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Record W1976566846 · doi:10.3138/cmlr.67.1.091

Sociocultural Dynamics of ESL Learning (De)Motivation: An Activity Theory Analysis of Two Adult Korean Immigrants

2011· article· en· W1976566846 on OpenAlexfundvenueno aff
Tae-Young Kim

Bibliographic record

VenueCanadian Modern Language Review/ La Revue canadienne des langues vivantes · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsnot available
FundersUniversity of TorontoChung-Ang UniversityUniversity of Miami
KeywordsDynamismPsychologyPerspective (graphical)ImmigrationDynamics (music)Context (archaeology)Sociocultural evolutionActivity theoryIntrinsic motivationAffect (linguistics)Longitudinal studySocial psychologyLearning theoryDevelopmental psychologyMathematics educationPedagogySociologyEpistemologyCommunication

Abstract

fetched live from OpenAlex

This study examines the longitudinal trajectories of two Korean ESL immigrants' L2 learning motivation from an Activity Theory perspective. Two highly skilled immigrants participated in monthly semi-structured interviews over a period of 10 months. The research questions are as follows: (1) How does the relationship between ESL learners and their perceived social contexts affect and shape the way in which their ESL learning motivation develops? (2) How can the factors affecting the changes in ESL learning motivation be explained from an Activity Theory perspective? The recurring themes in the monthly interview data were coded and aligned to Engeström's (1999a) activity-system model; important interactions among the subcomponents of the model are presented and discussed. The results indicate that (1) the dynamism in ESL learning (de)motivation can be coherently explained in a series of longitudinal activity-system models; and (2) that it is not the ESL context per se but each participant's recognition of it that plays a pivotal role in creating, maintaining, and terminating ESL learning motivation.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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 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

Citations50
Published2011
Admission routes2
Has abstractyes

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