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O’Brien, Zara (2021) Analysis of women in STEM: Technical Report. Undergraduate thesis, Dublin, National College of Ireland.
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Abstract
Women make up only 27% of the STEM (Science, Technology, Engineering, and Math) workforce as of 2019, despite the fact that employment in STEM has expanded by 79% since 1990. Understanding the variables that contribute to the lack of women in STEM fields is essential if more women are to be inspired to seek careers in the sector.
This study details the CRISP-DM methodology's knowledge acquisition approach. It outlines how the information was gathered and processed for analysis. The investigation aimed to glean information from a STEM-based survey, which questioned STEM professionals regarding the field's vulnerabilities. It detected trends and patterns in students who chose to study a STEM topic in their final year of secondary school by using a SEM (structural equation model).
The study also attempted to predict whether or not a student will choose a STEM topic in school. Many reasons, including a lack of support, role models, interest, and self-efficacy, have been identified as contributing to the absence of women in STEM. The article also includes recommendations for how to address these issues. The data was subjected to a variety of machine learning algorithms, with Multiple Logistic Regression proving to be the most effective.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Classes of Labour > Women and Work |
| Divisions: | School of Computing > Bachelor of Science (Honours) in Computing |
| Depositing User: | Clara Chan |
| Date Deposited: | 22 Sep 2021 10:29 |
| Last Modified: | 22 Sep 2021 10:29 |
| URI: | https://norma.ncirl.ie/id/eprint/5076 |
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