A Longitudinal Study of the Dimensions of Disciplinary Culture to Enhance Innovation and Retention among Engineering Students
Notice bibliographique
Résumé
The U.S. engineering educational system has been generally slow in developing pedagogies that successfully promote innovative behaviors. Although numerous sources recognize the growing scope and complexity of challenges that lie ahead in the 21st century, engineering is struggling to balance its goals between the high-risk pursuit of innovation and the traditional problem-solving approach of producing functional, reliable applications. In short, engineering needs more creativity and interdisciplinary fluency, but not at the expense of its discipline-specific problem-solving skills. At the same time, engineering programs continue to struggle with attracting and retaining members of underrepresented populations—whose diversity could greatly contribute to innovation. Interestingly, this lack of diversity is often attributed to cultural traits of the field—often characterized as masculine, individualistic and function-oriented. Notably, students in fields that emphasize functionality (e.g. engineering) rather than creativity (e.g. industrial design) express higher levels of uncertainty avoidance. Together, these cultural dimensions of engineering continue to limit innovative practices, such as interdisciplinary collaboration, design thinking, and diversity of perspectives. The purpose of this study is to investigate patterns of cultural traits in students across disciplines, with the goal of building an actionable theory of engineering culture that can support pedagogies of inclusive and collaborative innovation. Specifically, we are using Hofstede’s theory of dimensions of national culture to understand engineering disciplinary culture. We are using an instrument to evaluate the original four dimensions of national culture (power distance, uncertainty avoidance, individualism, masculinity) to see if the dimensions map to academic disciplines to explain how students develop skills to operate within and across disciplinary boundaries. Furthermore, we are exploring the relationships between these dimensions of disciplinary culture and student recruitment and retention, particularly for underrepresented groups. We are in the third year of a mixed methods study. During year 1, 1043 students from all the disciplines at one institution were surveyed. In year 2, 1199 undergraduate students across 6 institutions were surveyed, and 5 students in electrical and computer engineering were interviewed. During year 3, the survey will go out during the spring semester 2016, and 24 students will be interviewed. Quantitative results describe how undergraduate students in different disciplines understand their culture in terms of Hofstede’s dimensions. However, although we were able to confirm the validity of the instrument with the quantitative data collected, there have not been statistically significant differences between the majors studied, suggesting that the instrument used was to measure the dimensions of culture at the national level rather than at the academic level. In order to continue exploring whether Hofstede’s national cultures map to disciplinary cultures in universities, we are collecting qualitative data (informed by the quantitative results) to obtain in-depth information of how students understand and perceive their disciplines in terms of Hofstede’s dimensions. Results from our research will provide valuable information to understand disciplinary cultures in engineering majors, and contribute to better understanding how to improve engineering culture to make engineers more innovative, to make engineering classrooms more welcoming and inclusive, and to make better decisions regarding curriculum development in engineering.
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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 | 0,000 | 0,000 |
| 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 | 0,000 | 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.
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