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Record W2605214299 · doi:10.5539/elt.v10n5p16

Grammar Errors Made by ESL Tertiary Students in Writing

2017· article· en· W2605214299 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicEFL/ESL Teaching and Learning
Canadian institutionsnot available
Fundersnot available
KeywordsGrammarVerbPsychologySentenceSubject (documents)Tertiary levelEnglish grammarContext (archaeology)Mathematics educationAgreementLinguisticsHigher educationPedagogyComputer science

Abstract

fetched live from OpenAlex

The educational context in Malaysia demands students to be equipped with sound grammar so that they can produce good essays in the examination. However, despite having learnt English in primary and secondary schools, students in the higher learning institutions tend to make some grammatical errors in their writing. This study presents the grammatical errors made by tertiary students in their writing. The participants were a group of Diploma students who sat for a university entrance exam. One hundred and forty-four written essays of the students were collected and analysed using content analysis. Findings revealed that subject-verb agreement and tenses were the most common type of errors. Students over-generalised and perceived that the tenses could be used interchangeably. Another common error found was in the students’ construction of complex sentence. In such constructions, they failed to include essential and nonessential clauses. If teachers do not teach strategies to assist students in comprehending the concept of Subject-Verb Agreement (SVA), tenses, essential and nonessential clauses, these students will continue to make such errors in their tertiary education. The findings may have useful implications for English language teachers as understanding students’ learning difficulties and providing appropriate grammar instruction is the key to effective teaching for ESL teachers.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.013
GPT teacher head0.285
Teacher spread0.271 · 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