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Record W2411060569 · doi:10.1002/tesj.254

Dialogue Journals in Short‐Term Study Abroad: “Today I Wrote My Mind”

2016· article· en· W2411060569 on OpenAlexaffabout
Roswita Dressler, M. Gregory Tweedie

Bibliographic record

VenueTESOL Journal · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPopularityFeelingStudy abroadConversationPedagogyClass (philosophy)PsychologyVariety (cybernetics)Journal writingBridge (graph theory)Higher educationTerm (time)Intercultural communicationMathematics educationTeaching methodSocial psychologyPolitical scienceCommunicationComputer science

Abstract

fetched live from OpenAlex

Short‐term study abroad programs are growing in popularity, and educators and researchers are exploring effective tools to enhance the learning and cultural experiences of students in these programs. Dialogue journals, writing journals in which students respond to instructor prompts and in turn initiate topics for further written discussion, are a useful pedagogical tool in a variety of educational contexts, but their use in the short‐term study abroad setting remains largely unexplored. This article looks at the dialogue journal writing of eight Japanese students in a 4‐week visit to a Canadian faculty of education. Themes that emerged from their writing in conversation with their English for academic purposes instructor reveal that the dialogue journals provided a venue for students to express their feelings, draw upon their learning outside of class, and bring their intercultural learning into the dialogue. The use of dialogue journals facilitated the building of rapport between teacher and students and served to bridge cultural differences.

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)0.006
metaresearch head score (Gemma)0.022
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 score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.067
GPT teacher head0.321
Teacher spread0.254 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

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