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Record W4319299051 · doi:10.5430/wjel.v13n2p187

Students' Perceptions about Course Evaluation: A Discourse Analysis from the Perspective of the Appraisal System

2023· article· en· W4319299051 on OpenAlexvenueno aff
Bandar Alhamdan

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSubcategoryValuation (finance)Systemic functional linguisticsPerspective (graphical)Appraisal theoryQualitative analysisPerceptionDiscourse analysisQualitative researchPsychologyAction (physics)LinguisticsSociologyPedagogyMathematics educationComputer scienceSocial psychologySocial scienceArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

This qualitative study is based on a pedagogical action regarding discursive strategies used by university students in evaluating a course in which they are enrolled. The objective is to identify linguistic items using instruments and categories based on theoretical frameworks from the systemic functional linguistics (SFL) perspective (Halliday, 1985; Halliday & Mathiessen, 2014): more specifically, carrying out a discourse analysis through the appraisal system elaborated by Martin and Rose (2003) and Martin and White (2005). The corpus of this research comprises responses to three open-ended evaluation questions to 24 participants. The discourse analysis of students’ evaluations focuses on the perceptions of these learners regarding the course’s positive and negative aspects. The researcher observed how, through lexicogrammatical choices, students characterize their perceptions of the course using the categories of appreciation and judgment, which are components of the subsystem of attitude, in the appraisal system, considering the types: reaction, composition and valuation and the subcategory capacity. Results indicated that the discourses were marked mainly by the subcategories of reaction quality and valuation relevance.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.343
Teacher spread0.324 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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