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The Effectiveness of Interactive Instruction on the Intonation Learning of Chinese College Learners

2010· article· en· W1959478112 on OpenAlexvenueno aff
Liu Yan-li

Bibliographic record

VenueCross-cultural communication · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsIntonation (linguistics)LinguisticsInterlanguagePronunciationPsychologyPhonologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

The paper reported the findings from the study on the different effects of two form-focused instructional techniques on the EFL learner’s learning of English intonation. The purposes are to investigate: 1) do the intonation instructions reset EFL leaner’s interlanguage phonology, e.g., improving their intonation?; and 2) if there were some improvements of the interlanguage phonology through the pronunciation instruction, do two types of explicit instruction, differing in the manner of instruction, have the same or different effects on EFL leaner’s learning of English intonation? To which extent, the instruction is better than the other. The examination of F0 range and pitch contour in the study indicated that 1) most of the Chinese test subjects could improve their intonation performance after the instructions; 2) the experimental group input plus interaction(II) outperformed the experimental group input plus explanation(IE). The gain in intonation awareness leads to their (II group) significant improvement in the prosodic performance. Key words: Intonation instruction, cognitive approach, communicative approach Resume: Le present article reporte les resultats d’etude sur les differents effets de deux techniques d’enseignement focalisees sur la forme dans l’apprentissage de l’intonation anglaise des etudiants qui ont l’anglais comme langue etrangere (EFL). Le but de l’article consiste a investiguer : (1) Est-ce que l’instruction d’intonation influence la phonologie de l’interlangage des apprenants d’EFL, par exemple, ameliorer leur intonation ? (2) S’il y a des ameliorations de la phonologie de l’interlangage par l’instruction de prononciation, est-ce que les deux type d’instruction explicites, differant l’un de l’autre dans la maniere d’instruction, ont les memes ou differents effets sur l’apprentissage de l’intonation anglaise des apprenants. Dans cette mesure, l’instruction est meilleure que l’autre. L’etude indique : (1) la plupart des tests chinois peuvent ameliorer leur intonation apres l’instruction ; (2) le groupe experimental qui insiste sur l’interaction (II) depasse le groupe experimental qui met l’accent sur l’explication(IE). L’avantage du groupe II dans l’intonation les conduit a des progres signifiants dans la performance prosodique. Mots-Cles: instruction d’intonation, approche cognitive, approche communicative 摘 要:本研究通過分析兩種語音教學方法(認知語音教學法和交際語音教學法)對 10 名英語專業學生的朗讀的語音語調習得的效果旨在解決以下問題:1)語音教學是否能改善外語學習者的仲介語音的語調? 2)如果學習者的語音語調能夠被提高改善,哪種語音教學方法,認知語音教學還是交際性語音教學,對學習者的仲介語語音語調的改善更高?通過對 10名女受試者的在前測和後測的朗讀語調的F0 值的對比表明 1)中國英語學習者的仲介語音語調能夠通過語音教學能夠有所提高; 2)在對前測和後測的F0 值的對比分析表明,5名來自認知教學法的學生的 F0值要跟接近 2名英語本族語者的 F0值。 關鍵詞:語音教學;在語音教學;認知教學法;交際教學法;英語語調

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.316
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations4
Published2010
Admission routes1
Has abstractyes

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