Undergraduate Research: The Lafayette Experience
Notice bibliographique
Résumé
Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Undergraduate Research: The Lafayette Experience Kristen L. Sanford Bernhardt, Mary J.S. Roth Lafayette College Introduction Lafayette College is an undergraduate institution with approximately 2200 students. On average, approximately 80 of those students are civil engineering majors; the Department of Civil and Environmental Engineering graduates anywhere from 12-25 students per class. The opportunity for students to conduct one-on-one research with a faculty member is a strength of the Lafayette College environment. Lafayette encourages undergraduate research in all disciplines through a variety of programs, including independent studies, honors theses, and paid research assistantships (called the EXCEL Scholars program). The Department of Civil and Environmental Engineering has been highly successful in involving students in research experiences through independent studies and as EXCEL scholars, and moderately successful at graduating students with honors theses. On average, approximately one quarter of the students in the department are involved in research with faculty in any given semester, and a higher percentage participate at some time during their Lafayette careers. There are many possible ways to define what constitutes a “successful” undergraduate research experience. As an institution, Lafayette College does not aim to send students specifically to industry or to graduate school; rather, the goal is to provide students with experiences that will enable them to make informed decisions about their future. We consider the experience of a student who discovers that he or she does not enjoy research to be as much a success as the student whose experience spurs an application to graduate school. A successful research experience also must satisfy faculty needs. Lafayette’s tenure and promotion requirements include scholarly work. With no graduate research assistants, faculty members often must rely on undergraduate researchers for assistance. Research products, such as papers and presentations, are quantifiable measures of research productivity, and these products can result from student research experiences. A research product not only helps faculty members, it gives students a specific goal and a sense of accomplishment, and it provides a distinguishing characteristic for the student’s resume or graduate school applications. The objective of this paper is to examine the undergraduate research experience in our department at our institution. We first describe in detail the types of experiences that are available to our students. We then summarize the last five years of student research projects conducted in the department. Based on this information and discussions with department faculty, we summarize the lessons we have gleaned from this study. Finally, we outline our plans both for increasing student involvement and for increasing the quality of the experiences. Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright © 2004, American Society for Engineering
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 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 | 0,011 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,012 | 0,004 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,154 | 0,042 |
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 ».