自适应编程辅导系统中用于建模的一组学生特征

K. Chrysafiadi, M. Virvou
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引用次数: 4

摘要

本文提出了在自适应和/或个性化编程辅导系统中必须考虑的学生的一系列特征。这一组被称为k.e.m.c,包括:知识、错误、动机和认知状态。它允许系统识别潜在编程学习者的各种背景,他们的误解,需求和学习速度。通过不同的学生建模技术的组合:覆盖、刻板印象、模糊逻辑和OCC认知理论来完成k.e.m.c.的建模。这种方法的好处是,特定的学生模型代表了真正的编程学生的复杂维度的足够大的一部分。因此,它可以作为提高学习过程质量的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
K.E.M.Cs: A set of student's characteristics for modeling in adaptive programming tutoring systems
In this paper a set of student's characteristics that have to be considered in an adaptive and/or personalized programming tutoring system is presented. This set is called K.E.M.Cs and includes: knowledge, errors, motivation and cognitive states. It allows the system to identify the variety of backgrounds of prospective learners of programming, their misconceptions, needs and learning pace. The modeling of K.E.M.C.s is performed through a combination of different student modeling techniques: overlay, stereotypes, fuzzy logic and OCC cognitive theory. The gain of this approach is that the particular student model represents a sufficiently large part of the complex dimensions of a real student of programming. Therefore, it can be the base for the improvement of the quality of the learning process.
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