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Record 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 on OpenAlexaboutno aff
EJ Wood

Bibliographic record

VenueBiochemistry and Molecular Biology Education · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnthusiasmReading (process)Tone (literature)WelshPsychologyPoint (geometry)Mathematics educationLinguisticsSocial psychologyPhilosophy

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.300
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2004
Admission routes1
Has abstractyes

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