Development of Real-Time Learning Analytics Using Scraping and Pivot Tables

  • Konomu DobashiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1207)


In a PC classroom attended by a large number of students, the author conducted a face-to-face, blended lesson using Moodle and proposes a method to efficiently analyze student learning logs. The system (TSCS Monitor) allows the user to visualize the analyzed results in a time-series presented in both table and graph form. In this paper, real-time processing using scraping was integrated to the above functions in order to reduce the burden of system operation on the teacher and obtain analysis results faster while conducting classes. With the integrated scraping function, it is now possible to automatically download Moodle course logs. Teachers can check the clickstream of course materials in real-time in a time-series cross-section table simply by starting TSCS Monitor during class. The author tested the system, released the analysis results to the students, and assessed the effects on the students via a class evaluation questionnaire.


Real-time Learning analytics Scraping Visualization Time-series Cross-section Pivot table Moodle 



This work was supported by JSPS KAKENHI Grant Number 18K11588.


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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Modern Chinese StudiesAichi UniversityNagoya-shiJapan

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