Friday 25th March, 2011
9:00am to 9:50am
We describe our experience using an on-line automatic grading system for a course on technical computing and problem solving to over 900 freshman engineering students. What started out as a necessity has turned into an essential learning tool, providing students with ways to check reading comprehension and conceptual understanding, and to reinforce recall. Random generation with a question template allows instructors to give each student their unique version of a problem without increasing the staff effort in grading. Students spend ten hours per term in labs with face-to-face contact with instructional staff. An on-line pre-lab quiz encourages students to prepare for the lab. A post-lab on-line quiz/assignment solidifies comprehension and recall and provides further practice with computing and problem-solving. We encourage student use of quiz feedback to improve their work right when they are making the most effort to work with our problems. We allow multiple attempts for most questions. Peer-led and staff tutoring (face-to-face and online) provides "just in time" help for post-lab quizzes. This approach to assessment is a scalable instructional technique that has 24/7 availability and immediate feedback. Most staff time is spent interacting with students to help them master content, rather than working in a back room grading. It facilitates collection of statistics on all regularly graded materials, allowing instructors to monitor student learning down to individual questions. This can be used to give individualized remediation and indicate particular areas where the class is having difficulty. The data, over time, also provides information for learning patterns and retention. The costs of this approach is that IT expertise is needed to keep services running with high availability and reliability. Software engineering discipline is needed to construct robust questions and grading procedures. Finally, there are pedagogical challenges working around the limitations of current auto-grading technology.
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