Course Information Module Document

class OpenLA.course_information.CourseInformation(course_id=None, files_dir=None, event_stream_file=None, lecture_material_file=None, lecture_time_file=None, quiz_score_file=None, grade_point_file=None, event_stream_df=None, lecture_material_df=None, lecture_time_df=None, quiz_score_df=None, grade_point_df=None)

Bases: object

load_eventstream()

Load event stream and return the instance of EventStream class.

Returns

The instance of EventStream

Return type

EventStream

event_stream_df()

Load DataFrame about event stream.

Returns

DataFrame about event stream

Return type

pandas.DataFrame

lecture_material_df()

Load DataFrame about contents id, lecture week using the contents, and the number of pages in the contents.

Returns

DataFrame about lecture material (contents)

Return type

pandas.DataFrame

lecture_time_df()

Load DataFrame about lecture week, the lecture start time, and the lecture end time.

Returns

DataFrame about lecture time

Return type

pandas.DataFrame

quiz_score_df()

Load DataFrame about user id and quiz score.

Returns

DataFrame about quiz score

Return type

pandas.DataFrame

grade_point_df()

Load DataFrame about user id and grade point.

Returns

DataFrame about quiz score

Return type

pandas.DataFrame

contents_id()

Get the contents ids in this course.

Returns

List of contents ids in this course

Return type

list[str]

lecture_week()

Get the week number lectures conducted in this course

Returns

List of lecture weeks in this course

Return type

list[int]

num_users()

Get the number of users in this course.

Returns

Number of users in this course

Return type

int

user_id()

Get unique user ids in this course.

Returns

List of user ids in this course

Return type

list[str]

user_score(user_id=None)

Get user(s) final score in this course.

Parameters

user_id (str or List[str] or None) – user id or list of user ids to get score data.

Returns

The quiz score of the user(s).

If the arguments “user_id” is given as a list, the function returns list of quiz scores.

Else if “user_id” is None, the function returns all users score.

Return type

float or List[float]

user_grade(user_id=None)

Get user(s) final grade in this course.

Parameters

user_id (str or List[str] or None) – user id or list of user ids to get grade data.

Returns

The grade point of the user(s).

If the arguments “user_id” is given as a list, the function returns list of grade point.

Else if “user_id” is None, the function returns all users score.

Return type

str or list[str]

grade_distribution()

Get grade distribution in this course.

Returns

DataFrame of grade distribution. (index: ‘grade’, columns:[‘count’, ‘proportion’])

Return type

pandas.DataFrame

users_in_selected_score(users_list=None, bottom=None, top=None)

Get user id(s) who got the score between selected scores.

Parameters

• users_list (list[str] or None) – list of user_ids. The return users are selected from users in this list. If this list is None, the users are selected from all users in this course.

• bottom (int or float or None) – the bottom score for extraction

• top (int or float or None) – the top score for extraction

Returns

List of user ids who got the score between “bottom” and “top”.

If the argument “bottom” is None, extract all users whose scores are under “top”.

If the argument “top” is None, extract all users whose scores are above “bottom”.

Return type

list[str]

users_in_selected_grade(users_list=None, grade=None)

Get user id(s) who got the selected grade.

Parameters

• users_list (list[str] or None) – list of user_ids. The return users are selected from users in this list. If this list is None, the users are selected from all users in this course.

• bottom (int or float or None) – the bottom score for extraction

• top (int or float or None) – the top score for extraction

Returns

List of user ids who got the grade(s) indicated by the argument ‘grade’

Return type

list[str]

contents_id_to_lecture_week(contents_id)

Get the week number of the lecture(s) using the content(s) of the argument “contents_id”.

Parameters

contents_id (str or list[str]) – The contents id or list of contents ids.

Returns

The lecture week corresponding to the “contents_id”.

If the argument “contents_id” is given as a list, the function returns list of lecture weeks.

Return type

int or list[int]

lecture_week_to_contents_id(lecture_week)

Get the content(s) id used in the lecture of the argument “lecture_week”.

Parameters

lecture_week (int or list[int]) – The lecture week or list of lecture weeks

Returns

The contents id corresponding to the lecture week(s).

If there is more than one relevant contents id, the function returns a list with them.

Return type

str or list[str]

num_pages_of_contents(contents_id)

Get the number of pages of the content(s) with the argument “contents_id”.

Parameters

contents_id (str or list[str]) – contents id or list of contents ids

Returns

The number of pages of the lecture material.

If the argument “contents_id” is given as a list, the function returns list of number of pages.

Return type

int or list[int]

lecture_start_time(lecture_week)

Get the start time of the lecture(s) of the argument “lecture_week”.

Parameters

lecture_week (int or list[int]) – lecture week or list of lecture weeks to get lecture start time.

Returns

The start time of the lecture in the lecture week.

If the argument “lecture_week” is given as a list, the function returns list of start times.

Return type

pandas.Timestamp or list of pandas.Timestamp

lecture_end_time(lecture_week)

Get the end time of the lecture(s) of the argument “lecture_week”.

Parameters

lecture_week (int or list[int]) – lecture week or list of lecture weeks to get lecture end time.

Returns

The end time of the lecture in the lecture week.

If the argument “lecture_week” is given as a list, the function returns list of end times.

Return type

pandas.Timestamp or list of pandas.Timestamp

OpenLA.course_information.start_analysis(course_id=None, files_dir=None, event_stream_file=None, lecture_material_file=None, lecture_time_file=None, quiz_score_file=None, grade_point_file=None, event_stream_df=None, lecture_material_df=None, lecture_time_df=None, quiz_score_df=None, grade_point_df=None)

Get CourseInformation instance and EventStream instance simultaneously. For any given data source, the file path will take priority over the DataFrame if both arguments are passed.

Parameters

• course_id (str or None) – The id of the course to process.

• files_dir (str or None) – The directory which has “Course_xxx_EventStream.csv”, “Course_xxx_LectureMaterial.csv”, “Course_xxx_LectureTime.csv”, and “Course_xxx_QuizScore.csv (xxx is course id).

• event_stream_file (str or None) – If you want to specify the file path directly, use this argument.

• lecture_material_file (str or None) – If you want to specify the file path directly, use this argument.

• lecture_time_file (str or None) – If you want to specify the file path directly, use this argument.

• quiz_score_file (str or None) – If you want to specify the file path directly, use this argument.

• event_stream_df (pandas.DataFrame or None) – If you want to pass a DataFrame directly, use this argument.

• lecture_material_df (pandas.DataFrame or None) – If you want to pass a DataFrame directly, use this argument.

• lecture_time_df (pandas.DataFrame or None) – If you want to pass a DataFrame directly, use this argument.

• quiz_score_df (pandas.DataFrame or None) – If you want to pass a DataFrame directly, use this argument.

• grade_point_df (pandas.DataFrame or None) – If you want to pass a DataFrame directly, use this argument.

Returns

• course_info - Instances of class “CourseInformation”

• event_stream - Instances of class “EventStream”