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Problem selection of program tracing tasks in an intelligent tutoring system and visual programming environment.

机译：在智能辅导系统和可视化编程环境中选择程序跟踪任务的问题。

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摘要

Intelligent tutoring systems (ITSs) have been shown to be an effective supplementary teaching tool or aid for many domains. Applying ITSs in open-ended domains such as computer programming is especially challenging, most notably when trying to assist with the process of programming itself. Existing ITSs for programming focus on a very limited set of problems and concepts and are only useful early in an introductory CS course and a few limited places afterward. Visual programming environments are another tool that have been used in introductory CS courses to help students learn basic concepts. The key idea behind my work is the recognition of the importance of students' ability to read, understand, and trace code in order to write programs successfully. A broader goal of my work is to show that an ITS based on a visual programming environment can be used to support students throughout an entire introductory CS course, without being severely constrained and limited to a small number of concepts and to low-level, simple tasks. In my system, called RUR-ITS, students are given a program and are asked to predict the robot's behavior when running this program in a given environment. RUR-ITS allows each problem to be assigned a difficulty level and multiple concepts that it involves within the conceptual model. RUR-ITS can then use a problem selection algorithm to choose a problem that is most able to help the student master the concepts that they have not yet mastered.
机译：智能辅导系统（ITS）已被证明是许多领域的有效补充教学工具或帮助。在开放式领域（例如计算机编程）中应用ITS尤其具有挑战性，尤其是在尝试协助编程本身的过程时。现有的用于编程的ITS集中在一组非常有限的问题和概念上，并且仅在CS入门课程的早期有用，而在随后的几个有限位置才有用。视觉编程环境是CS入门课程中使用的另一种工具，可以帮助学生学习基本概念。我的工作背后的关键思想是认识到学生阅读，理解和跟踪代码以成功编写程序的能力的重要性。我工作的一个更广泛的目标是表明，基于视觉编程环境的ITS可用于在整个CS入门课程中为学生提供支持，而不会受到严格的限制，并且只限于少量概念和低层次，简单的任务。在我称为RUR-ITS的系统中，为学生提供了一个程序，并要求他们在给定环境中运行该程序时预测机器人的行为。 RUR-ITS允许为每个问题分配一个难度级别以及它涉及的概念模型中的多个概念。然后，RUR-ITS可以使用问题选择算法来选择最能帮助学生掌握他们尚未掌握的概念的问题。

著录项

  • 作者

    Walser, David John.;

  • 作者单位

    University of Maryland, Baltimore County.;

  • 授予单位 University of Maryland, Baltimore County.;
  • 学科 Education Technology of.;Computer Science.;Artificial Intelligence.
  • 学位 M.S.
  • 年度 2011
  • 页码 108 p.
  • 总页数 108
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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