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rgoogleclassroom
is a Google API wrapper that allows you
to use Google Classroom and Google Forms from the coziness and comfort
of R.
You can read the rgoogleclassroom package documentation here.
To use this package you need to have a Google Classroom account. Go here to get that: https://edu.google.com/workspace-for-education/classroom/
If you want the development version (not advised) you can install
using the remotes
package to install from GitHub.
if (!("remotes" %in% installed.packages())) {
install.packages("remotes")
}
remotes::install_github("datatrail-jhu/rgoogleclassroom")
In order to make a new course with rgoogleclassroom
you
need your owner id. You can get this by running the following:
`owner_id <- get_owner_id()
To start, you need to authorize()
the package to access
your files. Select all the scopes you feel comfortable sharing. Note
that you need to select certain scopes for certain functions to
work.
You can do this by running the authorize()
function. You
can authorize programmatically using a secret if you use the
auth_from_secret()
function.
There are different objects on the Google API:
Most of these objects have functions that do the following:
get_<object>_list()
create_<object>()
get_<object>_properties()
delete_<object>()
For example:
get_course_list(owner_id)
retrieves a list of courses
for a particular owner id. create_course()
creates a course
get_course_properties(course_id)
retrieves the properties
of a course given its id.
These can be built together to be pretty nifty.
Run the function to authorize the app to use your Google account.
authorize()
Retrieve whatever your owner id for Google Classroom is.
owner_id <- get_owner_id()
Now you can retrieve a list of courses that are associated with your owner id.
course_df <- get_course_list(owner_id)
For the following examples, we will need to use
Create a course
new_course <- create_course(owner_id$id, name = "New course")
We can create new material for the students using by building this together like this:
# Create a course we will use for this test
owner_id <- get_owner_id()
new_course <- create_course(owner_id$id, name = "New course")
# Create material at this course
new_material <- create_material(course_id = new_course$id,
title = "New material")
# Retrieve the material info
materials_info <- get_materials_properties(course_id = new_course$id,
materials_id = new_material$id)
Retrieve the list of all the materials for the course
materials_list <- get_materials_list(course_id = new_course$id)
We can manage courseworks!
It’s mandatory from the Google API that due dates for courseworks be given.
# Create a new coursework
new_coursework <- create_coursework(course_id = new_course$id,
title = "New coursework",
due_date = lubridate::today() + lubridate::hours(24))
# Get coursework properties
course_work_info <- get_coursework_properties(course_id = new_course$id, coursework_id = new_coursework$id)
# Retrieve all the courseworks for this course
coursework_list <- get_coursework_list(course_id = new_course$id)
We can build a quiz like this:
course_id <- get_course_list()$courses$id[1]
quiz_form_id <- create_quiz(
course_id = course_id,
quiz_title = "new quiz",
quiz_description = "This is a great quiz",
due_date = "2025-12-1")
We can create a new multiple choice question in the quiz we just made by using these steps:
create_multiple_choice_question(
form_id = quiz_form_id$formId,
question = "What answer do you want?",
choice_vector = c("A", "B", "C", "D"),
correct_answer = 3,
shuffle_opt = TRUE
)
We can create a text question in the quiz by doing this:
create_text_question(
form_id = quiz_form_id$formId,
question = "Put some text here to answer this question",
)
Before you can delete a course, you have to archive it:
archive_course(new_course$id)
Then we can delete it:
delete_course(new_course$id)
## R version 4.1.2 (2021-11-01)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## loaded via a namespace (and not attached):
## [1] digest_0.6.33 R6_2.5.1.9000 jsonlite_1.8.7 evaluate_0.21
## [5] rlang_1.1.1 cli_3.6.1 rstudioapi_0.13 jquerylib_0.1.4
## [9] bslib_0.3.1 rmarkdown_2.20 tools_4.1.2 xfun_0.39
## [13] yaml_2.3.7 fastmap_1.1.1 compiler_4.1.2 htmltools_0.5.2
## [17] knitr_1.43 sass_0.4.1
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.