Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Shimada, A., Konomi, S.I., Ogata, H.: Real-time learning analytics system for improvement of on-site lectures. Interact. Technol. Smart Educ. 15, 314–331 (2018)
Dougiamas, M., Taylor, P.: Moodle: using learning communities to create an open source course management system. In: Proceedings of EdMedia, World Conference on Educational Media and Technology 2003, pp. 171–178 (2003)
Dobashi, K.: Interactive mining for learning analytics by automated generation of pivot table. In: Advances in Artificial Intelligence, Software and Systems Engineering, AHFE 2018. Advances in Intelligent Systems and Computing, vol. 787, pp. 66–77. Springer, Cham (2018)
McKay, T., Miller, K., Tritz, J.: What to do with actionable intelligence: E2Coach as an intervention engine. In: LAK 2012 Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, Canada, pp. 88–91 (2012)
Arnold, K.E., Pistilli, M.D.: Course signals at Purdue: using learning analytics to increase student success. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, pp. 267–270. ACM (2012)
Hardy, J., Bates, S., Hill, J., Antonioletti, M.: Tracking and visualization of student use of online learning materials in a large undergraduate course. In: ICWL. LNCS, vol. 4823, pp. 464–474. Springer (2008)
May, M., Sebastien, G., Patrick, P.: TrAVis to enhance online tutoring and learning activities: real-time visualization of students tracking data. Technol. Smart Educ. 8(1), 52–69 (2011)
Mazza, R., Milani, C.: GISMO: a graphical interactive student monitoring tool for course management systems. In: 2004 International Conference on Technology Enhanced Learning, TEL 2004, Milan, Italia, pp. 1–8 (2004)
Acknowledgments
This work was supported by JSPS KAKENHI Grant Number 18K11588.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Dobashi, K. (2020). Development of Real-Time Learning Analytics Using Scraping and Pivot Tables. In: Nunes, I. (eds) Advances in Human Factors and Systems Interaction. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1207. Springer, Cham. https://doi.org/10.1007/978-3-030-51369-6_42
Download citation
DOI: https://doi.org/10.1007/978-3-030-51369-6_42
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51368-9
Online ISBN: 978-3-030-51369-6
eBook Packages: EngineeringEngineering (R0)