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Record W2952317597 · doi:10.5539/elt.v11n12p106

TED Talks as an ICT Tool to Promote Communicative Skills in EFL Students

2018· article· en· W2952317597 on OpenAlex

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

VenueEnglish Language Teaching · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)PsychologyMathematics educationEnglish as a foreign languageForeign languageAction (physics)PedagogyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

In many EFL classrooms in Colombia, it is evident how students struggle trying to use English to communicate; nonetheless, with the revolution of ICTs that has taken place in the last years, there is a variety of tools available to support English learning autonomously with applications, blogs, and online courses; however, many of these tools were not originally designed for teaching but can be adapted for such purpose. TED is a website and a downloadable application where videos are shared in which you can see a wide variety of English speakers born in many parts around the world speaking in a fun and familiar manner with the audience about various topics of interest that besides, come along with cultural content, which extends the range of accents, words, expressions, and ways of referring to the same topic. In this action research, we propose a reflection on the incidence of TED talks on the teaching and learning of English as a foreign language. The instruments used to collect data were interviews, questionnaires, and teacher journals. The use of these videos provided the students with all the communicative elements that allowed them to use English to express their ideas. This offers a glimpse of how useful authentic videos and subtitles are when encouraging students to learn English.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.300
Teacher spread0.289 · 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