Automatically Grading Programming Assignments with Web-CAT

SIGCSE 2009 Workshop Companion Wiki

This page contains the companion materials from the SIGCSE 2009 Workshop: Automatically Grading Programming Assignments with Web-CAT, presented by Stephen Edwards and Manuel Pérez-Quiñones from Virginia Tech's Department of Computer Science.

This wiki page and its children contains electronic copies of the workshop materials, together with links to installable versions of all required software.

Workshop Abstract

This workshop introduces participants to using Web-CAT, an open-source automated grading system. Web-CAT is customizable and extensible, allowing it to support a wide variety of programming languages and assessment strategies. Web-CAT is most well-known as the system that "grades students on how well they test their own code," with experimental evidence that it offers greater learning benefits than more traditional output-comparison grading. Participants will learn how to prepare reference tests, set up assignments, manage multiple sections, and allow graders to manually grade for design. Go home ready to start using it in your own classes! Prior exposure to a unit testing framework, such as JUnit, is recommended but not required. Laptop optional.

Workshop Contents

Workshop notes (presentation): Web-CAT-workshop-SIGCSE09.pdf

The SIGCSE 2009 Web-CAT workshop features live demonstration walkthroughs of how to use Web-CAT, from the very first step of creating your first course offering, through the steps required to create assignments, submit work, and grade work. As a resource to workshop participants--and those who could not attend the workshop--we also provide here both the instructions and the materials needed to walk through these steps yourself using a demonstration account on our Web-CAT server at Virginia Tech. You can request a guest account by e-mail and then follow the instructions below.

Hands-on Versions of the Workshop Demonstrations

Sponsorship

We gratefully acknowledge the support provided to this work by our sponsors. This work is sponsored in part by the National Science Foundation under Grant Nos. DUE-0618663 and DUE-0633594. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


Sigcse2009Workshop