Preface to the special issue on automated assessment of programming assignments
Preface to the special issue on automated assessment of programming assignments
复制标题
编程作业自动评估特刊前言
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
C. Higgins
中科院分区：
文献类型：
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作者：
Peter Brusilovsky;C. Higgins
计算机编程正在成为一项越来越受欢迎的活动，不仅对计算机科学专业的学生，而且对许多其他学科的学生。但是，用于编程教学的资金和其他资源在很大程度上没有跟上学习编程的学生人数的持续增长。学术机构面临的挑战是为学生提供更高质量的教学，同时尽量减少工作人员的额外工作量。虽然传统的教学方法可以通过视听手段和在线学习的进步得到加强，但在评估领域，问题仍然存在。基于计算机的评估（CBA），多年来已成为一个越来越重要的教学工具，可以帮助教育工作者解决这些问题。在过去的二十年里，教育工作者报告了使用自动评估工具来评估学生的编程课程的实际和教学效益。本期JERIC的目的是向更广泛的受众解释关于学生课程自动评估和其他类型的编程作业的前沿研究。它致力于全自动评估和部分学生程序评估的机器。我们不提供该领域的概述在这个介绍性的发言。Ala-Mutka最近的一项调查[Ala-Mutka 2005]、Douce等人在本期的评论[Douce et al. 2006]以及本期的其他几篇文章提供了一个全面的概述，并提供了对众多已知工作进行分类的各种方法。然而，为了介绍本期的文章，编辑们发现区分三类系统是有用的：（1）评估程序跟踪技能;（2）评估程序编写技能;（3）评估智能编程导师。第一组系统试图通过向学生展示一个程序并要求他们跟踪它来评估学生的编程语言语义知识。这类问题的答案来自于它的执行：打印了什么？数据结构中变量的最终状态是什么？自动评估学生答案的能力源于系统使用相同数据执行程序或算法并将该结果与学生输入的结果进行比较的能力。Brusilovsky和Sosnovsky [2006]在本期中报告的QuizPACK系统_
Programming computers is becoming an increasingly popular activity, not only for computer science students but across a large number of other disciplines. But funding and other resources for teaching programming have not, for the most part, kept pace with the continuous growth in the number of students studying programming. Academic institutions face the challenge of providing their students with better quality teaching while minimizing the amount of additional work for staff. While traditional teaching methods can be enhanced by audio/visual means and advances in online learning, in the area of assessment the problems continue to persist. Computer-based assessment (CBA), which over the years has become an increasingly important teaching tool, can help educators solve these problems. For the past twenty years, educators have reported on the practical and pedagogic benefits of using automated assessment tools to assess student coursework in programming. The purpose of this issue of JERIC is to explain cutting-edge research on the automated assessment of student programs, and other kinds of programming assignments, to a wider audience. It is devoted to both fully automated assessment and to partial student program assessment by machine. We do not provide an overview of the field in this introductory statement. A recent survey by Ala-Mutka [Ala-Mutka 2005], the review of Douce et al. in this issue [Douce et al. 2006], and several other articles in this issue provide a comprehensive overview and offer various ways to classify the multitude of known work. However, to introduce the articles in this issue, the editors found it useful to distinguish three categories of systems: (1) to assess program-tracing skills; (2) to assess program-writing skills; and (3) assess intelligent programming tutors. The first group of systems attempts to assess students’ knowledge of programming language semantics by presenting students with a program and asking them to trace it. The answer to this type of problem results from its execution: What was printed? What was the final state of the variables in the data structures? The ability to automatically evaluate student answers stems from the system’s ability to execute the program or the algorithm with the same data and compare that result with the one entered by the student. The QuizPACK system reported by Brusilovsky and Sosnovsky [2006] in this issue _________________________________________________________________________________________