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Enregistrement W2020473115 · doi:10.1126/science.298.5594.747b

Reforming Undergrad Biology Curriculum

2002· letter· en· W2020473115 sur OpenAlexaff
Stephen M. Smith

Notice bibliographique

RevueScience · 2002
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetics, Bioinformatics, and Biomedical Research
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésCurriculumMedical educationPsychologyMedicinePedagogy

Résumé

récupéré en direct d'OpenAlex

In his article on the new National Research Council (NRC) report on needed reforms in undergraduate biology education, Erik Stokstad (“Biology departments urged to bone up,” News of the Week, 13 Sept., p. [1789][1]) mentions some of the obstacles to effective curriculum reform—the immense inertia of the faculty and their reluctance to give up “their” subject. One of the primary drivers of these impediments was identified in the Editorial by Timothy Goldsmith in the same issue (“Why is a liberal education so elusive?”, 13 Sept., p. [1769][2]): Faculty are usually reluctant to teach outside their areas of expertise. From the perspective of curriculum reform, this combination can be deadly. It also leads to a curriculum whose composition is stochastic rather than planned, as courses are added or dropped as faculty arrive and leave. But at least for the first 2 or 3 years of undergraduate education, most biology faculty ought to be able to teach effectively in several broad areas—why do we insist that an upper-year high school teacher cover all areas but that only 1 or 2 years later, students must be taught in a specialist fashion? The solution is obvious but very challenging: design a curriculum around goals rather than content and involve the faculty in teaching fundamental, cross-disciplinary courses and courses outside their area of expertise. This could be enormously stimulating! For many years in a biology department, I taught biostatistics, a course whose content cut aggressively across all discipline areas. The freedom from parochial, specialty-driven course content and the sheer joy of teaching something that was fundamentally and enduringly important enlivened and invigorated my teaching. A curriculum designed on goals and cross-disciplinary content could be a lot slimmer than the obese, fact-filled, overlapping and often repetitive courses that constitute the typical biology curriculum. Such a lean curriculum would free up the time needed to involve undergraduates in real, meaningful research activity—a real benefit to both students and faculty. # {#article-title-2} It is encouraging to learn that biology faculty recognize that “undergraduates [need] a better appreciation of the connections between biology and the physical sciences” (“Biology departments urged to bone up,” E. Stokstad, News of the Week, 13 Sept., p. [1789][1]) and that steps are being taken to improve the situation. Let me suggest a method established 30 years ago at the University of California, Irvine, that required two luncheon meetings to implement: one with David Brandt (chemistry) and myself (biology) and the other between William Parker (physics) and myself. I asked these researchers and teachers to tell me what they teach in their beginning chemistry and physics courses: the gas laws, pH, oxidation and reduction, and kinetics and thermodynamics. I then made it a point in my beginning cell biology course to correlate those subjects with my lectures on osmotic pressure; colligative properties and determining the molecular weight of proteins; the Henderson-Hasselbach principles of buffers; electron transfer reactions in the mitochondria; Michaelis-Menton enzyme kinetics; and the production and utilization of energy in metabolism. As a result, the students grasped these concepts of cell biology more easily because they had already learned the basic chemistry and physics involved. They also recognized that chemistry and physics were necessary for a deeper understanding of biology and that those courses were not just requirements to take and then forget. And the lunches were good, too. [1]: /lookup/doi/10.1126/science.297.5588.1789a [2]: /lookup/doi/10.1126/science.297.5588.1769

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,066
Score d'incertitude au seuil0,827

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,002
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
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 Opus0,020
Tête enseignante GPT0,298
Écart entre enseignants0,278 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations3
Publié2002
Routes d'admission1
Résumé présentoui

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