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Record W1595346267

Vocabulary Learning Strategies For Communication Promotion —On English Vocabulary Learning Related to Listening, Speaking, Writing Capability

2011· article· en· W1595346267 on OpenAlexvenueno aff
Huiqing Liu

Bibliographic record

VenueStudies in literature and language · 2011
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyLinguisticsGlossaryVocabulary learningContext (archaeology)GrammarPsychologyPhilosophyHistory
DOInot available

Abstract

fetched live from OpenAlex

By analyzing the Chinese-characterized learning patterns which are so special for the learning is alien from the native environment thus it cannot be called second language acquisition but merely a foreign language leaning, this essay advocates for targeting strategies during the most fundamental study of the learners: vocabulary study. It suggests, mainly, taking advantage of glossary study, to improve the vocabulary learning efficiency; levelling the vocabulary cognition as three degrees; strengthening case and context study, to make language application possible; making the language output pattern Chinese - English just the laguage input pattern; using auditory representation strategy to turn the words you can only read into words you can hear and understand. It also suggests planning the glossary in terms of application as well as memorization, for the sake of learning them by resorting to according strategies. Key words: Second language learning strategies; Chinese-characterised; Vocabulary; Case/context study; Inverted input; Auditory representation Zusammenfassung : Durch die Analyse fur die typische chinesische  Zweisprachigkeit Lernmodus des chinesischen Englischlernenden, die ohne Sprachumgebung sind, hat dieser Artikel die Lernstrategie vorgeschlagen, die man am Anfang des Sprachlernen bzw. beim Worterlernen schon die gezielte Strategie benutzen sollte, d.h. durch die Benutzung der Wort-Liste Strategie die Worter auswendig lernen, um die Effizienz zu erhohen; er hat die Tiefe des Worterlernen als 2 Stufen geteilt; um die Wechseln fur Leseworter auf die mundliche, schriftliche Worter zu verstarken, 1. Das Lernen fur Fall, Sprachumgebung verstarken, um die Verwendung der Worter zu fordern, 2. Die “Chinesisch→Englisch” Inverse Eingabemodus beim Auswendiglernen bzw. beim Eingabe anregen, um die Mythologie “denken direkt auf Englisch”abzubrechen, auch um die Chinesisch→Englisch Antwort-Kette von Chinesen zu gewohnen; es fordert auch die Anhorungswiederaufgabe der auswendiggelernten Worter, um die Worter von Leseworter auf Horworter zu wechseln. Zum Schluss hat es auch die Planung zwischen die Auswendiglernen und Verwendung geausert, es kann den Sprachlernenden helfen, die Planung zu machen und Probleme zu losen. Schlusselworter: Zweisprachigkeit Lernmodus; Typische chinesische; Worter; Fall/Sprachumgebung; Inverse; Anhorungswiederaufgabe

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.349
Teacher spread0.318 · 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 designQualitative
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

Citations0
Published2011
Admission routes1
Has abstractyes

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