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Effects of Pre-Reading Activities on EFL Reading Comprehension by Moroccan College Students

2013· article· en· W1953708583 on OpenAlexvenueno aff
Redouane Madaoui

Bibliographic record

VenueHigher education of social science · 2013
Typearticle
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsReading comprehensionVocabularySchema (genetic algorithms)Reading (process)PsychologyMathematics educationTest (biology)ComprehensionComputer scienceClass (philosophy)LinguisticsArtificial intelligenceInformation retrieval

Abstract

fetched live from OpenAlex

This study investigated the effects of two pre-reading activities (class discussion and vocabulary definitions) and a control condition on the reading comprehension of 57 Moroccan college freshmen. It also investigated the differential facilitative effect of the two pre-reading activities on the students’ comprehension. Each student read an expository text under one of the three conditions and immediately afterwards answered a 9-item short-answer test designed to measure comprehension of the text. A one-way ANOVA and a post-hoc comparison test were applied to the results. This revealed that the two pre-reading activities produced significantly higher comprehension scores than the control condition. Vocabulary definitions activity resulted in increased comprehension compared with the control condition, but was significantly less effective than the class discussion activity. Results of the study were interpreted in relation to the schema-theoretic view of the reading process, and to their implications for EFL reading instruction. Key words: Pre-reading activities; Activating background knowledge; Reading comprehension

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.995

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.010
GPT teacher head0.352
Teacher spread0.341 · 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 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

Citations4
Published2013
Admission routes1
Has abstractyes

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