Using game-based learning in teaching CS algorithms

I. Hatzilygeroudis, F. Grivokostopoulou, I. Perikos
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引用次数: 5

Abstract

Artificial Intelligence curriculum comprises some difficult concepts for a student to grasp and traditional teaching methods are proven to be ineffective and unable to motivate them. A basic AI concept is Constraint Satisfaction (CS), which is acknowledged by most tutors to be a hard domain for teachers to teach and student to understand. To solve a CS problem (CSP), a CS algorithm should be used. In this paper we present a game based approach, to be used as an assistant tool in an AI course, to assist students in understanding CS algorithms in an easy, interactive and motivating way. The game is based on a classical CSP, the map-coloring problem. Preliminary evaluation results are quite encouraging.
在CS算法教学中运用基于游戏的学习
人工智能课程包含一些学生难以掌握的概念,传统的教学方法被证明是无效的,无法激励学生。人工智能的一个基本概念是约束满足(CS),大多数导师都认为这是一个教师难以教授、学生难以理解的领域。为了解决CS问题(CSP),必须使用CS算法。在本文中,我们提出了一种基于游戏的方法,作为人工智能课程的辅助工具,以一种简单、互动和激励的方式帮助学生理解CS算法。这款游戏基于经典的CSP,即地图着色问题。初步评价结果相当令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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