A Review of Influencing Factors for Selection of Engineering Pathway for Women – A Case Study of Females Studying Engineering at Waikato Institute of Technology (Wintec), New Zealand
Notice bibliographique
Résumé
Females are underrepresented in engineering cohorts in New Zealand. The lack of female participation in engineering fields at the tertiary education level has been a barrier for diversity and equality in both the industry and academic professions. A recent study by Docherty et al. [11] noted girls coming to engineering at Canterbury University, New Zealand are more likely to be from a single sex school and this phenomenon can be due to cultural reasons. They identified that future work is needed to look at the cultural changes in New Zealand which could potentially mitigate the gender bias.However, we first need to identify a range of contributing factors (including cultural issues) for the lack of diversity in engineering schools in New Zealand. By identifying these factors, we can then propose and implement necessary remediation actions to address the lack of female participation in engineering. Common influencing factors for female participation in STEM and selection of engineering pathways were found during a review of literature and included parental and teacher influences, self-efficacy, perception and attitude, gender stereotypes, and peer and media influences. We believe that New Zealand context in terms of how it influences female study and career pathway to engineering has not been well studied and documented to date. The objective of this research is to identify the main factors and cultural issues that contribute to low female participation in engineering studies in New Zealand. We carried out individual and focus group interviews on both domestic and international female students at Wintec enrolled in the Diploma, Bachelor of Engineering Technology and Graduate Diploma programmes in Civil Engineering. The interviews helped us to understand our students’ perspectives around the factors that influenced their study decisions. We used the collected data to identify patterns and generate themes. n the New Zealand context, we found, barriers to selection of engineering pathway for females include the school system; lack of career and subject choice guidance available to students at school, lack of promotion of the profession, and society’s perception of engineers as being masculine - “a tradie working in a workshop”. For our international students’ participants, it appears that the school system in their country directed them (regardless of gender) to maths and engineering study pathways if they showed talent in these areas and engineering is a highly regarded profession.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».