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Enregistrement W2113658554 · doi:10.1002/bmb.2004.494032019995

Response to G. R. Parslow “listen to the message” [<i>biochemistry and molecular biology education</i> 31, 269 (2003)]

2004· article· en· W2113658554 sur OpenAlexaboutno aff
EJ Wood

Notice bibliographique

RevueBiochemistry and Molecular Biology Education · 2004
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueGenetics, Bioinformatics, and Biomedical Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEnthusiasmReading (process)Tone (literature)WelshPsychologyPoint (geometry)Mathematics educationLinguisticsSocial psychologyPhilosophy

Résumé

récupéré en direct d'OpenAlex

Graham Parslow's commentary in the previous issue of Biochemistry and Molecular Biology Education [1] reminded me about three points relating to the use of voice, one trivial, the other two important in our teaching. First the trivial point, that emotion and tone of voice are important when we lecture. This point arises because I was reminded that when my children were young I was often faced with the task of reading them their bedtime story. The same story was demanded time after time, and the job of reading it again and again was jaw-achingly boring. The aim was to get the kids to sleep but more often it put me to sleep rather than them. (I especially remember the story of Pièrre Bear who lived in the Canadian woods and ate minced moose meat: I could still repeat it word for word!) My solution, to keep me awake and put them to sleep, was to read the story in different accents: Scottish, Welsh, Irish, and French (à la Peter Sellers as Inspector Clousseau), for example. Emotion and tone of voice are important (although I am not suggesting precisely this method when lecturing to students). When we are teaching (lecturing), the voice, as Parslow says, can convey emotion and keep students interested: the enthusiasm of the teacher rubs off on the students and keeps them interested. Second, and perhaps more importantly, is the use of so-called “extraverbal” language when one is communicating. This extraverbal language includes the “ums” and “ers” that we typical use in common speech, as well as the “by the ways,” “you knows,” “did you get that's?,” “shall I say that again?,” “I means,” “in facts,” “wells,” and many others that are used in speech but do not appear on our slides. (Hopefully the students do not copy these down in their notes.) These little phrases are interactive and provide feedback. They check that the audience is listening and that the lecturer is going at the right pace for the majority of the audience: in computer terms it is like the “hand-shaking” used when a PC “talks” to a peripheral device to check that it is ready and that the message is being received. There are probably similar phrases in other languages. (If you simply read your lecture you probably do not do this—and perhaps you are not communicating so well?) I could mention here that “body language” is important too. People gesticulate with their hands, they look individuals in the audience in the eye, and do lots of other things in order to “sell their message” to an audience. You do not convince people of anything if you face your slide on the screen and mumble. The third comment I would like to make is that not only do our PowerPoint slides not have these “hand-shaking” features (they do not need them because students can study them at leisure in our hand-outs?), but also, most importantly, we should remember not to show a slide and then talk about something else. This applies especially if there is quite a lot of wordage on the slide. It is unreasonable to expect people to read something they have never seen before, and listen to something different at the same time. This applies even more if one has people in the audience whose first language is not English (for example). If the messages conflict then learning is not likely to be successful. If students are trying to write notes simultaneously there is not going to be much “processing” of the information. “Processing” means taking in new information, checking that you understand it, and fitting it into one's existing knowledge: digesting and consolidating are other terms applied to this process. It is not the same as simply “remembering” as one would “remember” a telephone number, the molecular weight of Tris, or a poem. I never quite understood what Marshall McLuhan meant by saying that “The medium is the message,” but we should remember that when an audience is encountering new material, there needs to be processing or “digestion” of that new material taking place in order for them to make sense of it and gain ownership of it. This takes time, and if the presentation is dull, the story is not clear, the pace is wrong, or the messages are conflicting, then it is highly likely that learning will not take place. It's not so much what you say as the way that you say it.

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)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 enseignants0,163
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
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 Opus0,007
Tête enseignante GPT0,300
Écart entre enseignants0,293 · 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.

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

Citations1
Publié2004
Routes d'admission1
Résumé présentoui

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