Assessing Bootstrap:Algebra Students on Scaffolded and Unscaffolded Word Problems

Emmanuel Schanzer, Kathi Fisler, Shriram Krishnamurthi

ACM Technical Symposium on Computer Science Education, 2018


Bootstrap:Algebra is a curricular module designed to integrate introductory computing into an algebra class; the module aims to help students improve on various essential learning outcomes from state and national algebra standards. In prior work, we published initial findings about student performance gains on algebra problems after taking Bootstrap. While the results were promising, the dataset was not large, and had students working on algebra problems that had been scaffolded with Bootstrap’s pedagogy. This paper reports on a more detailed study with (a) data from more than three times as many students, (b) analysis of performance changes in incorrect answers, (c) some problems in which the Bootstrap scaffolds have been removed, and (d) an IRT analysis across the elements of Bootstrap’s program-design pedagogy. Our results confirm that students improve on algebraic word problems after completing the module, even on unscaffolded problems. The nature of incorrect answers to symbolic-form questions also appears to improve after Bootstrap.



These papers may differ in formatting from the versions that appear in print. They are made available only to support the rapid dissemination of results; the printed versions, not these, should be considered definitive. The copyrights belong to their respective owners.