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Authentic Materials

2018· other· en· W4249533023 on OpenAlexaff
Guofang Li, Wenying Zhou

Bibliographic record

VenueThe TESOL Encyclopedia of English Language Teaching · 2018
Typeother
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCommunicative language teachingEnglish languageComputer scienceLinguisticsLanguage educationLanguage acquisitionPsychologyPedagogyMathematics education

Abstract

fetched live from OpenAlex

Authentic materials in English as an international language (EIL) include both the oral and written materials that are used in the English language environment but that are not created expressly for the purpose of English language teaching or learning. Central to the prominent use of authentic materials in EIL are the advances in pedagogical approaches such as the audio‐lingual methods and the communicative language teaching that have resulted in a paradigm shift in the role of English language teacher and the types of texts used in English language instruction. While research has identified many advantages of using authentic materials in EIL, there exist many challenges in locating and designing communicative tasks around authentic materials. Future research must address the processes of authentic materials use as well as audience (i.e., advanced versus beginner learners) and purpose (i.e., culture learning and what and whose culture) of use of such materials.

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)0.005
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.386
Threshold uncertainty score0.876

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0060.005
Open science0.0030.007
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.3860.195

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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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