Article Sidebar

Submitted
September 14, 2024
Accepted
September 20, 2024
Published
September 21, 2024
Download
PDF
Statistic
Read Counter : 0 Download : 0

Main Article Content

Abstract

The research titled "Bajau-tainment" Educational Game (Edu-game) is a research project that focuses on the development of a Puzzle Game designed to improve memory, specifically in language learning. In this game, players must arrange randomized letters to form a word in the Bajau language. This research applies the shuffle random algorithm, which aims to ensure that the arrangement of letters is always shuffled, making the gameplay dynamic, non-monotonous, and engaging. AI Artificial Intelligence (AI) technology will also be applied in this research. Using the Finite State Machine (FSM) model method, the game will feature a game agent character that will accompany children during gameplay, like how a friend accompanies students in a classroom. This virtual friend can display emotions such as happiness or sadness based on the game environment. The research aims to make this edu-game more appealing and interactive for children. The AI game agent will act as a friend who accompanies the child throughout the game.

Keywords

Bajau, Puzzle Game, Educational Game, Shuffle Random, Finite State Machine

Article Details

License

Copyright (c) 2024 TEPIAN

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Khoirunnita, A., Alex, R., & Rosmasari , R. (2024). The Bajau-Tainment: An AI-Powered Puzzle Game for Learning the Bajau Language Using Finite State Machine and Shuffle Techniques. TEPIAN, 5(3), 94–101. https://doi.org/10.51967/tepian.v5i3.3140
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Adeniyi, A. E., Brahma, B., Adebiyi, M. O., Awotunde, J. B., Jimoh, R. G., Olasinde, E., & Bandyopadhyay, A. (2024). Development of Two Dimension (2D) Game Engine with Finite State Machine (FSM) Based Artificial Intelligence (AI) Subsystem. Procedia Computer Science, 235, 2996-3006.
  2. Al Hamaq, A., Elasyouti, A. A., Abou-Amona, R. T., & ElKhatib, N. G. (2024). Development and Evaluation of an Edutainment Tool for Imparting Education and Awareness among Type 1 Diabetes Children in Qatar. Journal of Diabetology, 15(2), 229-234.
  3. Alvian, M. B. R., Bukhori, S., & Furqon, M. A. (2024). Implementation of Finite State Machine to Determine The Behaviour of Non-Playabale Character in Leadership Simulation Game. Journal of Games, Game Art, and Gamification, 9(1), 11-21.
  4. Andrea, R., Yusnita, A., Daud, J., & Khoirunnita, A. (2023). Combination Probability in Finite State Machine Model for Intelligent Agent of Educational Game “I LOve Maratua”. In The International Symposium on Computer Science, Digital Economy and Intelligent Systems (pp. 252-265). Cham: Springer Nature Switzerland.
  5. Astuti, D., Kusuma, A. F. A. A., & Syah, F. (2022). Application of the Finite State Machine Method to Determine the End of the Story Based on User Choice in Multiple Role Playing Games. International Journal of Computer and Information System (IJCIS), 3(2), 64-68.
  6. Barthel, A. C., & Hoffmann, E. (2023). On the existence of stable equilibria in monotone games. Journal of Mathematical Economics, 105, 102817.
  7. Barz, N., Benick, M., Dörrenbächer-Ulrich, L., & Perels, F. (2024). The effect of digital game-based learning interventions on cognitive, metacognitive, and affective-motivational learning outcomes in school: A meta-analysis. Review of Educational Research, 94(2), 193-227.
  8. Behnamnia, N., Kamsin, A., Ismail, M. A. B., & Hayati, S. A. (2023). A review of using digital game-based learning for preschoolers. Journal of Computers in Education, 10(4), 603-636.
  9. Bryant, R. (2024). Game Testing All in One. Walter de Gruyter GmbH & Co KG.
  10. Cirant, M., & Porretta, A. (2021). Long time behavior and turnpike solutions in mildly non-monotone mean field games. ESAIM: Control, Optimisation and Calculus of Variations, 27, 86.
  11. Dunnett, N. (2024). Reimagining Boredom in Classrooms Through Digital Game Spaces: Sociomaterial Perspectives. Taylor & Francis.
  12. Freire, M., Serrano-Laguna, Á., Manero Iglesias, B., Martínez-Ortiz, I., Moreno-Ger, P., & Fernández-Manjón, B. (2023). Game learning analytics: Learning analytics for serious games. In Learning, design, and technology: An international compendium of theory, research, practice, and policy (pp. 3475-3502). Cham: Springer International Publishing.
  13. Greipl, S., Moeller, K., & Ninaus, M. (2020). Potential and limits of game-based learning. International Journal of Technology Enhanced Learning, 12(4), 363-389.
  14. Juul, J. (2024). Without a goal: on open and expressive games. In Videogame, player, text (pp. 191-203). Manchester University Press.
  15. Khoirunnita, A., Harpad, B. ., Ikhsan, N. ., Andrea, R., Beze, H., & Rudito, R. (2023). Development Intelligent Agent in Educational Game “Pesut Adventure – Borneo Animal Match-Up” with Shuffle Random Algorithm . TEPIAN, 4(4), 183–188. https://doi.org/10.51967/tepian.v4i4.2891
  16. Kuhail, M. A., ElSayary, A., Farooq, S., & Alghamdi, A. (2022, September). Exploring immersive learning experiences: A survey. In Informatics (Vol. 9, No. 4, p. 75). MDPI.
  17. Mahali, S. N. H. (2014, February). The Bajaus language. In Proceedings of the International Conference of Education and Social Sciences (INTCESS) (pp. 298-304).
  18. Mattei, V. (2023, November). Artificial Intelligence in Video Games 101: An Easy Introduction. In International Conference on Intelligent Technologies for Interactive Entertainment (pp. 40-51). Cham: Springer Nature Switzerland.
  19. Mosum, N. B., & Yusoff, M. Y. M. (2024). The Current Ethics And Civilisation In Bajau Society Today. Educational Administration: Theory and Practice, 30(5), 11907-11913.
  20. Noor, I. H., & Purnamasari, N. (2019). The Use of Local Context Learning Material in Integrated Teaching and Learning Instruction at Junior Secondary School (JSS): A Case Study in Pekanbaru District, Riau Province, Indonesia. Education Quarterly Reviews, 2(1), 232-241.
  21. Pukeng, A. F., Fauzi, R. R., Andrea, R., Yulsilviana, E., & Mallala, S. (2019, October). An intelligent agent of finite state machine in educational game “Flora the Explorer”. In Journal of Physics: Conference Series (Vol. 1341, No. 4, p. 042006). IOP Publishing.
  22. Pupius, R. (2015). SFML Game Development By Example. Packt Publishing Ltd.
  23. Suherman, A., & Winarso, W. (2021). Teaching-material of elementary social studies; constructing a powerful approach to local wisdom in Indonesia. International Journal of Education and Humanities (IJEH), 1(1), 2020.
  24. Steinkuehler, C., & Squire, K. (2024). Gaming in educational contexts. In Handbook of educational psychology (pp. 674-695). Routledge.
  25. Vistorte, A. O. R., Deroncele-Acosta, A., Ayala, J. L. M., Barrasa, A., López-Granero, C., & Martí-González, M. (2024). Integrating artificial intelligence to assess emotions in learning environments: a systematic literature review. Frontiers in Psychology, 15, 1387089.
  26. Zhan, Z., Tong, Y., Lan, X., & Zhong, B. (2024). A systematic literature review of game-based learning in Artificial Intelligence education. Interactive Learning Environments, 32(3), 1137-1158.