Generation quiz with genetic algorithm based on bloom's taxonomy classification in serious game based virtual environments

Rasim, A. Langi, Y. Rosmansyah, Munir
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引用次数: 7

Abstract

Learning with seorius game based virtual environments provide immersive and motivation. One aspect of learning is evaluation. But evaluation provides anxiety on the learner, as question that is too difficult. In this paper will describe how to generate questions in evaluation(quiz) based on bloom taxonomy with composition 25:50:25 for the types of questions C1, C2, and C3. The question generation used genetic algorithms and implemented in the virtual learning environment (VLE) through SLOODLE for 5th grades math course. System testing used compare genetic algorithm (GA) with random method. The result is the question composition of the generation of GA better than the generation of random method.
基于bloom分类法的虚拟严肃游戏环境下的遗传算法生成测验
在严肃的基于游戏的虚拟环境中学习提供了沉浸感和动力。学习的一个方面是评价。但是评价给学习者带来了焦虑,因为问题太难了。本文将描述如何基于bloom分类法(composition 25:50:25)对问题C1、C2和C3类型生成评估(quiz)中的问题。问题生成采用遗传算法,并通过SLOODLE在虚拟学习环境(VLE)中实现。系统测试采用遗传算法与随机方法进行比较。结果表明,遗传算法生成的问题组成优于随机生成方法。
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