@inproceedings{67e0ce3616a54ef3ae8574fa6f268bb2,
title = "Learning Analytics Icons for analytics' transparency, information, and easy comprehension of data treatment of students",
abstract = "The principles defined in the General Data Protection Regulation (GDPR) of fair and transparent processing require that 1) the data subject be informed of the existence of the processing operation and its purposes, 2) the data subject should be informed of the existence of profiling and the consequences of such profiling, and 3) that information may be provided in combination with standardized icons to give in an easily visible, intelligible, and legible manner, a meaningful overview of the intended processing. These 3 points apply to education. However, processes mediated by Learning Analytics treat sensitive educational data, generate profiles, and have direct consequences for students, but no icons exist that represent this data processing accurately. Our study aims to provide icons that report the processing of data in Learning Analytics processes. The main objective is to facilitate educational institutions to be transparent and enhance information and easy comprehension of data treatment of students to students themselves. The methodology of the study consists of designs of icons and surveys to the students in an iterative execution. Our results expose a series of initial icons despite the strong dispersion in responses among students.",
keywords = "GDPR, Learning Analytics, data treatment, education, icons, privacy",
author = "Daniel Amo and Marc Alier and Rogelio Sansaloni and Javier Geli and David Fonseca and Garc{\'i}a-Pe{\~n}alvo, {Francisco Jos{\'e}} and Casa{\~n}, {Mar{\'i}a Jos{\'e}}",
note = "Publisher Copyright: {\textcopyright} 2021 ACM.; 9th International Conference on Technological Ecosystems for Enhancing Multiculturality, TEEM 2021 ; Conference date: 27-10-2021 Through 29-10-2021",
year = "2021",
month = oct,
day = "26",
doi = "10.1145/3486011.3486520",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "587--593",
editor = "Marc Alier and David Fonseca",
booktitle = "Proceedings - TEEM 2021",
address = "United States",
}