MS Presentation: Jean Salac

Why Access isn’t Enough: An Analysis of
Elementary-Age Students’ Computational Thinking Performance through an
Equity Lens

With the rise of pre-university Computer Science (CS) and
Computational Thinking (CT) instruction worldwide, it is crucial that
such instruction is effective for wide range of learners. While great
strides have been made in giving access to students through
large-scale school district-level efforts, inequities in learning
outcomes may result from tools, curricula, and/or teaching that are
appropriate for only a subset of the population. In this paper, we
present an analysis of learning outcomes from a large school
district's elementary CT curriculum through an equity lens—one of
the few studies with this young age group in a formal school setting.
While many students were exposed to CS/CT from an implementation of
this scale, we found troubling differences across school performance
levels. Our analysis also revealed that reading comprehension and math
proficiency were predictive of performance in most CT concepts to
varying degrees, and that there were wide gaps between students who
were performing below grade level and those who were performing at or
above grade level in those subjects. These disparities point to the
need for curricular changes and learning strategies to better support
students who struggle with reading and math. More insidiously, we
found gender and under-represented minority identity to be the most
predictive of performance in a small subset of assessment questions.
Our results underscore the need for improvement in the way computing
is taught to achieve the equity desired from the wider spread of CS/CT
instruction.