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Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation

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...

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Detalles Bibliográficos
Autores principales: Turnbull, Steven Martin, O’Neale, Dion R. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931889/
https://www.ncbi.nlm.nih.gov/pubmed/33693423
http://dx.doi.org/10.3389/fdata.2020.599016
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author Turnbull, Steven Martin
O’Neale, Dion R. J.
author_facet Turnbull, Steven Martin
O’Neale, Dion R. J.
author_sort Turnbull, Steven Martin
collection PubMed
description 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 in life science standards, they were less well represented in physics, calculus, and vocational (e.g., agriculture, practical technology) standards. Our results also show that the enrollment patterns of Asian students had lower entropy, an observation that may be explained by increased enrolments in key science and mathematics standards. Through further investigation of differences in entropy across ethnic group and high school SES, we find that ethnic group differences in entropy are moderated by high school SES, such that sub-populations at higher SES schools had lower entropy. We also discuss these findings in the context of the New Zealand education system and policy changes that occurred between 2010 and 2016.
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spelling pubmed-79318892021-03-09 Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation Turnbull, Steven Martin O’Neale, Dion R. J. Front Big Data Big Data 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 in life science standards, they were less well represented in physics, calculus, and vocational (e.g., agriculture, practical technology) standards. Our results also show that the enrollment patterns of Asian students had lower entropy, an observation that may be explained by increased enrolments in key science and mathematics standards. Through further investigation of differences in entropy across ethnic group and high school SES, we find that ethnic group differences in entropy are moderated by high school SES, such that sub-populations at higher SES schools had lower entropy. We also discuss these findings in the context of the New Zealand education system and policy changes that occurred between 2010 and 2016. Frontiers Media S.A. 2021-01-27 /pmc/articles/PMC7931889/ /pubmed/33693423 http://dx.doi.org/10.3389/fdata.2020.599016 Text en Copyright © 2021 Turnbull and O'Neale. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Turnbull, Steven Martin
O’Neale, Dion R. J.
Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title_full Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title_fullStr Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title_full_unstemmed Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title_short Entropy of Co-Enrolment Networks Reveal Disparities in High School STEM Participation
title_sort entropy of co-enrolment networks reveal disparities in high school stem participation
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931889/
https://www.ncbi.nlm.nih.gov/pubmed/33693423
http://dx.doi.org/10.3389/fdata.2020.599016
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