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Enregistrement W2584357700 · doi:10.18260/1-2--6049

An Experimental Program To Enhance Retention Of At Risk Freshmen

2020· article· en· W2584357700 sur OpenAlexaboutno aff
Joan Burtner, Benjamin S. Kelley, Allen F. Grum

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Pedagogy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAttritionMathematics educationQuarter (Canadian coin)Engineering educationSession (web analytics)Academic yearScience and engineeringPsychologyMathematicsComputer scienceMedical educationEngineeringMedicineEngineering management

Résumé

récupéré en direct d'OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract . — Session 2653 ..-. -- An Experimental Program to Enhance Retention of At-Risk Freshmen Benjamin S. Kelley, Joan A. Burtner, and Allen F. Grum Mercer University School of Engineering, Macon, Georgia INTRODUCTION In the Fall of 1992, the Mercer University School of Engineering implemented an experimental program entitled Applications in Math and Science (AIMS). This program targeted marginally-qualified and thus at-risk entering engineering freshmen. The goals of the program were to 1) increase the rate of retention of this group of students from their freshman to their sophomore year and 2) enhance their performance in introductory science and mathematics courses. The year-long program consisted of two parts: the Fall Quarter applications courses in math and science, and the Winter and Spring Quarter follow-up lab courses designed to provide academic support for the students while they were enrolled in regular Chemistry and Calculus courses, Program success was measured in terms of satisfactory performance in Calculus and Chemistry courses as well as persistence in the School of Engineering at the beginning of the student’s second year in college. Motivation for an Intervention Strategy Approximately one-third of all of the undergraduate students who enrolled at Mercer for the 1990 Fall Quarter were no longer enrolled in the Fall of 1991. For the School of Engineering, the attrition rate was even higher. Almost half of the 1990 freshman engineering class did not return to the Engineering School for their sophomore year. These statistics clearly indicated that there was a need for some kind of intervention. In addition to the concern about low rates of retention, the School of Engineering had a variety of other reasons for wanting to implement this experimental program. The primary motivating factors included several that may be somewhat unique to schools like Mercer. First, the School of Engineering has a primary mission of quality undergraduate education and teaching. This philosophy of quality education and teaching led us to examine the possible causes for the lack of persistence of our least-qualified entering freshmen. Second, because Mercer is a small private school, by the time the student arrives on campus, the university has already made a substantial investment of time and money in the student. Finally, because Mercer is a moderately selective school, our freshmen engineering students are academically qualified and expect to succeed in an engineering curriculum. The Importance of the Freshman Year In terms of retention, the freshman year appears to be the most critical. Various sources indicate that the freshman-to-sophomore attrition rate for four year colleges is approximately 30%. 1JZ3 In fact, almost 20% of the freshmen leave before the end of their first term. Many of the students decide to leave within the first six weeks of classes. Because of the importance of the first year, the School of Engineering decided to design a program that focused on at-risk freshmen engineering students. ---- .- ?@xij 1996 ASEE Annual Conference Proceedings ‘.JyyHll’3

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,517

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,322
Écart entre enseignants0,303 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2020
Routes d'admission1
Résumé présentoui

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