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Record W1595156244 · doi:10.18806/tesl.v30i7.1154

Teaching Pragmatics and Intercultural Communication Online

2014· article· en· W1595156244 on OpenAlexaffvenueabout
Erin Waugh

Bibliographic record

VenueTESL Canada Journal · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsNorQuest College
Fundersnot available
KeywordsPragmaticsIntercultural communicationIntercultural competencePsychologyCompetence (human resources)Cultural competencePedagogyLanguage acquisitionMathematics educationLinguistics

Abstract

fetched live from OpenAlex

English in the Workplace (EWP) programs are increasingly surfacing across Can- ada to assist internationally educated professionals (IEPs) with the challenges of integrating into the Canadian workplace. One critical topic of these courses is targeted pragmatics (soft skills) instruction. By learning these skills, IEPs gain valuable tools for communicating effectively and appropriately with their Cana- dian-born colleagues and leaders. The workplace is also becoming increasingly culturally diverse, broadening the required skillsets of IEPs to include intercultural competence—the ability to adapt both cognitively and behaviourally across cultures to achieve communicative goals (Bennett, 1993). As an EWP instructor in a medium-sized institution in Alberta, I worked on the redesign of an EWP course with both pragmatics and intercultural components to be offered online. The course results showed learner development in both pragmatics and intercul- tural competence. In this article, I outline the theory that informed the course design, content, and assessment tools; discuss results of a sample of learners from four pilot offerings; and provide considerations for instructors and instructional designers tasked with the development of online courses of this nature.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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

Citations4
Published2014
Admission routes3
Has abstractyes

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