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Game programming projects are concrete and motivational for students, especially when used to teach more abstract concepts such as algebra. These projects must have open-ended elements to allow for creativity, but too much freedom makes it hard to reach specific learning outcomes. How many degrees of freedom do students need to make a game feel like one they genuinely designed? What kinds of personalization do they undertake of their games? And how do these factors correlate with their prior game-playing experience or with their identified gender? This paper studies these questions in the concrete setting of the Bootstrap:Algebra curriculum. In this curriculum, students are only given four parameters they can customize and only a few minutes in which to do so. Our study shows that despite this very limited personalization, students still feel a strong sense of ownership, originality, and pride in their creations. We also find that females find videogame creation just as satisfying as males, which contradicts some prior research but may also reflect the nature of games created in this curriculum and the opportunities it offers for self-expression. 

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.