Using ‘GIFTr’ Package To Prepare ‘MOODLE’ Quiz from Spreadsheet

What is GIFTr?

GIFTr package in intended to help course creators to upload questions to MOODLE and other LMS for quizzes. GIFTr takes dataframe or tibble of questions of four types: mcq, numerical questions, true or false and short answer,and export it a text file formatted in MOODLE GIFT format. You can prepare a spreadsheet in any software and import it in R and generate any number of questions with HTML, markdown and LATEX support.

Aim of this document

The aim of vignette is to highlight the most useful features of GIFTr in preparing a flexible MOODLE quiz as quick as possible with the lowest possibility of errors.

Before you start.

Before going through this tutorial you should have: - R installed - spreadsheet application, like MS Excel, Google Sheets, Libre Calc …etc.

How to start your quiz spreadsheet?

The data passed would differ slightly according to question type, however generally you need to have:-

a column contains question. This cannot contain empty values
answer(s) column(s). This may be multiple columns if you have multiple answers. If you mix single and multiple answer it is better to write the single answer in the first column. If you have only single answer MCQ and NO multiple answer MCQ, you can set the answers without asterisk in the first column of the answers columns. More details in the vignette and below.
a column specifying the type of question. The current supported questions are MCQ, numerical entry, true or false and short answer questions. The should be named ‘mcq’ , ‘num_q’ , ‘tf_q’ and ‘short_ans’ respectively.
a column specifying categories and subcategories in the MOODLE categories are important when you are preparing a quiz as you may want to specify certain proportions of inclusions. Categories and subcategories are spaced by forward slash like Categ1/subcateg1/subsubcateg1 …etc.
a column specifying question names. So you can easily enter a certain question names by like certain ID or keyword to make the questions easily on the system. however you don’t need to worry about that as automatically if not set, the first 40 letter are set a question name.

Here is what your spreadsheet heading should look like.

categories	names	question	A	B	C	D	E	question_type

categories column

If you want to add high control for your quiz, you can specify categories in hierarchical order. For example if you want to create this quiz under category Questions and subcategory to be history and under that chapter2 , you can write it as Ques/hist/chap2

Questions column

This is where you specify the question text. This can’t be empty at any question row.

Markdown and HTML Support

You can use markdown formatting like **bold** and italic and the more advance formatting like tables. You also can use HTML tags in this question like <sub> and <sup>

LATEX Support

You can use latex as inline or block code, between single $ or double $$ dollar sign. However you have to be careful if you have equal sign or curly brackets to use to escape it. For more about escaping characters in GIFT check MOODLE docs

Answers column

You can have one or more answer columns. The formatting can differ slightly from question to another. Below I will highlight the most important tips. #### HTML, markdown and LATEX Like question text, answers can be formatted with HTML, markdown or LATEX.

MCQ

When you write MCQs answers you have the flexibility of marking more than one correct answer to be preceded by asterisk *. If you mark only one answer by asterisk, you will get an MCQ question of single answer type and this answer will hold 100% of credit. If you mark many answers, answer will take partial equally divided positive credit and the wrong answers will take equally divided negative credit. This is to prevent selecting all the answers to get 100% credit as MOODLE don’t allow it automatically.
Below is a whole example of a single and a multiple answer MCQ respectively.

categories	names	question	A	B	C	D	E	question_type
Ques/hist	Q1	Who’s buried in Grant’s tomb?	*Grant	no one#Was true for 12 years, but Grant’s remains were buried in the tomb in 1897	Napoleon#He was buried in France	Churchill#He was buried in England	Mother Teresa#She was buried in India	mcq
Ques/hist	Q2	What two people are entombed in Grant’s tomb?	No one	*Grant	*Grant’s wife	Grant’s father		mcq

If you don’t want to have a multiple answers MCQ and want to write ONLY single answer MCQ and want a quicker approach than asterisk, you can neglect asterisk and position the all right answers to be in the first column answer. Below is an example of single answer MCQ with the correct answer in column A

categories	names	question	A	B	C	D	E	question_type
Ques/hist	Q1	Who’s buried in Grant’s tomb?	Grant	no one#Was true for 12 years, but Grant’s remains were buried in the tomb in 1897	Napoleon#He was buried in France	Churchill#He was buried in England	Mother Teresa#She was buried in India	mcq

Numeric Entry

You can right single or multiple answers of numeric entry questions with ranges and limits. - Answer with no preceding credit will take 100% credit. - If you precede an answer with partial credit, for example, ’‘%80%2’, typing 2 will give 80% of the credit for this question. - You can use ranges and limits like. - ‘4..6’ is any answer minimum 4 and maximum 6 - ‘5:1’ the answer is 5 plus or minus 1 Below are examples of numeric questions

	categories	names	question	A	B	question_type
7	Ques/math	Q7	What is the value of pi (to 3 decimal places)?	3.14159:0.0005		num_q
8	Ques/math	Q8	What is the value of pi (to 3 decimal places)?	3.141..3.142		num_q
9	Ques/hist	Q9	When was Ulysses S. Grant born?	1822:0	%50%1822:2#Not very percise	num_q
10	Ques/math	Q10	2<sup>2</sup>	4		num_q
11	Ques/hist	Q11	\[\int_\{1\}^\{2\}\{2xdx\}\]	3		num_q

Short Answer Question

You can use a single or multiple answers to be the answer with the same concept of partial credits of numeric questions, where no preceding credit is 100% and %90% is 90% …etc.

	categories	names	question	A	B	C	D	E	question_type
5	Ques/hist	Q5	Who’s buried in Grant’s tomb?	Grant	Ulysses S. Grant		Ulysses Grant		short_ans
6	Ques/math	Q6	Two plus two equals	four	4				short_ans

True or False

For true or false questions, you just right ‘T’ or ‘F’ in the first answer column.

	categories	names	question	A	B	C	D	E	question_type
3	Ques/hist	Q3	Grant was buried in a tomb in New York City	T					tf_q
4	Ques/science	Q4	The sun rises in the West.	F					tf_q

Answer Feedback

You can always add a feedback for any answer selected by adding # sign after the answer.

	A	B	C	D	E
1	*Grant	no one#Was true for 12 years, but Grant’s remains were buried in the tomb in 1897	Napoleon#He was buried in France	Churchill#He was buried in England	Mother Teresa#She was buried in India
9	1822:0	%50%1822:2#Not very percise

Question type column

The question types supported are mcq, numeric entry, true or false and short answer. You don’t have to specify those if you have only one type of them as you can use a single function specific to create those types of questions, however if you want to use GIFTr() function, you can’t leave this column empty.

for mcq value is mcq
for numeric entry value is ‘num_q’
for true or false value is tf_q
for short answer value is short_ans

Question names column

If you want to specify a specific keyword or ID for a question, you can specify it here. However you don’t have to worry about that this as question name is automatically generated to be the first 40 words of the questions column.

Here is how a full data may like.

categories	names	question	A	B	C	D	E	question_type
Ques/hist	Q1	Who’s buried in Grant’s tomb?	*Grant	no one#Was true for 12 years, but Grant’s remains were buried in the tomb in 1897	Napoleon#He was buried in France	Churchill#He was buried in England	Mother Teresa#She was buried in India	mcq
Ques/hist	Q2	What two people are entombed in Grant’s tomb?	No one	*Grant	*Grant’s wife	Grant’s father		mcq
Ques/hist	Q3	Grant was buried in a tomb in New York City	T					tf_q
Ques/science	Q4	The sun rises in the West.	F					tf_q
Ques/hist	Q5	Who’s buried in Grant’s tomb?	Grant	Ulysses S. Grant		Ulysses Grant		short_ans
Ques/math	Q6	Two plus two equals	four	4				short_ans
Ques/math	Q7	What is the value of pi (to 3 decimal places)?	3.14159:0.0005					num_q
Ques/math	Q8	What is the value of pi (to 3 decimal places)?	3.141..3.142					num_q
Ques/hist	Q9	When was Ulysses S. Grant born?	1822:0	%50%1822:2#Not very percise				num_q
Ques/math	Q10	2<sup>2</sup>	4					num_q
Ques/hist	Q11	\[\int_\{1\}^\{2\}\{2xdx\}\]	3					num_q

Import to R

It doesn’t matter how you import to R, you can use readxl package or read.csv() or what ever you like to import your spreadsheet as dataframe or tibble. A build-in data called GIFTrData is implemented here as example of spreadsheet after importing.

library(GIFTr)
head(GIFTrData)

##     categories names                                          question
## 1    Ques/hist    Q1                 Who's buried in **Grant's tomb**?
## 2    Ques/hist    Q2 What two people are entombed in **Grant's tomb?**
## 3    Ques/hist    Q3       Grant was buried in a tomb in New York City
## 4 Ques/science    Q4                        The sun rises in the West.
## 5    Ques/hist    Q5                     Who's buried in Grant's tomb?
## 6    Ques/math    Q6                               Two plus two equals
##        A
## 1 *Grant
## 2 No one
## 3      T
## 4      F
## 5  Grant
## 6   four
##                                                                                   B
## 1 no one#Was true for 12 years, but Grant's remains were buried in the tomb in 1897
## 2                                                                            *Grant
## 3                                                                              <NA>
## 4                                                                              <NA>
## 5                                                                  Ulysses S. Grant
## 6                                                                                 4
##                                  C                                  D
## 1 Napoleon#He was buried in France Churchill#He was buried in England
## 2                    *Grant's wife                     Grant's father
## 3                             <NA>                               <NA>
## 4                             <NA>                               <NA>
## 5                             <NA>                      Ulysses Grant
## 6                             <NA>                               <NA>
##                                       E question_type
## 1 Mother Teresa#She was buried in India           mcq
## 2                                  <NA>           mcq
## 3                                  <NA>          tf_q
## 4                                  <NA>          tf_q
## 5                                  <NA>     short_ans
## 6                                  <NA>     short_ans

str(GIFTrData)

## 'data.frame':    11 obs. of  9 variables:
##  $ categories   : chr  "Ques/hist" "Ques/hist" "Ques/hist" "Ques/science" ...
##  $ names        : chr  "Q1" "Q2" "Q3" "Q4" ...
##  $ question     : chr  "Who's buried in **Grant's tomb**?" "What two people are entombed in **Grant's tomb?**" "Grant was buried in a tomb in New York City" "The sun rises in the West." ...
##  $ A            : chr  "*Grant" "No one" "T" "F" ...
##  $ B            : chr  "no one#Was true for 12 years, but Grant's remains were buried in the tomb in 1897" "*Grant" NA NA ...
##  $ C            : chr  "Napoleon#He was buried in France" "*Grant's wife" NA NA ...
##  $ D            : chr  "Churchill#He was buried in England" "Grant's father" NA NA ...
##  $ E            : chr  "Mother Teresa#She was buried in India" NA NA NA ...
##  $ question_type: chr  "mcq" "mcq" "tf_q" "tf_q" ...

GIFTr Function

GIFTr() function is the main function of GIFTr Package. It arguments are:- - data: dataframe or tibble of the questions data - questions: name or index of the questions column - answers: a vector of names or indices of answers column(s) - categories: name or index of categories column if available, Default: NULL - question_name: Default is NULL and you don’t have to pass it. If you want them, it will be name or index of the questions names column. If NULL, it will be the first 40 letters of the question title. - question_type name or index of the questions type column. - mcq_answer_column: This parameter you can use on GIFTrData_2 as the answers of MCQs are in the first column and you have not multiple answer mcq. Default: FALSE - output: directory of .txt file name the questions will be exported to. The generated text will be appended to this file if it is already there, if not a new file will be created.

GIFTr::GIFTr(data = GIFTrData, question_names = 2, 
             questions = 3, answers = c(4:8), 
             categories = 1, question_type = 9,
            output = file.path(tempdir(), "quiz.txt"))

## Total Number of Questions passed: 11

## 
## ====
## ====
## ====
## ====

## MCQ questions input count: 2 
## MCQ questions with single answer passed: 1 
## MCQ questions with multiple answers passed: 1 
## Error found: 0 
## No valid question found : 0 
## No valid answer found: 0

## 
## ====
## ====
## ====
## Done MCQ!
## ===

## Numerical questions input count: 5 
## Numerical questions with single answer passed: 4 
## Numerical questions questions with multiple answers passed: 1 
## Error found: 0 
## No valid question found : 0 
## No valid answer found: 0

## 
## ====
## ====
## ====
## Done Numerical questions!
## ====

## total short answer questions passed is 2. 
## Valid answer: 2 
## error in 0 
## 0 no question has been found 
## 0 no valid answer has been found

## 
## ====
## ====
## ====
## Done Short Answer questions!
## ====

## T/F questions passed input: 2 
## T/F questions Passed: 2 
## Error found: 0 
## No question found : 0 
## No valid answer found: 0

## 
## ====
## ====
## ====
## Done T/F questions!
## ====

Now you have a file called quiz.txt in temporary directory that has the questions ready to be imported by MOODLE. You can simply use only “quiz.txt” to make the file permanent in the home directory.

You can also use specific functions if your dataframe holds only one type of questions. Check the documentation mcq(), num_q, tf_q() and short_ans() functions.