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Record W2398088003 · doi:10.5430/wjel.v7n1p11

Lecturers’ and Students’ Perceptions and Preferences about ESL Corrective Feedback in Namibia: Towards an Intervention Model

2017· article· en· W2398088003 on OpenAlexvenueno aff
Saara S. Mungungu-Shipale, Jairos Kangira

Bibliographic record

VenueWorld Journal of English Language · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsCorrective feedbackTertiary levelPerceptionVariety (cybernetics)GrammarMathematics educationEnglish as a second languageIntervention (counseling)PsychologyEnglish languageEnglish grammarPedagogyComputer scienceLinguistics

Abstract

fetched live from OpenAlex

This study investigated tertiary lecturers’ and students’ perceptions and preferences on the provision of CorrectiveFeedback (CF) in the English as a Second Language (ESL) classroom at the Namibia University of Science andTechnology. The study focused on students’ speaking and writing skills in the Language in Practice English course.The findings revealed that both lecturers and students perceive CF as an essential aspect of developing ESL productiveskills. Both lecturers and students were of the perception that CF is more focused on English grammar than form.Students preferred more correction than their lecturers provided. Both lecturers and students concurred thatmetalinguistic feedback is the best practice for CF in English. The contribution this study made is the ten-stageIntervention Model that works towards the effectiveness of ESL CF at tertiary level in Namibia. The modelrecommends that lecturers should carefully scrutinise the specific ESL target language features; practise a variety ofsuitable CF techniques; and cater for individual students’ specific needs and preferences in learning English as aSecond Language at tertiary level.

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)0.000
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 score0.485
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.308
Teacher spread0.282 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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