The datasets for this data challenge have been synthetically generated from real data, and include 4 types of files: 

Course_#_EventStream.csv

   - Data of the logged activity data from students' interactions with the BookRoll system.

Course_#_LectureMaterial.csv

   - Information about the length of the lecture materials used.

Course_#_LectureTime.csv 

   - Information about the schedule of the lectures. This can be used to analyze the preview/in-class/review reading behaviors.

Course_#_GradePoint.csv

       OR

Course_#_QuizScore.csv 

   - Data on the final score(0-100) OR grade(A, B, C, D, F) for each student. This can be used as a label for each student when modeling data.

For a more description of the columns, please refer to the README file in the dataset download.

A link to download the dataset will be provided after your contact information has been registered and agreement with the terms of use have been met.

In order to handle GradePoint files in the dataset with OpenLA, it is necessary to update OpenLA by using the following command if you already have it installed.

pip install -U OpenLA

Acknowledgements: Ryusuke Murata (Kyushu University, Japan) contributed to the development of OpenLA and the generation of a part of the datasets.

Handy Tools:

The following is a Python library that can read BookRoll log files provided by this workshop, extract data, convert data, and perform simple visualization.

OpenLA：http://limu.ait.kyushu-u.ac.jp/~openLA/

Developer: Laboratory for Image and Media Understanding, Kyushu University.