@inproceedings{bcf4b7d996e34890a634b6f1472757f7,
title = "Capturing changes and variations from teachers' time series usage data",
abstract = "The type of time series data is very common in educational settings, such data set usually provide usage trajectories involved complex contexts and unknown noisy. In this paper, we describe a statistical analysis method to detect a switch point over teacher's comment data set which is collected from a student evaluation system. We find that it is indeed possible to employ a statistical model and Bayesian inference to detect teacher who increased, decreased or no-changed their behavior. We also illustrated the potential of the application of change detection to conduct data exploration, which can be relative to understand teacher technology adoption and usage transition.",
keywords = "Change detection, MCMC, Statistical modeling, Teacher's technology adoption",
author = "Longwei Zheng and Yuanyuan Feng and Rui Shi and Xiaoqing Gu",
note = "Publisher Copyright: {\textcopyright} 2017 Asia-Pacific Society for Computers in Education. All rights reserved.; 25th International Conference on Computers in Education, ICCE 2017 ; Conference date: 04-12-2017 Through 08-12-2017",
year = "2017",
language = "英语",
isbn = "9789869401265",
series = "Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "475--480",
editor = "\{Mohd Ayub\}, \{Ahmad Fauzi\} and Antonija Mitrovic and Jie-Chi Yang and Wong, \{Su Luan\} and Wenli Chen",
booktitle = "Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings",
address = "中国台湾",
}