Tutorial of Course Information Module

Course Information Module has a Python class structure.

CourseInformation class receives dataset files and the method functions return basic course information.

The dataset structure is introduced in Dataset for OpenLA.

Specify the directory path including four types of files and course id.

import openLA as la

course_info = la.CourseInformation(files_dir="dataset_sample", course_id="A")

If you want to specify the dataset files paths directly, use the arguments “event_stream_file”, “lecture_material_file”, “lectrue_time_file”, “quiz_score_file”, and “grade_point_file”.

These arguments are useful in the case that the course does not have the course id, the dataset files do not exist in same directory, etc.

import openLA as la

course_info = la.CourseInformation(event_stream_file="dataset_sample/Course_A_EventStream.csv",
                                   lecture_material_file="dataset_sample/Course_A_LectureMaterial.csv",
                                   lecture_time_file="dataset_sample/Course_A_LectureTime.csv",
                                   quiz_score_file="dataset_sample/Course_A_QuizScore.csv",
                                   grade_point_file="dataset_sample/Course_A_GradePoint")

If you want load pandas DataFrames instead of CSV files, use the arguments “event_stream_df”, “lecture_material_df”, “lectrue_time_df”, “quiz_score_df”, and “grade_point_df”.

import openLA as la
import pandas as pd

event_stream_df = pd.read_csv("dataset_sample/Course_A_EventStream.csv")
lecture_material_df = pd.read_csv("dataset_sample/Course_A_LectureMaterial.csv")
lecture_time_df = pd.read_csv("dataset_sample/Course_A_LectureTime.csv")
quiz_score_df = pd.read_csv("dataset_sample/Course_A_QuizScore.csv")
grade_point_df = pd.read_csv("dataset_sample/Course_A_GradePoint.csv")

course_info = la.CourseInformation(event_stream_df=event_stream_df,
                                   lecture_material_df=lecture_material_df,
                                   lecture_time_df=lecture_time_df,
                                   quiz_score_df=quiz_score_df,
                                   grade_point_df=grade_point_df)

The method functions in below table are available now.

You can get the basic information of the course like course_info.num_users().

The documentation is in Course Information Module Document

function	description
num_users	Get the number of users
user_id	Get the unique user ids
contents_id	Get the unique contents ids
lecture_week	Get the lecture weeks
user_score	Get the user(s) final score
users_in_selected_score	Get the user ids who got the score between selected scores
user_grade	Get the user(s) final grade
users_in_selected_grade	Get the user ids who got the score between selected grade
grade_distribution	Get the grade distribution in the course
contents_id_to_lecture_week	Get the lecture week using the specified content(s)
lecture_week_to_contents_id	Get the contents id used in the specified lecture(s)
num_page_of_contents	Get the number of pages in the specified content(s)
lecture_start_time	Get the start time of the specified lecture(s)
lecture_end_time	Get the end time of the specified lecture(s)
load_event_stream	Get the instance of EventStream class Tutorial of EventStream Class
lecture_material_df	Get the DataFrame about information of contents
lecture_time_df	Get the DataFrame about lecture start and end time
quiz_score_df	Get the DataFrame about users’ final score

Example

• Example of Course Information