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Record W2799448198 · doi:10.5430/wjel.v8n1p28

The Role of Persian Elaboration on Incidental Vocabulary Learning from Reading by EFL Learners

2018· article· en· W2799448198 on OpenAlexvenueno aff
Shahin Vaezi, Aso Biri, Farhang Moradi

Bibliographic record

VenueWorld Journal of English Language · 2018
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVocabularyReading (process)PersianVocabulary learningTest (biology)PsychologyElaborationMathematics educationComputer scienceLinguisticsHumanities

Abstract

fetched live from OpenAlex

This study attempted to tap into the potential of reading for incidental vocabulary learning by exposing EFL learnersto elaborated texts. This study was also concerned with investigating learners’ attitudes toward using elaboratedpassages in their reading classes. To this end, 38 students were selected as the participants of this research anddivided into two groups. Students attending the experimental group (N=20) read Persian elaborated texts in whichthe Persian meanings of the specified target words were provided in apposition to them. On the other hand, studentsof the control group (N=18) were required to read the non-elaborated version of the aforementioned texts. Generally,the results of the post-test pointed to the effectiveness of this approach in incidental vocabulary learning, and theparticipants of the experimental group were found to gain a significant vocabulary improvement in comparison to thecontrol group. Furthermore, the interview suggested that students held positive attitudes to reading elaborated textsand regarded them as effective in their vocabulary learning experience. The findings of this study have implicationsfor material developers who need to reconsider the role of modified 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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.178
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.005
GPT teacher head0.264
Teacher spread0.258 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations0
Published2018
Admission routes1
Has abstractyes

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