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Record W4392854873 · doi:10.1017/9781009417594.020

Learner differences 1: age

2024· other· en· W4392854873 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Differences between younger and older learners It is commonly assumed that young children learn languages better than older ones. This is largely based on the observation that in immigrant families, young children normally become – apparently effortlessly – highly proficient in the new language. Research on children who did not have the opportunity to acquire language at an early age (‘wolfchildren’, or congenitally deaf children who recovered their hearing at a late age) indicate that they found it very difficult to learn it later. According to the critical period hypothesis (CPH), young children have a natural ability to learn languages which deteriorates when they get older; though when exactly this critical period ends is a subject of debate. The CPH has been the subject of much controversy and criticism (see, for example, Marinova-Todd et al., 2000). In any case, the evidence summarized above has commonly been used to justify starting foreign-language instruction in schools as early as possible; but this conclusion is not in fact supported by the research. A longitudinal study of children learning English in Barcelona comparing early with late starters in English courses in schools showed that even given the larger number of total hours that younger beginners had studied, their ultimate achievement was no better than that of the older beginners (Muñoz, 2006). This result corresponds to the findings of Swain and her colleagues in extensive studies of students in immersion courses in Canada (Swain, 2000). Pause for thought What are your own feelings about starting English lessons early in schools? Comment In my country, English lessons are increasingly introduced – usually one or two a week – in the early years of primary school, while all the rest of the curriculum is taught in another language. When I ask the question on the previous page, I get a lot of different answers, depending on who is being asked. Parents, school principals, teachers of other subjects usually assume that starting English early in schools is a good thing. The majority of English teachers and other ELT professionals, on the other hand, are strongly opposed. Their opposition is not only because of the reasons given below, but also because the teachers who are leading these English lessons are usually not English teachers, but the class homeroom teachers. These may or may not be fluent in English and in any case do not have much knowledge of effective language-teaching procedures.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.227
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4470.220

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 head0.090
GPT teacher head0.383
Teacher spread0.292 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2024
Admission routes1
Has abstractyes

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