An Equity-Minded Assessment of Belonging Among Computing Students at Cal Poly
Notice bibliographique
Résumé
Creating a Computer Science and Software Engineering Department that supports students with diverse identities and backgrounds is essential to creating a computing workforce that reflects the world at large. Inspired by the work of Metcalf et al.'s survey conducted at the University of Illinois, we use the same methods to examine the state of our computing department with respect to issues of inclusive climate and student sense of belonging, which have been shown to be important for retention in STEM fields. We use the four areas that contribute to belonging based on the work of Rainey et al. along with a fifth category of learning environment in order to assess our students' sense of belonging. This paper's main focus is based on results from two surveys of Cal Poly Students conducted exactly one year apart (2019: n=154, 2020: n=122). Both surveys were sent to all computing majors in Spring quarter, the last quarter of the regular academic year. We found that 58-68\% of students felt they were not typical computer scientists, which mirrors the results of the survey conducted at the University of Illinois, indicating that the lack of belonging is perhaps a ubiquitous problem within the field of computing. Other salient results include identifying the presence of statistically significant differences for some groups based on gender and race & ethnicity. These differences were found when looking at students' senses of their science identity and learning environment. We also found that women had a significantly greater chance of having strong interpersonal relationships within computing. The survey results are augmented by a survey of first-quarter freshmen in Fall 2019 (n=44) and student interviews conducted in Spring 2021 (n=15). We hope that the addition of these results explain and expand upon our main results and add insight as to how the student experience can evolve from a student's first quarter onward. These differences shine an important light on some positive trends as well as several concerning differences to be examined in our quest to create a diverse and equitable department.
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 | 0,001 | 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 | 0,001 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| 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 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 ».