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Record W7137658199

Exploring Language Education

2022· other· en· W7137658199 on OpenAlexaboutno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Selection (genetic algorithm)Language industryLanguage educationField (mathematics)Intersection (aeronautics)Comprehension approachOn LanguageLanguage acquisition
DOInot available

Abstract

fetched live from OpenAlex

The overarching aim of this book is to offer researchers and students insight into some currently discussed issues at the Swedish as well as the international research frontline of Language Education in a selection of up-to-date work. Another aim is to provide teachers, teacher educators and policy-makers with input from research within the interconnected disciplines of Applied Linguistics, Language Education and Second Language Acquisition. The volume includes five examples of topical research on language education and the authors are internationally renowned scholars. The chapters are based on a selection of talks presented at the 1st ELE Conference (‘Exploring Language Education’), which was held at Stockholm University in 2018. Employing a broad thematic scope, the volume reflects the variety of perspectives on language education brought together at the conference by authors working in diverse areas of the field and in different parts of the world. With the first ELE conference the organizers wished to call attention to the intersection of the global and the local, in terms of linguistic and cultural diversity, which may inform both research questions and language education practices. Issues related to multilingualism, Global Englishes, and experienced tensions between research and practice are examples of generally shared issues that were brought up by many speakers. The chapters of the book represent this variety of themes and illustrate how different regions and communities are contingent on local prerequisites and circumstances, leading to a number of particular challenges and assets when it comes to language education. The chapters represent different parts of the broad array of research directions that can be discerned under the large umbrella of Language Education, zooming in on the Western context, specifically Sweden, Canada and the United States. Two of the plenary speakers from the conference, Nina Spada and John Levis contribute in the volume. In Spada’s text different ways to bridge the gap between research and practice in language education are discussed, an issue highly relevant to all of those interested in collaborative research between researchers and teachers. The second chapter, written by Levis, presents current research on phonology and the importance of pronunciation in second or foreign language communication. These two are followed by three chapters reporting on empirical studies. Amanda Brown and colleagues present their work on translanguaging in the English L2 classroom, giving an extensive overview of ideological stances from the last decades on the use of mother tongues vs. target language only in the language classroom. Liss Kerstin Sylvén reports on a recent study on very young Swedish learners of English, their exposure of English before school age and outside school and the role that this exposure plays for the development of English language proficiency. Finally, Gudrun Erickson and colleagues, present a questionnaire answered by a large number of modern language teachers in Sweden. The study explores the teachers’ answers on questions about their professional satisfaction, their use of the target language in the classroom, and the curricular status of foreign languages studied after English. Despite many critical points raised by these teachers, the survey reveals that they would not change profession, were they given the chance. The book ends with an Afterword by Stellan Sundh, University of Uppsala.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.015
Scholarly communication0.0110.010
Open science0.0010.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.238
GPT teacher head0.448
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2022
Admission routes1
Has abstractyes

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