遊戲輔助機制之設計：以「小蜜蜂」射擊遊戲為例

Designing Game Assisted Mechanism: Using ＂Galax＂ Shooting Game as the Design Example

10.30105/JDS.201512_18(2).0004

周文修(Wen-Shou Chou)；許晏銘(Yen-Ming Hsu)；鄧進宏(Chin-Hung Teng)

遊戲輔助機制 ； 遊戲設計 ； 適應性關卡 ； 遊戲愉悅性 ； 遊戲挑戰性 ； Game Assisted Mechanism ； Game Design ； Adaptive Game Level Design ； Game Enjoyment ； Game Challenge

設計學研究

18卷2期（2015 / 12 / 01）

67 - 82

繁體中文

數位遊戲中玩家的技能能否與遊戲中挑戰的困難度相匹配，對於玩家的愉悅感與遊戲的遊戲性影響相當大。因而於遊戲中經常會提供一些輔助機制，以提升玩家在遊戲中的技能，並增進遊戲的愉悅性。目前有關遊戲輔助機制的設計，有的是提供不同難度的關卡供玩家選擇，有的是動態調整遊戲本身的難度，前者常常依然無法符合各種不同技能程度玩家的需求，而後者容易造成玩家對於遊戲挑戰性認知上的錯亂。本研究除了整理目前遊戲輔助機制的設計方法外，以射擊遊戲為例，提出一個輔助機制設計方法。此方法讓玩家在闖關失敗後，給予玩家提升技能的輔助。經由實驗結果顯示，此輔助機制，確實能幫助遊戲技巧能力不足的玩家達到與遊戲挑戰性平衡的效果，並進而改善遊戲的愉悅性。

How to match player's skills and game challenges plays an important role in digital game design. Many games have imbedded some mechanisms to assist players to enhance their skills and to improve the game playfulness. However, current assisted mechanisms either provide the selection of level difficulties before playing the game, or dynamically adjust the game difficulty while playing. For the former approach, the simplest level is still too difficult for some players. For the latter one, it will let players confuse about the game challenges. This study will analyze these assisted mechanisms and propose a design method. This method will provide the assisted mechanism to players if they can't overcome the game challenges. By using the shooting game as an illustration, It was shown that the proposed method can effectively match the player's skills and game challenges. The game playfulness and enjoyment can be effectively improved by using the proposed assisted mechanism.

1. 周文修、曾彥能(2011)。數位休閒遊戲愉悅性之評估與分析。設計學研究，14(2)，49-72。
   連結：
2. Csikzentmihalyi, M.(1990).Flow: The Psychology of Optimal Experience.New York:Harper and Row.
3. Hunicke, R.,Chapman, V.(2004).AI for dynamic difficulty adjustment in games.Proceedings of the Challenges in Game AI Workshop Nineteenth National Conference on Artificial Intelligence (AAAI'04),San Jose, California:
4. Jennings-Teats, M,Smith, G.,Wardrip-Fruin, N.(2010).Polymorph: Dynamic difficulty adjustment through level generation.PCGames'10:Proceeding of the 2010 Workshop on Procedural Content Generation in Games,New York:
5. Jenova, C.(2007).Flow in games.Communications of the ACM,50(4),31-34.
6. Malone, T. W.,Lepper, M. R.(1987).Making learning fun: A taxonomy of intrinsic motivations for learning.Aptitude, Learning, and Instruction: III. Cognative and Affective Process Analysis,Hillsdale, NJ:
7. Moneta, G. B.,Csikszentmihalyi, M.(1996).The effect of perceived challenges and skills on the quality of subjective experience.Journal of Personality,64(2),275-310.
8. Pilke, E. M.(2004).Flow experiences in information technology use.International Journal of Human-Computer Technology,61,347-357.
9. Sweetser, P.,Wyeth, P.(2005).GameFlow: A model for evaluating player enjoyment in games.ACM Computers in Entertainment,3(3),1-24.
10. Trefy, G.(2010).Casual Game Design: Designing Play for Gamer in ALL of Us.USA:Morgan Kaufmann.
11. Yun, C.,Trevino, P.,Holtkamp, W.,Deng, Z.(2010).PADS: Enhancing gaming experience using profile-based adaptive difficulty system.Proceeding of 5th ACM SIGGRAPH Symposium on Video Games,New York:
12. 吳明隆(2006)。SPSS 統計應用學習實務。台北:知城數位科技。