A qualitative assessment of barriers within the university learning environment and their influence on students’ participation in engineering education
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Notice bibliographique
Résumé
Abstract The field of engineering is essential for socio-economic development; however, it is characterised by low female representation. The objective of this study was to explore the challenges within the university learning environment that could affect the participation of women and men in engineering and propose recommendations. Six focus group discussions (FGDs) were held with undergraduate students from a Ghanaian university (i.e. one FGD each for male and female students in the second, third, and fourth years of study). The discussions, among others, elicited the challenges that students face during their studies, their coping strategies as well as some pointers for enhancing students’ experiences in the engineering learning environment. Data were analysed by employing content analysis with the aid of Atlas.ti software and then categorised into themes inspired by the three dimensions of learning environment. Barriers related to the physical learning environment were overcrowded lecture rooms and inadequate laboratory space and equipment. Barriers related to pedagogical learning environment were inadequate practical sessions, outmoded curriculum and poor teaching methods, and limited orientation for students. Barriers associated with the psychosocial learning environment included inadequate involvement of females in practical work, backlash and apathetic attitude when women become group leaders, silencing and intimidating female students in class, and limited female role models. These barriers combined with gender stereotypes exhibited by male students, laboratory technicians and lecturers intimidate female students, reduce their confidence levels and limit their exploratory abilities. We recommend sensitising and training lecturers and students to mainstream gender considerations in learning environments to make engineering gender-neutral. It is also critical for engineering faculties to develop and implement practical-oriented and gender-responsive curricula and pedagogies, standardise teaching methods, and explore e-learning options to compensate for the increasing number of students in enrolment. Universities must also devise intentional strategies for recruiting and retaining more female engineering lecturers and enhancing the quantity and quality of teaching and learning infrastructure.
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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 | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 découle