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Record W2913869209 · doi:10.18806/tesl.v35i2.1296

Building a Community of Connected ELT Professionals on Twitter

2018· article· en· W2913869209 on OpenAlex
Bonnie Nicholas, Augusta Avram, Jennifer Chow, Svetlana Lupasco

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTESL Canada Journal · 2018
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesProfessional developmentWorkloadSociologyLibrary sciencePolitical sciencePedagogyManagementArtComputer science

Abstract

fetched live from OpenAlex

Although English language teaching professionals are committed to ongoing continuous professional development, economic and workload factors may impede their ability to attend a traditional 2-day annual conference. Teachers have turned to social media as an alternative approach to self-directed professional development. In particular, Twitter has become the choice of many educators with its potential for networking and collaboration. There are scheduled Twitter chats held regularly on a variety of topics of interest to language teaching professionals, including #CdnELTchat. In addition, connected educators have built a community of practice on the Twitter platform and provide inspiration and support to their colleagues online. In this article, four connected educators who have found their community on Twitter share their stories of how they got started on Twitter, how they connected with each other, and what they value about the open Twitter platform.
 Bien que les professionnels de l’enseignement de l’anglais s’engagent à poursuivre un perfectionnement professionnel continu, des facteurs économiques ou des charges de travail peuvent les empêcher d’assister à une conférence annuelle traditionnelle de 2 jours. Les enseignantes et enseignants trouvent dans les réseaux sociaux une solution de rechange qui leur permet de veiller à leur propre perfectionnement professionnel. Twitter, notamment, est le nouveau choix de nombreux éducateurs et éducatrices en raison des possibilités de réseautage et de collaboration qu’il présente. Des sessions de clavardage ont régulièrement lieu sur une variété de sujets présentant un intérêt pour les professionnels de l’enseignement des langues, et ce, notamment sur #CdnELTchat. Qui plus est, les éducatrices et éducateurs connectés ont construit une communauté de praticiens sur la plateforme Twitter et fournissent une inspiration et un soutien à leurs collègues en ligne. Dans cet article, quatre éducatrices connectées qui ont découvert leur communauté sur Twitter décrivent comment elles ont commencé à se servir de Twitter, comment elles se sont connectées les unes aux autres, et ce qu’elles apprécient le plus sur la plateforme ouverte de Twitter.

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.

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)0.001
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 score0.623
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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)0.0200.000

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 head0.087
GPT teacher head0.435
Teacher spread0.348 · 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