Evaluating Computer-Aided Design Software as a Barrier to Women’s Engagement in Engineering: A Focused Literature Review
Notice bibliographique
Résumé
Abstract To tackle today's toughest problems, like climate change and the threat of global pandemics, design teams will need to deliver not only software solutions, but also innovative hardware products, sometimes called "tough-tech" or "hard-tech." Computer-Aided Design (CAD) is a key tool for these design teams to leverage in order to reach creative, innovative, hard-tech solutions for society's most pressing issues. Given CAD's importance in design, it is positioned to be a key enabler, or barrier, to increasing diversity in design teams. Statistics on the representation of women in CAD-reliant engineering fields, such as mechanical engineering, show that the numbers remain much below the overall female representation in engineering, and far below gender parity. Differences in confidence and ability level with CAD software are factors that may explain why this disparity exists, and so a focus on increasing accessibility of this tool provides an opportunity to increase female and non-binary representation in design teams. In this paper, we conduct a focused literature review to provide a comprehensive understanding of what factors position CAD as a barrier to women's engagement in engineering. The primary finding of this literature review is, in fact, the lack of literature; a deep body of knowledge exists to understand Women in Engineering and gender barriers in the profession more broadly, and in parallel, a rich literature on considerations for designing effective and efficient CAD tools and training exists. Yet we see a distinct lack of literature with a primary focus on the intersection of gender considerations in CAD. Based on the limited literature we did discover, we identify several potential barriers to gender diversity in CAD-reliant engineering fields: gender bias in CAD training, lack of representation of women in CAD communities, gender disparity in spatial reasoning skills, and differences in self-efficacy levels. With knowledge of these barriers, we then propose two strategic approaches for leveraging CAD as an avenue to increase gender diversity in mechanical design, which incorporate course design, outreach activities, and general considerations for engineering. These preliminary recommendations can be utilized by educators to support women and non-binary students towards the goal of creating more diverse design teams in undergraduate studies and beyond, ultimately leading to the innovative and creative hard-tech solutions needed to solve society's biggest problems. Importantly, we aim for this paper to act as a motivator to conduct further research in the area of gender considerations in CAD tools and trainings to better understand the actual barriers that women and non-binary individuals face in this field.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».