question_category()

Examples


qc <- question_category(category = 'Initial test') |>
  define_extended_question(
    question = 'What are the basic arithmetic operations?',
    answer = 'Addition, subtraction, multiplication and division.',
    a_1 = 'Addition and subtraction.',
    a_2 = 'Addition, subtraction, multiplication, division and square root.'
  )

Define a question

Description

Define a question and the possible answers. The type of question is deduced.

Usage

define_question(qc, type, question, image, image_alt, answer, ...)

## S3 method for class 'question_category'
define_question(
  qc,
  type = "",
  question = "",
  image = "",
  image_alt = "",
  answer = "",
  ...
)

Arguments

qc

A question_category object.

type

A string, question type (if needed).

question

A string, statement of the question.

image

A string, optional, image file to include in the question.

image_alt

A string, description of the image to include in the question.

answer

A string, correct answer to the question.

...

A string, rest of the answers to the question.

Details

If we include an image in the question, we must also include text in the alt field associated with it.

After the correct answer, we can indicate as many answers as we want, if we do not indicate all the parameters, we have to give each answer a parameter name different from the rest of the parameter names.

Value

A question_category.

See Also

Other question definition functions: define_extended_question(), define_questions_from_csv(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml(), generate_xml_file(), question_category()

Examples


qc <- question_category(category = 'Initial test') |>
  define_question(
    question = 'What are the basic arithmetic operations?',
    answer = 'Addition, subtraction, multiplication and division.',
    a_1 = 'Addition and subtraction.',
    a_2 = 'Addition, subtraction, multiplication, division and square root.'
  )

Define questions from a csv file

Description

Each row in the text file is interpreted as a question. We only have to define the columns that we are going to use, the rest of the columns are taken by default.

Usage

define_questions_from_csv(qc, file, sep)

## S3 method for class 'question_category'
define_questions_from_csv(qc, file, sep = ",")

Arguments

qc

A question_category object.

file

A string, name of a text file.

sep

Column separator character.

Details

For answers where a vector is required, "<|>" is used as a separator of the vector elements.

Value

A question_category.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml(), generate_xml_file(), question_category()

Examples


file <- system.file("extdata", "questions.csv", package = "moodef")
qc <-
  question_category(category = 'Initial test', adapt_images = TRUE) |>
  define_questions_from_csv(file = file)

Define questions from a data frame

Description

Each row in the text data frame is interpreted as a question. We only have to define the columns that we are going to use, the rest of the columns are taken by default.

Usage

define_questions_from_data_frame(qc, df)

## S3 method for class 'question_category'
define_questions_from_data_frame(qc, df)

Arguments

qc

A question_category object.

df

A data frame.

Details

For answers where a vector is required, "<|>" is used as a separator of the vector elements.

Value

A question_category.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_csv(), define_questions_from_excel(), generate_xml(), generate_xml_file(), question_category()

Examples


file <- system.file("extdata", "questions.csv", package = "moodef")
df <- read_question_csv(file = file)

qc <-
  question_category(category = 'Initial test', adapt_images = TRUE) |>
  define_questions_from_data_frame(df)

Define questions from a data frame

Description

Define questions from a data frame

Usage

define_questions_from_df(qc, df)

Define questions from a Excel file

Description

Each row in the Excel file is interpreted as a question. We only have to define the columns that we are going to use, the rest of the columns are taken by default.

Usage

define_questions_from_excel(qc, file, sheet_index, sheet_name)

## S3 method for class 'question_category'
define_questions_from_excel(qc, file, sheet_index = NULL, sheet_name = NULL)

Arguments

qc

A question_category object.

file

A string, name of an Excel file.

sheet_index

A number, sheet index in the workbook.

sheet_name

A string, sheet name.

Details

In addition to the file, we can indicate the sheet by its name or index. If we do not indicate anything, it considers the first sheet.

For answers where a vector is required, "<|>" is used as a separator of the vector elements.

Value

A question_category.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_csv(), define_questions_from_data_frame(), generate_xml(), generate_xml_file(), question_category()

Examples



file <- system.file("extdata", "questions.xlsx", package = "moodef")
qc <-
  question_category(category = 'Initial test', adapt_images = TRUE) |>
  define_questions_from_excel(file = file)

Determine question type

Description

Determines the type of the question based on its content, provided answers, and optional type parameter.

Usage

determine_question_type(type, question, answer, a_values)

Arguments

type

A string, suggested type for the question.

question

A string, the main question text.

answer

A string or vector, the correct answer(s) for the question.

a_values

A vector, additional answers for the question.

Value

A string indicating the question type.

Extract Type and Orientation

Description

This function takes a string representing a question type and its optional orientation (e.g., "ordering<|>h") and splits it into two separate components: the type and the orientation. If the orientation is not provided, it defaults to "v".

Usage

extract_type_orientation(type)

Arguments

type

A character string indicating the type of a question, which may optionally include an orientation separated by "<|>". For example: "ordering<|>h", "ordering<|>v", or just "ordering".

Value

A list with two elements:

type

The main question type as a character string.

orientation

The orientation of the type as a character string. Defaults to "v".

Filter non-empty answers

Description

Filters additional answers provided in ... to ensure only non-empty answers are included in the final output.

Usage

filter_non_empty_answers(...)

Arguments

...

Strings, additional answers.

Value

A vector of non-empty answers.

Generate ddmarker question

Description

Generate ddmarker question

Usage

generate_ddmarker(image, image_alt, answer, fb_answer)

Arguments

image

A string, optional, image file to include in the question.

image_alt

A string, description of the image to include in the question.

answer

A string vector.

fb_answer

A string, answer feedback.

Value

A string.

Generate ddwtos question

Description

Generate ddwtos question

Usage

generate_ddwtos(
  answer,
  a_values,
  correct_feedback,
  incorrect_feedback,
  partially_correct_feedback
)

Arguments

answer

A vector of strings.

a_values

A vector, rest of answers.

correct_feedback

A string.

incorrect_feedback

A string.

partially_correct_feedback

A string.

Value

A string.

Generate essay question

Description

Generate essay question

Usage

generate_essay()

Value

A string.

Generate gapselect question

Description

Generate gapselect question

Usage

generate_gapselect(
  answer,
  a_values,
  correct_feedback,
  incorrect_feedback,
  partially_correct_feedback
)

Arguments

answer

A vector of strings.

a_values

A vector, rest of answers.

correct_feedback

A string.

incorrect_feedback

A string.

partially_correct_feedback

A string.

Value

A string.

Generate matching question

Description

Generate matching question

Usage

generate_matching(
  answer,
  a_values,
  correct_feedback,
  incorrect_feedback,
  partially_correct_feedback
)

Arguments

answer

A vector of strings.

a_values

A vector, rest of answers.

correct_feedback

A string.

incorrect_feedback

A string.

partially_correct_feedback

A string.

Value

A string.

Generate multichoice question

Description

Generate multichoice question

Usage

generate_multichoice(
  answer,
  a_values,
  correct_feedback,
  incorrect_feedback,
  fb_partially,
  fb_answer,
  fb_a_values,
  fraction
)

Arguments

answer

A string.

a_values

A vector, rest of answers.

correct_feedback

A string.

incorrect_feedback

A string.

fb_partially

A string.

fb_answer

A string, answer feedback.

fb_a_values

A vector, rest of answer feedback.

fraction

A number between 0 and 1.

Value

A string.

Generate numerical question

Description

Generate numerical question

Usage

generate_numerical(answer, a_values, fb_answer, fb_a_values)

Arguments

answer

A vector of strings.

a_values

A vector, rest of answers.

fb_answer

A string, answer feedback.

fb_a_values

A vector, rest of answer feedback.

Value

A string.

Generate ordering question

Description

Generate ordering question

Usage

generate_ordering(
  answer,
  a_values,
  correct_feedback,
  incorrect_feedback,
  partially_correct_feedback,
  orientation
)

Arguments

answer

A vector of strings.

a_values

A vector, rest of answers.

correct_feedback

A string.

incorrect_feedback

A string.

partially_correct_feedback

A string.

orientation

A string, 'h' or 'v'.

Value

A string.

Generate the question body

Description

Creates the body of the question based on its type and additional parameters such as feedback and orientation.

Usage

generate_question_body(
  type,
  answer,
  a_values,
  fb_correct,
  fb_incorrect,
  fb_partially,
  orientation,
  fb_answer,
  fb_a_values,
  image,
  image_alt,
  fraction
)

Arguments

type

A string, the question type.

answer

A string or vector, the correct answer(s) for the question.

a_values

A vector, additional answers for the question.

fb_correct

A string, feedback for correct answers.

fb_incorrect

A string, feedback for incorrect answers.

fb_partially

A string, feedback for partially correct answers.

orientation

A string, 'v' or 'h'.

fb_answer

A string, answer feedback.

fb_a_values

A vector, rest of answer feedback.

image

Path to an image file associated with the question.

image_alt

Alternative text describing the image for accessibility.

fraction

A number between 0 and 1.

Value

A string containing the question body in XML format.

generate question name node

Description

generate question name node

Usage

generate_question_name(first_question_number, type, question)

Arguments

first_question_number

An integer, first number to compose the question names.

type

A string, question type (if needed).

question

A string, statement of the question.

Value

A string.

Generate shortanswer question

Description

Generate shortanswer question

Usage

generate_shortanswer(answer, fb_answer)

Arguments

answer

A string.

fb_answer

A string, answer feedback.

Value

A string.

Generate truefalse question

Description

Generate truefalse question

Usage

generate_truefalse(answer, fb_answer, fb_a_values, fraction)

Arguments

answer

A string.

fb_answer

A string, answer feedback.

fb_a_values

A vector, rest of answer feedback.

fraction

A number between 0 and 1.

Value

A string.

Generate questions xml string

Description

Generate questions xml string

Usage

generate_xml(qc)

## S3 method for class 'question_category'
generate_xml(qc)

Arguments

qc

A question_category object.

Value

A string.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_csv(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml_file(), question_category()

Examples


qc <- question_category(category = 'Initial test') |>
  define_question(
    question = 'What are the basic arithmetic operations?',
    answer = 'Addition, subtraction, multiplication and division.',
    a_1 = 'Addition and subtraction.',
    a_2 = 'Addition, subtraction, multiplication, division and square root.'
  )

xml <- qc |>
  generate_xml()

Generate questions xml file

Description

Generate questions xml file

Usage

generate_xml_file(qc, file)

## S3 method for class 'question_category'
generate_xml_file(qc, file = NULL)

Arguments

qc

A question_category object.

file

A string, file name.

Value

A question_category.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_csv(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml(), question_category()

Examples


qc <- question_category(category = 'Initial test') |>
  define_question(
    question = 'What are the basic arithmetic operations?',
    answer = 'Addition, subtraction, multiplication and division.',
    a_1 = 'Addition and subtraction.',
    a_2 = 'Addition, subtraction, multiplication, division and square root.'
  ) |>
  generate_xml_file(file = tempfile(fileext = '.xml'))

Get Detailed Type Names

Description

Determines the type column of a data frame based on specific conditions and the content of other columns in the data frame.

Usage

get_detailed_type_names(df)

Arguments

df

A data frame containing at least the following columns:

  • type: A character column representing the type of each question.

  • answer: A character column containing answers for each question.

  • Additional columns with a prefix "a_" representing associated answer fields.

Details

It checks if some value in the type column are within the allowed set (⁠'', 'h', 'v', 'x'⁠) and updates each row based on the associated answers and other fields.

Value

A character vector containing the updated type values.

Get non-empty values from fields with a specific prefix

Description

This function takes a dataframe, a row index, and a prefix, returning a vector with the content of columns that start with the given prefix and are not empty.

Usage

get_non_empty_fields_by_prefix(df, i, prefix)

Arguments

df

A dataframe containing the relevant columns.

i

An integer representing the row index.

prefix

A string representing the prefix of the column names (e.g., "a_", "fb_a_", "tag_").

Value

A vector with non-empty values from the fields with the given prefix in the specified row.

Convert Answer String to Vector

Description

Converts an answer string into a vector using string_to_vector. If the input is NULL, it returns an empty string.

Usage

get_vector_answer(answer)

Arguments

answer

A character string representing the answer.

Value

A vector if the answer is successfully converted, or an empty string if the answer is NULL.

Check if a String Contains Gaps

Description

Checks if a string contains the specific substrings "[[1]]" and "[[2]]".

Usage

has_gaps(str)

Arguments

str

character A string to check.

Value

logical TRUE if the string contains gaps, FALSE otherwise.

Check if a String Represents a Numeric Value

Description

Verifies if a string can be converted to a numeric value.

Usage

is_numeric(str)

Arguments

str

character A string to check.

Value

logical TRUE if the string is numeric, FALSE otherwise.

Process Question DataFrame

Description

Processes a dataframe by converting columns to character type, handling NAs, and renaming attributes to snake_case.

Usage

process_question_dataframe(df)

Arguments

df

A dataframe to process.

Value

A processed dataframe.

question_category S3 class

Description

Creates a question_category object.

Usage

question_category(
  category = "Default category",
  first_question_number = 1,
  copyright = "",
  license = "",
  correct_feedback = "Correct.",
  partially_correct_feedback = "Partially correct.",
  incorrect_feedback = "Incorrect.",
  adapt_images = FALSE,
  width = 800,
  height = 600,
  author = "",
  fraction = 0
)

Arguments

category

A string, category name.

first_question_number

An integer, first number to compose the question names.

copyright

A string, copyright text to be included in each question that is defined.

license

A string, license text to be included in each question that is defined.

correct_feedback

A string, feedback on correct answers to each question.

partially_correct_feedback

A string, feedback on partially correct answers to each question.

incorrect_feedback

A string, feedback on incorrect answers to each question.

adapt_images

A boolean, adapt the images so that they are a similar size.

width

A integer, width of each image.

height

A integer, height of each image.

author

A string, author name to be included in each question that is defined.

fraction

A number between 0 and 1.

Details

Defines a category of questions to be included in the Moodle question bank.

It allows us to define the name of the category, the copyright and license literals that will be added to each question, and the feedback literals for correct, partially correct and incorrect questions.

Each question can include an image after the text. We can also configure if we want to automatically transform the images so that they have a standard size that we can also indicate.

The fraction attribute is used in various question types to determine how a specific answer impacts the question's score. Specifically, for incorrect answers in the multichoice and truefalse types, the value calculated by dividing fraction by the number of incorrect answers available is considered as the amount deducted in case of an incorrect response.

Value

A question_category object.

See Also

Other question definition functions: define_extended_question(), define_question(), define_questions_from_csv(), define_questions_from_data_frame(), define_questions_from_excel(), generate_xml(), generate_xml_file()

Examples


qc <- question_category(category = 'Initial test')

Read a question csv file

Description

Reads a csv file of questions and returns a data frame.

Usage

read_question_csv(file, sep = ",")

Arguments

file

A string, name of a text file.

sep

Column separator character.

Value

A data frame.

See Also

Other support functions: create_question_csv(), create_question_data_frame(), create_question_excel(), read_question_excel(), vector_to_string()

Examples


file <- system.file("extdata", "questions.csv", package = "moodef")
df <- read_question_csv(file = file)

Read a question Excel file

Description

Reads an Excel file of questions and returns a data frame.

Usage

read_question_excel(file, sheet_index = NULL, sheet_name = NULL)

Arguments

file

A string, name of a text file.

sheet_index

A number, sheet index in the workbook.

sheet_name

A string, sheet name.

Details

In addition to the file, we can indicate the sheet by its name or index. If we do not indicate anything, it considers the first sheet.

Value

A data frame.

See Also

Other support functions: create_question_csv(), create_question_data_frame(), create_question_excel(), read_question_csv(), vector_to_string()

Examples



file <- system.file("extdata", "questions.xlsx", package = "moodef")
df <- read_question_excel(file = file)

Simplified Question Types

Description

A vector of simplified question types used internally in the package.

Usage

simplified_types

Format

A character vector with 4 elements:

""

Empty type

"h"

Horizontal type

"v"

Vertical type

"x"

Other type

Transform a String into a String-Formatted Vector

Description

Converts a string into a string-formatted vector (e.g., "a<|>b<|>c" -> c("a", "b", "c")).

Usage

string_to_string_vector(str)

Arguments

str

character A string to transform.

Value

A string representing a vector in R syntax (e.g., c("a", "b", "c")), or ⁠"\"\""⁠ if the input string is empty.

Transform a String into a Vector of Strings

Description

Splits a string into a vector of strings using "<|>" as a delimiter.

Usage

string_to_vector(str)

Arguments

str

character A string to transform.

Value

A vector of strings (character), or NULL if the input string is empty.

Transforms a vector of strings into a string

Description

Insert the separator that we consider to later perform the reverse operation.

Usage

vector_to_string(vector)

Arguments

vector

A vector of strings.

Value

A string.

See Also

Other support functions: create_question_csv(), create_question_data_frame(), create_question_excel(), read_question_csv(), read_question_excel()

Examples


s <- vector_to_string(c('Addition', '+'))

Generate HTML and XML Representations for an Image

Description

This function generates an HTML ⁠<img>⁠ tag and an XML ⁠<file>⁠ tag for a given image. The image can be processed to adjust its dimensions and encoded in base64 for embedding.

Usage

xml_image(image, image_alt, adapt_images = FALSE, width = NULL, height = NULL)

Arguments

image

character Path to the image file. If the string is empty, the function returns empty values.

image_alt

character Alternative text for the image, used for accessibility purposes (e.g., screen readers).

adapt_images

logical, default FALSE If TRUE, the image dimensions are adjusted to the specified width and height. If FALSE, the original dimensions are used.

width

numeric or NULL, default NULL Desired width for the image. Only used when adapt_images = TRUE. If NULL, the width is derived from the image file.

height

numeric or NULL, default NULL Desired height for the image. Only used when adapt_images = TRUE. If NULL, the height is derived from the image file.

Details

Value

A list with two elements:

img

character: HTML string containing the ⁠<img>⁠ tag.

fimg

character: XML string containing the base64-encoded ⁠<file>⁠ tag.

Define the question in xml

Description

Define the question in xml

Usage

xml_question(type, name, questiontext, question_body, question_tags = "")

Arguments

type

A string, question type.

name

A string, question name.

questiontext

A string, question text.

question_body

A string, question tags.

Value

A string.

Define the question category in xml

Description

Define the question category in xml

Usage

xml_question_category(category)

Arguments

category

A string, category name.

Value

A string.

Define the question id number in xml

Description

Define the question id number in xml

Usage

xml_question_idnumber(idnumber)

Arguments

idnumber

A string, question id number.

Value

A string.

Define the question name in xml

Description

Define the question name in xml

Usage

xml_question_name(name)

Arguments

name

A string, question name.

Value

A string.

Define the question tags in xml

Description

Define the question tags in xml

Usage

xml_question_tags(tag_values)

Arguments

tag_values

A string, tag values.

Value

A string.

generate questiontext node

Description

generate questiontext node

Usage

xml_questiontext(
  copyright,
  license,
  adapt_images,
  width,
  height,
  question,
  image,
  image_alt,
  type,
  author,
  fb_general,
  idnumber
)

Arguments

copyright

A string, copyright text to be included in each question that is defined.

license

A string, license text to be included in each question that is defined.

adapt_images

A boolean, adapt the images so that they are a similar size.

width

A integer, width of each image.

height

A integer, height of each image.

question

A string, statement of the question.

image

A string, optional, image file to include in the question.

image_alt

A string, description of the image to include in the question.

type

A string, question type.

author

A string, author name to be included in each question that is defined.

fb_general

A string, general feedback to be included in each question that is defined.

idnumber

A string, idnumber to be included in each question that is defined.

Value

A string.