Opening Up Contested Spaces: Interdisciplinary Writing at an HBCU
Notice bibliographique
Résumé
Inequalities in academic writing are not uncommon in higher education and become more complex when we look at the landscape of historically black colleges and universities (HBCUs), which serve a large number of first-generation Black students. HBCUs serve minority students and provide them a cultural connection that they often do not achieve at predominantly white institutions. Such first-generation students face a range of challenges and graduate at lower rates than other student. In terms of academic writing, such students often struggle to develop an academic identity and voice. At Johnson C. Smith University, an HBCU in the heart of Charlotte, North Carolina, all students, regardless of major, are required to complete a senior investigative paper. Many students struggle with this graduation requirement for a variety of reasons, ranging from inexperience with academic writing, lack of interest in the topic, and poor writing mechanics skills A goal specifically in the Interdisciplinary Studies Department is to have students develop a topic they find interesting and engaging. Many IDS students choose topics that address inequalities they have encountered and endured in their life or ones that are specific to their demographic (age, race, gender, sexual orientation, etc). When students are able to research and write about topics they are passionate about, their writing shows marked improvement as they develop a writing voice. As Bean (2011) notes, sometimes it is beneficial to set aside the formal academic writing expectations and focus on the content and context of a paper. This provides students with the message that what they are researching is valuable and they gain confidence in their research skills and thus their critical thinking skills. Bean also notes that when we focus on content rather than sentence-level correctness, the result is often a well-written paper, or one that is improved from the previous drafts. This article focuses on specific lessons learned from our experience working with HBCU seniors and how to apply the practices of content feedback to promote academic writing to help close the gap of academic inequality that many students experience.
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 | 0,002 | 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 | 0,004 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».