Gaming System Practice Mode for Player Skill Development
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Solution Overview
Problem
Gaming machines lack innovative features to retain player interest and attract new players, as existing games do not offer sufficient variety or skill-based progression, leading to decreased engagement and participation.
Innovation Solution
A gaming system and method that allows players to choose between a practice game state and a standard game state, providing distinct award structures and skill-based challenges, with the practice state offering assistance and lower risk to develop skills, and the standard state offering higher volatility and potential rewards based on player performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a practice game state is added to allow skill development, then player engagement and confidence are improved, but device complexity and game structure become more complex
Solution Approach 1:
The game is divided into distinct practice and standard modes, allowing players to choose between skill development (practice) and reward optimization (standard). This segmentation resolves the contradiction by providing adaptability through mode selection while maintaining a manageable structure through clear separation of functions.
Solution Approach 2:
The system dynamically adjusts game parameters, award structures, and help availability based on the selected mode. In practice mode, help is more abundant and awards are guaranteed; in standard mode, help is reduced and awards are outcome-based. This dynamic adjustment provides adaptability while keeping the underlying game engine reusable.
2Reliability
If practice mode provides guaranteed awards to build confidence, then player retention is improved, but the quantity and distribution of awards change from traditional outcome-based structures
Solution Approach 1:
Different award structures are applied to different game modes. Practice mode receives guaranteed awards with nominal values to build confidence, while standard mode receives outcome-based awards with variable values. This local differentiation resolves the contradiction by providing reliability through guaranteed practice awards while maintaining traditional award distribution in standard mode.
Solution Approach 2:
The system changes key parameters including award guarantee status, award values, and volatility levels based on game mode. Practice mode uses low volatility and guaranteed awards, while standard mode uses high volatility and outcome-based awards. These parameter changes enable player retention through confidence-building while managing overall award distribution.
3Adaptability or versatility
If standard game state offers higher volatility and potential rewards, then player excitement and attraction are improved, but player risk and potential losses increase
Solution Approach 1:
The game is segmented into practice mode (low risk, skill development) and standard mode (high risk, high reward). This segmentation resolves the contradiction by allowing players to attract interest through the excitement of standard mode while managing risk through the safety net of practice mode.
Solution Approach 2:
Players are encouraged to perform preliminary practice sessions before engaging in standard mode gameplay. This preliminary action allows skill development and confidence building in a low-risk environment, reducing the harmful effect of risk when players later engage in higher-stakes standard mode games.
4Ease of operation
If practice mode provides extensive help and tips, then ease of operation is improved, but device complexity increases due to additional help systems
Solution Approach 1:
The help system dynamically adjusts its intensity and availability based on game mode. Practice mode provides extensive help, tips, and guidance to improve ease of operation. Standard mode provides minimal or no help to maintain challenge and excitement. This dynamic adjustment resolves the contradiction by providing extensive help when needed for skill development while avoiding unnecessary complexity in standard gameplay.
Data Source
AI summary
The gaming system and method includes a game that can be played in a first game state or a second game state with the possibility of different awards for each game state. The first game state enables a player to play the game and receive a first award. The first award may be a predetermined award and not based on the outcome the game in first game state. In some embodiments, the first award is not based on how well a player played a game. The second game state enables the player to play the game and receive a second award based on the outcome of the game in the second game state. In some embodiments, the second game state enables the player to play the game and receive a second award based on how well the player played the game in the second game state.