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Record W2864504670 · doi:10.5539/elt.v11n8p51

Free Voluntary Reading: Promoting Vocabulary Learning and Self-Directedness

2018· article· en· W2864504670 on OpenAlexvenueno aff
Diana Carolina Durán-Bautista, Mario Alberto Rendón Marulanda

Bibliographic record

VenueEnglish Language Teaching · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)VocabularyPsychologyAction researchForeign languageMathematics educationVocabulary developmentPedagogyVocabulary learningAction (physics)Teaching methodLinguistics

Abstract

fetched live from OpenAlex

This action research study focuses on measuring the impact of a Free Voluntary Reading Program on students’ active vocabulary use and self-direction in language learning in two different programs of English as a foreign language. The impetus for this research came from close observation and a needs analysis that confirmed students’ reluctant attitude towards reading, due to deficiency in vocabulary, as well as the limited access to books of their interest in the target language. The implementation of the program took place in blended classes in two university contexts, with 14 and 11 students respectively. All the students from both universities were classified in the A1 level according to the Common European Framework of Reference for Languages and their ages ranged from 16-21 years. The data was collected using a pretest and a posttest, students’ diaries, pre and post implementation surveys and book reviews. The program attempted to promote extensive reading, self-direction, reading habits, vocabulary gain and a more positive attitude towards written stories.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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 designObservational
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

Citations9
Published2018
Admission routes1
Has abstractyes

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