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Record W2619722715 · doi:10.5539/ells.v7n2p99

The Text Type Effect on Moroccan EFL University Learners’ Reading Achievement

2017· article· en· W2619722715 on OpenAlexvenueno aff
Mohammed Msaddek

Bibliographic record

VenueEnglish Language and Literature Studies · 2017
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsReading comprehensionTypologyReading (process)NarrativeTest (biology)English as a foreign languageLinguisticsMathematics educationForeign languageComputer scienceRhetorical modesPsychologySociology

Abstract

fetched live from OpenAlex

This study is a potential endeavor to make an inquiry into the perceived effect of text typology on reading achievement gains among Moroccan English as a foreign language (EFL) learners. It also evinces whether strategy instruction can be an influencing variable on learners’ reading achievement with regards to text type (i.e., narrative, expository). Indeed, incorporating two primary text genres (i.e., narrative, expository) in the conduct of this current research, the study is intended to substantiate any marked interrelatedness existing between text typology and reading achievement at the pre- and post-testing stages among EFL university learners. For assuring a thorough, rich investigation of this stated postulate, two sampled Moroccan EFL groups (n=113), as first-year English majors, were addressed. The obtained data were collected by means of a corpus of research instruments such as reading comprehension tests (i.e., pre-test, post-test), strategy training and reading comprehension texts (i.e., narrative, expository). The findings showcased that text genre is not a significant, influential variable on reading achievement scores among the control (n=50) and treatment groups (n=63). Finally, the study puts forward some useful implications pertaining to EFL text processing/ analysis and an explicit mention of some limitations, which encountered the undertaken study, is made.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.301
Teacher spread0.290 · 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.

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

Citations3
Published2017
Admission routes1
Has abstractyes

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