MétaCan
Menu
Back to cohort
Record W2122471903 · doi:10.7202/019649ar

Teaching Interpreting by Distance Mode: An Empirical Study

2009· article· en· W2122471903 on OpenAlexvenueno aff
Leong Ko

Bibliographic record

VenueMeta Journal des traducteurs · 2009
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsDistance educationEmpirical researchPsychologyMode (computer interface)Mathematics educationTest (biology)Face-to-faceMedical educationComputer scienceHuman–computer interactionMedicineMathematics

Abstract

fetched live from OpenAlex

This paper is based on an empirical study of teaching liaison interpreting – specifically, dialogue interpreting, consecutive interpreting and sight translation – by distance mode. In this research, two groups of students were recruited – the experimental group to be taught by distance mode and a control group trained face-to-face. The training program lasted for 13 weeks or 39 hours, with three contact hours per week. The training followed the principle that no face-to-face contact with distance students was made during the training process, including the final examination. The major media used in the research included sound-only teleconferencing, telephone and the Internet. Students’ interpreting skills including language transfer and paralinguistic skills were assessed in different tests including an independent national test. The results of the research indicate that students trained by distance mode can achieve a level similar or comparable to those trained in the face-to-face manner in terms of interpreting ability and skills. The research has generated pedagogical implications for future attempts to teach interpreting by distance mode.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.004
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 head0.104
GPT teacher head0.486
Teacher spread0.382 · 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.

Study designNot applicable
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

Citations26
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMeta Journal des traducteursSame topicInterpreting and Communication in HealthcareFrench-language works237,207