TY - GEN
T1 - Data Mining Techniques for Analysing Data Extracted from Serious Games
T2 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022
AU - Acosta-Urigüen, María Inés
AU - Orellana, Marcos
AU - Cedillo, Priscila
N1 - Publisher Copyright:
Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Serious games are applications that pursue, on the one hand, the users' entertainment and, on the other hand, look to promote their learning, cognitive stimulation, among reaching other objectives. Moreover, data generated from those games (e.g., demographic information, gaming precision, user efficiency) provide insights helpful in improving certain aspects such as the attention and memory of the gamers. Therefore, applying data mining techniques over those data allows obtaining multiple patterns to improve the game interface, identify preferences, discover, predict, train, and stimulate the users' cognitive situation, among other aspects, to reach the games' objectives. Unfortunately, although several solutions have been addressed about this topic, no secondary studies have been found to condensate research that uses data mining to extract patterns from serious games. Thus, this paper presents a Systematic Literature Review (SLR) to extract such evidence from studies reported between 2001 and 2021. Besides, this SLR aims to answer research questions involving serious games solutions that train the cognitive functions of their users and data mining techniques associated with data gathered from those games.
AB - Serious games are applications that pursue, on the one hand, the users' entertainment and, on the other hand, look to promote their learning, cognitive stimulation, among reaching other objectives. Moreover, data generated from those games (e.g., demographic information, gaming precision, user efficiency) provide insights helpful in improving certain aspects such as the attention and memory of the gamers. Therefore, applying data mining techniques over those data allows obtaining multiple patterns to improve the game interface, identify preferences, discover, predict, train, and stimulate the users' cognitive situation, among other aspects, to reach the games' objectives. Unfortunately, although several solutions have been addressed about this topic, no secondary studies have been found to condensate research that uses data mining to extract patterns from serious games. Thus, this paper presents a Systematic Literature Review (SLR) to extract such evidence from studies reported between 2001 and 2021. Besides, this SLR aims to answer research questions involving serious games solutions that train the cognitive functions of their users and data mining techniques associated with data gathered from those games.
KW - Data Mining
KW - Serious Games
KW - Systematic Review
UR - https://www.academia.edu/103457013/Arqueolog%C3%ADa_p%C3%BAblica_y_comunicaci%C3%B3n_configuraciones_medi%C3%A1ticas_del_y_sobre_el_patrimonio_arqueol%C3%B3gico
U2 - 10.5220/0011042900003188
DO - 10.5220/0011042900003188
M3 - Contribución a la conferencia
AN - SCOPUS:85140969498
T3 - International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE - Proceedings
SP - 220
EP - 227
BT - Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health, ICT4AWE 2022
A2 - Ziefle, Martina
A2 - Mulvenna, Maurice
A2 - Maciaszek, Leszek
A2 - Maciaszek, Leszek
PB - Science and Technology Publications, Lda
Y2 - 23 April 2022 through 25 April 2022
ER -