Analyzing the improvement process of table tennis using the game refinement theory
Jiangzhou, Li and Primanita, Anggina and Khalid, M. N. A. and Iida, Hiroyuki
Proceedings of the Sriwijaya International Conference on Information Technology and Its Applications · 2020
Abstract
Table With a history of just over 100 years, table tennis has slowly become the seventh-largest sport in the world. However, it is unclear whether the improvement actually makes the game better or worst. As such, a consistent quantification approach is needed. In this paper, game refinement (GR) theory was adopted to measure the attractiveness of table tennis and study the change of the GR value when the game is improved. The improvement observed in this study includes physical plays such as ball diameters, the game rules, set numbers, and score limits are analyzed. In addition, in comparison with real Table The finding of the study proves that the continuous improvement of table tennis is beneficial.
Interactive demo
This interactive is a faithful re-design of the research, simplified for illustrative and teaching purposes. It conveys the idea and behaviour of the model — it is not the paper’s full method, data, or results.
A looping preview of game-refinement theory: an abstract game plays itself, and its refinement value GR = √B ⁄ D settles on the engagement spectrum against the comfortable zone, with live thrill and addiction readouts.
Jiangzhou, Li and Primanita, Anggina and Khalid, M. N. A. and Iida, Hiroyuki. “Analyzing the improvement process of table tennis using the game refinement theory.” In Proceedings of the Sriwijaya International Conference on Information Technology and Its Applications, 2020.
@inproceedings{jiangzhou2020analyzing,
author = {Jiangzhou, Li and Primanita, Anggina and Khalid, M. N. A. and Iida, Hiroyuki},
title = {Analyzing the improvement process of table tennis using the game refinement theory},
booktitle = {Proceedings of the Sriwijaya International Conference on Information Technology and Its Applications},
year = {2020},
doi = {10.2991/aisr.k.200424.067},
}