Multiplayer Board Game Strategies in the Introductory CS Curriculum

CS 入门课程中的多人棋盘游戏策略

• 批准号: 1044721
• 负责人: Ivona Bezakova
• 金额: $ 19.87万
• 依托单位: Rochester Institute of Tech
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-15 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1044721&HistoricalAwards=false
• 关键词: Multiplayer; Board; Game; Strategies; Introductory

Research has demonstrated that learning to program in context, especially a context that students are familiar with, increases student motivation. This project explores the context of traditional board games. Unlike modern computer games, board games are inherently discrete. The board has a fixed number of allowed positions for the game pieces and each player performs a mental search through a finite number of possible moves to decide the next action. Designing an automated player strategy for a board game provides a natural context for basic data structures and search algorithms covered in CS 1 and CS 2.For this project, researchers are developing software scaffolding to allow students to implement computer-based versions of actual board games. The game engines are responsible for the graphical user interface, rule enforcement and round-robin calling of the individual player strategies. Students design and implement player strategies to compete with a basic strategy provided by the instructor or more advanced strategies provided by other students. Three game engines are being developed in both Java and Python programming languages. Collaborations include a research university, a liberal arts college and an institute of technology. At least four hundred students are expected to use the materials during the project. Use beyond the project lifetime is expected because materials will be available on the Web and workshops are provided in the final project year to help faculty at other institutions adopt the materials. Project goals including student motivation and performance are evaluated by an evaluation team including three external experts.

研究表明，在上下文中学习编程，尤其是在学生熟悉的上下文中，可以提高学生的积极性。 该项目探讨了传统棋盘游戏的背景。 与现代电脑游戏不同，棋盘游戏本质上是离散的。 棋盘上有固定数量的游戏棋子位置，每个玩家都会通过有限数量的可能动作进行心理搜索，以决定下一步行动。 为棋盘游戏设计自动玩家策略为 CS 1 和 CS 2 中涵盖的基本数据结构和搜索算法提供了自然的背景。对于该项目，研究人员正在开发软件支架，以允许学生实现实际棋盘游戏的基于计算机的版本。 游戏引擎负责图形用户界面、规则执行和单个玩家策略的循环调用。 学生设计并实施玩家策略，以与教师提供的基本策略或其他学生提供的更高级策略进行竞争。 正在使用 Java 和 Python 编程语言开发三个游戏引擎。 合作机构包括一所研究型大学、一所文理学院和一所技术学院。预计至少有四百名学生在项目期间使用这些材料。预计会在项目生命周期之外使用，因为材料将在网上提供，并且在项目的最后一年提供研讨会以帮助其他机构的教师采用这些材料。 包括学生动机和表现在内的项目目标由由三名外部专家组成的评估小组进行评估。