@inproceedings{e1d0c87a5aff4aa5acd9c149dfccfe55,
title = "FATED: Fairness, Accountability, and Transparency in Educational Data (Mining)",
abstract = "This document outlines a proposed full-day workshop focused on the intersection of fairness, accountability, transparency, and educational data mining (EDM). The workshop aims to provide a multidisciplinary perspective on fairness-related work from both “sides” of the EDM community (education and data mining) along with other relevant fields (human–computer interaction, machine learning, etc.). Our workshop aims to be an inclusive opportunity for EDM researchers to learn about an emerging field, as well as to define a research agenda for this area of critical importance to the field.",
author = "Nigel Bosch and Christopher Brooks and Shayan Doroudi and Josh Gardner and Kenneth Holstein and Lan, {Andrew S.} and Collin Lynch and Woolf, {Beverly Park} and Mykola Pechenizkiy and Steven Ritter and Vie, {Jill J{\^e}nn} and Renzhe Yu",
note = "Publisher Copyright: {\textcopyright} 2020 Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020. All rights reserved.; 13th International Conference on Educational Data Mining, EDM 2020 ; Conference date: 10-07-2020 Through 13-07-2020",
year = "2020",
language = "English (US)",
series = "Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020",
publisher = "International Educational Data Mining Society",
pages = "831--834",
editor = "Rafferty, {Anna N.} and Jacob Whitehill and Cristobal Romero and Violetta Cavalli-Sforza",
booktitle = "Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020",
}