Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
Steven Martin Turnbull, Dion R.J. O'Neale

TL;DR
This study uses network analysis and entropy measures on New Zealand high school STEM co-enrolment data to reveal disparities in participation across sex, ethnicity, and socio-economic status, highlighting structural differences and temporal changes.
Contribution
It introduces a novel entropy-based measure to analyze co-enrolment networks and uncovers disparities in STEM participation among different demographic groups in New Zealand high schools.
Findings
Female students more enrolled in life sciences.
Higher entropy in Maori and Pacific students' enrolment patterns.
Disparities moderated by socio-economic status.
Abstract
The current study uses a network analysis approach to explore the STEM pathways that students take through their final year of high school in Aotearoa New Zealand. By accessing individual-level microdata from New Zealand's Integrated Data Infrastructure, we are able to create a co-enrolment network comprised of all STEM assessment standards taken by students in New Zealand between 2010 and 2016. We explore the structure of this co-enrolment network though use of community detection and a novel measure of entropy. We then investigate how network structure differs across sub-populations based on students' sex, ethnicity, and the socio-economic-status (SES) of the high school they attended. Results show the structure of the STEM co-enrolment network differs across these sub-populations, and also changes over time. We find that, while female students were more likely to have been enrolled…
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