MétaCan
Menu
Back to cohort
Record W4379875884 · doi:10.5539/elt.v16n7p19

Intrinsic Feedback vs. Extrinsic Feedback on Developing Oral Fluency and Self-Concept of Iraqi English (EFL) Students

2023· article· en· W4379875884 on OpenAlexvenueno aff
Ismail Bagheridoust, Buraq Hamid Hashim Al-Bakirat

Bibliographic record

VenueEnglish Language Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyFluencyCorrective feedbackInterpretation (philosophy)PerceptionVerbal fluency testClass (philosophy)Self-conceptMathematics educationTest (biology)Social psychologySelf-esteemLinguisticsCognition

Abstract

fetched live from OpenAlex

This study mainly examines internal and external feedback on Iraqi EFL learners' oral language ability and self-concept development. Researchers tested the research questions, followed the statistical procedures of the situation, and arrived at thoroughly prepared statistical results. After t test analysis and interpretation of mean differences, the mean of verbal fluency in the external feedback group attracted much more attention than the verbal fluency of students receiving internal feedback. However, the same story does not apply to the development of self-concept in both groups. the self-esteem average of students who received external feedback is slightly lower than the average of students in the internal feedback group. The self-perception of students who received internal feedback in class changed over time and they became more confident students with their own self-image. They felt more independent than before.

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)0.018
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.018
GPT teacher head0.325
Teacher spread0.307 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueEnglish Language TeachingSame topicEducation and Critical Thinking DevelopmentFrench-language works237,207