CFP last date
20 May 2024
Reseach Article

Computational Intelligence in Serious Games: A Case Study to Identify Patterns in a Game for Children with Learning Disabilities

by Andreia M. Domingues, Sabrinna Delgado, Marcia A.S. Bissaco, Sidnei A. De Araújo
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 7
Year of Publication: 2022
Authors: Andreia M. Domingues, Sabrinna Delgado, Marcia A.S. Bissaco, Sidnei A. De Araújo
10.5120/ijca2022922044

Andreia M. Domingues, Sabrinna Delgado, Marcia A.S. Bissaco, Sidnei A. De Araújo . Computational Intelligence in Serious Games: A Case Study to Identify Patterns in a Game for Children with Learning Disabilities. International Journal of Computer Applications. 184, 7 ( Apr 2022), 40-44. DOI=10.5120/ijca2022922044

@article{ 10.5120/ijca2022922044,
author = { Andreia M. Domingues, Sabrinna Delgado, Marcia A.S. Bissaco, Sidnei A. De Araújo },
title = { Computational Intelligence in Serious Games: A Case Study to Identify Patterns in a Game for Children with Learning Disabilities },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2022 },
volume = { 184 },
number = { 7 },
month = { Apr },
year = { 2022 },
issn = { 0975-8887 },
pages = { 40-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number7/32344-2022922044/ },
doi = { 10.5120/ijca2022922044 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:54.100555+05:30
%A Andreia M. Domingues
%A Sabrinna Delgado
%A Marcia A.S. Bissaco
%A Sidnei A. De Araújo
%T Computational Intelligence in Serious Games: A Case Study to Identify Patterns in a Game for Children with Learning Disabilities
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 7
%P 40-44
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This work explores the application of computational intelligence techniques in a serious game (SG) for children with learning disabilities. Specifically, Data Mining (DM) techniques such as Decision Tree and Apriori algorithms were applied to identify the existence of patterns that allow a better understanding of the children’s profiles involved in the game. The data analyzed are related to the interaction of twenty children with the considered SG, which consists of a three-dimensional virtual zoo, developed with features that appeal to the preferences of children about nine years old to assist and motivate their learning. The results obtained in the conducted experiments revealed patterns in the profiles of the game's players under analysis, allowing to identify some characteristics that can help the psychopedagogical team. These findings can also enable the improvement of the game making it adaptable to different player profiles.

References
  1. Cornejo, R., Martínez, F., Álvarez, V. C., Barraza, C., Cibrian, F. L., Martínez-García, A. I., &Tentori, M. “Serious games for basic learning mechanisms: reinforcing Mexican children’s gross motor skills and attention”,Personal and Ubiquitous Computing, 25(2), 375-390, 2021.
  2. American Psychiatric Association. “Diagnostic and statistical manual of mental disorders: DSM-5 (Vol. 5)”. Washington, DC: American psychiatric association. 2013.
  3. dos Santos, I. J., Frighetto, A. M., & dos Santos, J. C. “Dyslexia: A Learning Disability”. Nativa–Revista de Ciências Sociais do Norte de Mato Grosso, 2(1). 2013.
  4. Avila-Pesantez, D., Delgadillo, R., & Rivera, L. A. “Proposal of a conceptual model for serious games design: A case study in children with learning disabilities”. IEEE Access, 7, 161017-161033.2019.
  5. Flogie, A., Aberšek, B., Aberšek, M. K., Lanyi, C. S., &Pesek, I. “Development and evaluation of intelligent serious games for children with learning difficulties: observational study”. JMIR Serious Games, 8(2), 2020.
  6. Palma, N. M. & Ramos, J. L. “Physical activity, obesity and active video games at school: study of gaming habits and practices in elementary and secondary school youth”. Doctoral dissertation, Evora University (Portugal). 2013.
  7. da Silva Lourenço, W., de Araujo Lima, S. J., & Alves de Araújo, S. “TASNOP: A tool for teaching algorithms to solve network optimization problems”. Computer Applications in Eng. Education, 26(1), 101-110.2018.
  8. Keller, C., Döring, A. K., & Makarova, E. “The potential of Serious Games to foster learning among children and adolescents with disabilities: A systematic review”. Digital Culture and Education, 13(2), 6-36. 2021.
  9. Rocha, T., & Barroso, J. “PLAY for LEARNING: Serious Games to Assist Learning of Basic Didactic Concepts: A Pilot Study”. In:International Conference on Human-Computer Interaction (pp. 62-71). Springer, Cham. 2021.
  10. Fayyad, U, Piatetsky-Shapiro, G., Smyth, P., &Uthurusamy, R. “Advances in knowledge discovery and data mining”. American Association for Artificial Intelligence. Menlo Park: MIT Press. 1996.
  11. Bhat, P., Malaganve, P., & Hegde, P. “A new framework for social media content mining and knowledge discovery”. International Journal of Computer Applications, 182(36), 17-20. 2019.
  12. Mitchell, T. M. “Machine Learning”. New York: McGraw-Hill. 1997.
  13. Quinlan, J. R. “Induction of decision trees”. Machine Learning, 1(1):81-106. 1986.
  14. de Araújo, S. A., de Barros, D. F., da Silva, E. M., & Cardoso, M. V. “Applying computational intelligence techniques to improve the decision making of business game players”. Soft Computing, 23(18), 8753-8763.2019.
  15. Quinlan, J. R. “C4.5: programs for machine learning”. Morgan Kaufmann Publ. Inc., San Francisco, USA. 1993.
  16. Bramer,M. “Principles of data mining”. Springer, London. 2007.
  17. Agrawal, R., & Srikant, R. “Fast algorithms for mining association rules”. In:Proc. 20th int. conf. very large data bases, VLDB (vol. 1215, pp. 487-499). 1994.
  18. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Logan S, Medford E, &Hughes, N.“The importance of intrinsic motivation for high and low ability readers' reading comprehension performance”. Learning and Individual Differences 21(1), 124-128. 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Computational Intelligence Data Mining Pattern Recognition Decision Tree Apriori Algorithm