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Record W4410116552 · doi:10.22329/jtl.v19i2.8977

From Challenges to Transformation: The Professional Development Journey of Transnational Language Teachers in the United States

2025· article· en· W4410116552 on OpenAlexvenueno aff
Yu Wu, Huan Gao

Bibliographic record

VenueJournal of Teaching and Learning · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsTransformation (genetics)Professional developmentPolitical scienceSociologyPedagogy

Abstract

fetched live from OpenAlex

In the context of global educational exchange, this study explores the experiences of Chinese teachers temporarily teaching Mandarin Chinese in United States K-12 schools. Using case-study methodology, this research examines the professional challenges and learning experiences of these transnational Chinese language teachers. Findings reveal that teachers’ career difficulties arise from the use of teaching strategies that do not align well with the environments of the host schools and from insufficient cultural sensitivity. Moreover, inadequate pre-service training and limited professional development opportunities exacerbate these challenges, prompting self-directed transformative learning efforts. The findings also emphasize how tailored training combined with teachers' transformative learning initiatives can effectively address and mitigate the difficulties faced in transnational teaching environments. This study provides valuable insights into the preparation for transnational educators navigating cross-cultural teaching landscapes, thereby contributing to the discourse on international teacher-exchange programs.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.237
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.288
Teacher spread0.261 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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