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Record W1896736089 · doi:10.18806/tesl.v27i1.1031

A Sociocultural View of Language Learning: The Importance of Meaning-Based Instruction

2009· article· en· W1896736089 on OpenAlexvenueno aff
Barohny Eun, Hye-Soon Lim

Bibliographic record

VenueTESL Canada Journal · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
FundersHallym University
KeywordsSociocultural evolutionFacilitatorPsychologyMeaning (existential)PedagogyLanguage acquisitionComprehension approachLanguage educationTeaching methodLinguisticsMathematics educationSociologySocial psychology

Abstract

fetched live from OpenAlex

The process of second-language teaching is grounded in the sociocultural theory of Vygotsky, which emphasizes meaningful interaction among individuals as the greatest motivating force in human development and learning. In this theoretical framework, the concepts of meaning and mediation are considered as the two essential elements affecting an individual’s learning of a second language. Suggestions are offered for enhancing students’ second-language learning in their regular classrooms by applying sociocultural theories to practice. Socioculturally based implications for classroom teaching include bilingual instruction, focus on pragmatics, literacy instruction based on drama, inclusive learning environments, instruction based on children’s interests, and the teacher’s role as a facilitator mediating between students and their second-language learning environment.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0060.043
Scholarly communication0.0110.009
Open science0.0010.006
Research integrity0.0030.004
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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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 designTheoretical or conceptual
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

Citations51
Published2009
Admission routes1
Has abstractyes

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