TY - GEN
T1 - Online change detection for monitoring individual student behavior via clickstream data on E-book system
AU - Shimada, Atsushi
AU - Taniguchi, Yuta
AU - Okubo, Fumiya
AU - Konomi, Shin’ichi
AU - Ogata, Hiroaki
N1 - Funding Information:
This work was supported by JST PRESTO Grant Number JPMJPR1505, and JSPS KAKENHI Grand Number JP16H06304, Japan.
Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/3/7
Y1 - 2018/3/7
N2 - We propose a new change detection method using clickstream data collected through an e-Book system. Most of the prior work has focused on the batch processing of clickstream data. In contrast, the proposed method is designed for online processing, with the model parameters for change detection updated sequentially based on observations of new click events. More specifically, our method generates a model for an individual student and performs minute-by-minute change detection based on click events during a classroom lecture. We collected clickstream data from four face-to-face lectures, and conducted experiments to demonstrate how the proposed method discovered change points and how such change points correlated with the students’ performances.
AB - We propose a new change detection method using clickstream data collected through an e-Book system. Most of the prior work has focused on the batch processing of clickstream data. In contrast, the proposed method is designed for online processing, with the model parameters for change detection updated sequentially based on observations of new click events. More specifically, our method generates a model for an individual student and performs minute-by-minute change detection based on click events during a classroom lecture. We collected clickstream data from four face-to-face lectures, and conducted experiments to demonstrate how the proposed method discovered change points and how such change points correlated with the students’ performances.
UR - http://www.scopus.com/inward/record.url?scp=85045878713&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045878713&partnerID=8YFLogxK
U2 - 10.1145/3170358.3170412
DO - 10.1145/3170358.3170412
M3 - Conference contribution
AN - SCOPUS:85045878713
T3 - ACM International Conference Proceeding Series
SP - 446
EP - 450
BT - Proceedings of the 8th International Conference on Learning Analytics and Knowledge
PB - Association for Computing Machinery
T2 - 8th International Conference on Learning Analytics and Knowledge, LAK 2018
Y2 - 5 March 2018 through 9 March 2018
ER -