@inproceedings{d1be21eb59c846d39a4c0d18b1840621,
title = "Learning analytics: An enabler for dropout prediction",
abstract = "A key application of learning analytics is predicting students' learning performances and risks of dropping out. Heterogeneous data were collected from selected school to yield a model for predicting student's dropout. Results from this exploratory study conclude dropout prediction by learning analytics may provide more precise information on identifying at-risk students and factors causing them to be at risk.",
keywords = "Dropout, Learning analytics, Predictive model",
author = "Tseng, {Shu Fen} and Chou, {Chih Yueh} and Chen, {Zhi Hong} and Chao, {Po Yao}",
year = "2014",
language = "English",
series = "Workshop Proceedings of the 22nd International Conference on Computers in Education, ICCE 2014",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "286--288",
editor = "Thepchai Supnithi and Kong, {Siu Cheung} and Ying-Tien Wu and Tomoko Kojiri and Chen-Chung Liu and Hiroaki Ogata and Akihiro Kashihara",
booktitle = "Workshop Proceedings of the 22nd International Conference on Computers in Education, ICCE 2014",
note = "22nd International Conference on Computers in Education, ICCE 2014 ; Conference date: 30-11-2014 Through 04-12-2014",
}