Summer Research Internship Curriculum to Promote Self-Efficacy, Researcher Identity, and Peer-to-Peer Learning: Retrospective Cohort Study
Notice bibliographique
Résumé
Background: Common barriers to students' persistence in research include experiencing feelings of exclusion and a lack of belonging, difficulties developing a robust researcher identity, perceptions of racial and social stigma directed toward them, and perceived gaps in research skills, which are particularly pronounced among trainees from groups traditionally underrepresented in research. To address these known barriers, summer research programs have been shown to increase the participation and retention of undergraduate students in research. However, previous programs have focused predominantly on technical knowledge and skills, without integrating an academic enrichment curriculum that promotes professional development by improving students' academic and research communication skills. Objective: This retrospective pre-then-post study aimed to evaluate changes in self-reported ratings of research abilities among a cohort of undergraduate students who participated in a summer research program. Methods: The Human BioMolecular Atlas Program (HuBMAP) piloted the implementation of a web-based academic enrichment curriculum for the Summer 2023 Research Internship cohort, which was comprised of students from groups underrepresented in biomedical artificial intelligence research. HuBMAP, a 400-member research consortium funded by the Common Fund at the National Institutes of Health, offered a 10-week summer research internship that included an academic enrichment curriculum delivered synchronously via the web to all students across multiple sites. The curriculum is intended to support intern self-efficacy, researcher identity development, and peer-to-peer learning. At the end of the internship, students were invited to participate in a web-based survey in which they were asked to rate their academic and research abilities before the internship and as a result of the internship using a modified Entering Research Learning Assessment instrument. Wilcoxon matched-pairs signed rank test was performed to assess the difference in the mean scores per respondent before and after participating in the internship. Results: A total of 14 of the 22 undergraduate students who participated in the internship responded to the survey. The results of the retrospective pre-then-post survey indicated that there was a significant increase in students' self-rated research abilities, evidenced by a significant improvement in the mean scores of the respondents when comparing reported skills self-assessment before and after the internship (improvement: median 1.09, IQR 0.88-1.65; W=52.5, P<.001). After participating in the HuBMAP web-based academic enrichment curriculum, students' self-reported research abilities, including their confidence, their communication and collaboration skills, their self-efficacy in research, and their abilities to set research career goals, increased. Conclusions: Summer internship programs can incorporate an academic enrichment curriculum with small-group peer learning in addition to a laboratory-based experience to facilitate increased student engagement, self-efficacy, and a sense of belonging in the research community. Future research should investigate the impact of academic enrichment curricula and peer mentoring on the long-term retention of students in biomedical research careers, particularly retention of students underrepresented in biomedical fields.
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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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».