Survey data on student expectations from teaching assistants in engineering education

Teaching Assistants (TAs) make important contributions to STEM teaching in
higher education. While TAs often play both peer and authority figure
roles, however, relatively little is known about exactly what students
expect from TAs.  To fill this gap, the first major goal of this
study was to comprehensively understand these expectations from a large
population of undergraduate engineering students. In addition, this study
sought to understand how these expectations vary with gender,
race/ethnicity, and country of origin within distinct time periods
associated with the recent COVID-19 pandemic (pre-COVID, during COVID, and
post COVID).  Student expectations were measured via a
short-answer survey question in a cross-sectional dataset at a single,
large institution comprised of sophomore to senior level students (n =
1,678) enrolled in engineering courses between 2016 and 2023. Thematic
analyses were used to analyze student expectations, and statistical,
quantitative techniques were used to identify demographic differences.
While no single majority theme emerged, many (42.9%) of students overall
thought that teaching practice was most important for TAs to emphasize,
while 37.6% believed teacher preparation to be most important. A smaller
but noteworthy percentage (7.61%) of students expected TAs to be caring
and hospitable. Significant differences emerged across time period,
race/ethnicity, and country of origin, but gender differences were not
significant. The results of this study indicate that students have a wide
range of expectations of TAs, that these expectations vary over time, and
that their expectations are largely consistent with cognitivism approaches
to teaching and learning. While the results of this study can directly
inform TA professional development and faculty guidance and supervision of
TAs, it is also important that both faculty and TAs introduce other
learning theories into their teaching (e.g., constructivist, humanistic,
connectivist) to further develop deep learning skills and better prepare
engineers for the workforce.