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Direct Phonemic Awareness Instruction as a Means of Improving Academic Text Comprehension for Adult Language Learners

2018· article· en· W2982029658 on OpenAlexaboutno aff
M. Gregory Tweedie, Robert C. Johnson, Denise Kay, Jody Shimoda

Bibliographic record

VenueJournal of educational thought. · 2018
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsnot available
Fundersnot available
KeywordsVowelPhonemic awarenessMathematics educationPsychologyEnglish for academic purposesTest (biology)ComprehensionArabicControl (management)PedagogyComputer scienceLinguisticsLiteracy

Abstract

fetched live from OpenAlex

At an international branch campus of a Canadian university located in Qatar, difficulty comprehending academic English text has been an institutionally acknowledged barrier to student success. A team of teacher-researchers in the English for Academic Purposes program conducted a quasi-experimental investigation into the efficacy of phonemic awareness instruction as a means of addressing this competency gap. This project was conducted in an attempt to achieve better alignment between teaching strategies, classroom activities, and student learning outcomes. Sixty-seven students, enrolled in three program level s, were given one hour per week of standardised direct phonemic awareness instruction over a 10-week period. Two tests were used to measure pre-/post-instruction differences: a missing vowel identification test and a C-test. Learners in the treatment group improved significantly more in both measures than those in the control group. The results suggest that direct phonemic awareness instruction can promote the development of both vowel recognition and ability to comprehend academic English text among tertiary-level EAP learners in a predominantly native Arabic language environment.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.438

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)0.0000.000

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 head0.025
GPT teacher head0.367
Teacher spread0.342 · 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 designBench or experimental
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

Citations1
Published2018
Admission routes1
Has abstractyes

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