What is it about?
We had a large data set of open-response answers from questions where students predicted the output of code. The data came from three semesters worth of introductory computer science classes and includes over 4,000 students. We counted how often a given string of text appeared as an answer and found that some answers are extremely more common than others. We then examined only these popular wrong answers and reported what we found.
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Why is it important?
The question type we studied is powerful because it is both open-ended and possible to grade automatically. This work showed that we can use this data to better understand what is going on in the class with only a reasonable amount of effort, despite the diversity of student responses.
Perspectives
I hope that this paper shows that using mixed methods is possible and a viable thing to do not only for research but also for teaching practices.
Kristin Stephens-Martinez
Duke University
Read the Original
This page is a summary of: Taking Advantage of Scale by Analyzing Frequent Constructed-Response, Code Tracing Wrong Answers, August 2017, ACM (Association for Computing Machinery),
DOI: 10.1145/3105726.3106188.
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