MétaCan
Menu
Back to cohort
Record W2886560897 · doi:10.5539/elt.v11n9p33

Experimenting With Academic ESL: An ESL/Sociology Link

2018· article· en· W2886560897 on OpenAlexvenueno aff
Gail August

Bibliographic record

VenueEnglish Language Teaching · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyClass (philosophy)PsychologyMathematics educationCurriculumAction researchPedagogyLinguisticsComputer science

Abstract

fetched live from OpenAlex

To improve academic ESL, a community college has been experimenting with linking an ESL class to a Sociology class. The primary goal was to use the methodology of Content Based Instruction to develop a curriculum that would promote academic vocabulary acquisition, critical thinking, and authentic communication in a sheltered environment. The paradigm of Action Research was used as a framework to reflect on the strengths of the program and to identify activities that engaged the students and contributed to improved language skills. Supplementary assignments of a Young Adult novel and provocative movies, used across both the ESL and Sociology class, helped students to apply abstract concepts to familiar situations. The structure of the link produced an effective learning community and a support system for the students. We suggest that linking ESL to a content course might be preferable to other options for developmental ESL students entering college.

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)0.009
metaresearch head score (Gemma)0.013
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.061
GPT teacher head0.414
Teacher spread0.353 · 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
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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicEducator Training and Historical PedagogyFrench-language works237,207