@inproceedings{55d62f2c606f4510a912acc2f41c1d8e,
title = "Identify and help at-risk students before it is late",
abstract = "Identifying at-risk students early in the term is valuable. It is because an instructor can have more time to provide extra support, and students can also estimate how much extra effort they should put on to succeed in class. Prior work showed it is possible to predict at-risk students, but they either did not provide a specific prediction method or are too onerous to implement. Thus, my dissertation will develop and evaluate more robust, universal, and simple prediction methodology to classify at-risk students and propose how to automatically generate customized practice materials for early intervention. Once the methodology becomes robust, I will implement publicly accessible educational software application so that other CS instructors can easily adopt this method.",
keywords = "At-risk students, Clicker data, Early-intervention, Final exam scores",
author = "{Nam Liao}, Soohyun",
note = "Publisher Copyright: {\textcopyright} Copyright is held by the owner/author(s).; 12th Annual International Computing Education Research Conference, ICER 2016 ; Conference date: 08-09-2016 Through 12-09-2016",
year = "2016",
month = aug,
day = "25",
doi = "10.1145/2960310.2960355",
language = "English (US)",
series = "ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research",
publisher = "Association for Computing Machinery, Inc",
pages = "295--296",
booktitle = "ICER 2016 - Proceedings of the 2016 ACM Conference on International Computing Education Research",
}