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Record W2752208322 · doi:10.5539/elt.v10n10p1

Exploring Students’ Perspectives toward Clarity and Familiarity of Writing Scoring Rubrics: The Case of Saudi EFL Students

2017· article· en· W2752208322 on OpenAlexvenueno aff
Dukhayel Aldukhayel

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsnot available
Fundersnot available
KeywordsRubricCLARITYPsychologyMathematics educationQuality (philosophy)Set (abstract data type)Strengths and weaknessesMedical educationComputer scienceSocial psychologyMedicineChemistry

Abstract

fetched live from OpenAlex

The main aim of this research study is to investigate the clarity and familiarity of three scoring rubrics used in a Saudi university’s preparatory year program (PYP) for assessing students’ writing achievement in midterm and final exams. This exploration is important in providing some evidence for the quality of scoring rubrics. To achieve that purpose, a 13-item online questionnaire was used to collect Saudi EFL PYP students’ perspectives toward two quality criteria concerning rubrics; 1) clarity of the information included in the PYP rubrics, and (2) familiarity of the rubrics to students. The subjects were 281 Arabic-speaking male and female EFL Saudi students enrolled in three different academic levels in a Saudi university’s PYP. The results suggest that the quality of the PYP rubrics is insufficient and the criteria set for providing evidence for the rubric qualities were not met. The results show that students tend to have a mild agreement on the clarity of the PYP rubrics, whereas they show a clear disagreement on their familiarity with the rubrics and with why and how the rubrics are used. The study implicates that administrators and teachers need to carefully consider the clarity and familiarity of rubrics in order to justify the decisions made about students’ writing abilities. Rubrics that are unclear or unfamiliar can make students feel confused and frustrated, as they cannot get a clear sense of their writing scores, as well as their strengths and weaknesses.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
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 science0.0010.001
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 head0.091
GPT teacher head0.399
Teacher spread0.308 · 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 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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