Diagnostic Models for Procedural Bugs in Basic Mathematical Skills
Diagnostic Models for Procedural Bugs in Basic Mathematical Skills
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DOI：
10.1207/s15516709cog0202_4
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发表时间：
1978-04
期刊：
影响因子：
--
通讯作者：
J. Brown;R. Burton
中科院分区：
文献类型：
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作者：
J. Brown;R. Burton
一种新的诊断建模系统，用于自动合成学生基本数学技能中的错误概念或错误的深层结构模型，提供了一种解释学生为什么犯错误的机制，而不是简单地识别错误。本报告分为四个部分：第一部分提供了诊断模型必须处理的问题的示例。然后，它引入了程序性网络，作为表示技能基础知识的一般框架。设计这种表示法的挑战是找到一种便于发现特定学生对这种知识编码中存在的误解或错误的表示法。第二部分讨论了在教学系统中使用诊断模型所产生的一些教学问题。这一讨论是在一个基于计算机的辅导/游戏系统的背景下开发的，该系统旨在教学生和实习教师如何战略性地诊断错误，以及如何更好地理解算术技能的基本结构。第三部分描述了我们使用可执行网络作为工具来自动诊断学生行为、自动生成“诊断”测试以及判断给定考试的诊断质量。本部分讨论了该系统如何成功地从包含20,000个测试项目的数据库中诊断出1300名在校学生。最后一部分讨论了未来的研究方向。高级研究计划局、空军人力资源实验室、陆军行为和社会科学研究所以及海军人事研究和发展中心根据第#号合同，部分支持了作为本研究基础的诊断模型一般框架的开发。MDA903-76-C-0108。
A new diagnostic modeling system for automatically synthesizing a deep-structure model of a student's misconceptions or bugs in his basic mathematical skills provides a mechanism for explaining why a student is making a mistake as opposed to simply identifying the mistake. This report is divided into four sections: The first provides examples of the problems that must be handled by a diagnostic model. It then introduces procedural networks as a general framework for representing the knowledge underlying a skill. The challenge in designing this representation is to find one that facilitates the discovery of misconceptions or bugs existing in a particular student's encoding of this knowledge. The second section discusses some of the pedagogical issues that have emerged from the use of diagnostic models within an instructional system. This discussion is framed in the context of a computer-based tutoring/gaming system developed to teach students and student teachers how to diagnose bugs strategically as well as how to provide a better understanding of the underlying structure of arithmetic skills. The third section describes our uses of an executable network as a tool for automatically diagnosing student behavior, for automatically generating “diagnostic” tests, and for judging the diagnostic quality of a given exam. Included in this section is a discussion of the success of this system in diagnosing 1300 school students from a data base of 20,000 test items. The last section discusses future research directions. Development of the general framework of Diagnostic Models which underlies this research was supported, in part, by the Advanced Research Projects Agency, Air Force Human Resources Laboratory, Army Research Institute for Behavioral and Social Sciences, and Navy Personnel Research and Development Center under Contract No. MDA903-76-C-0108.