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Record W4327951968 · doi:10.5430/jct.v12n3p1

An Investigation into University English Language Instructors’ Inclusion of the Revised Bloom's Taxonomy of Cognitive Skills in Testing Language Skills: Selected Universities in Focus

2023· article· en· W4327951968 on OpenAlexvenueno aff
Alemayehu Wochato Laiso, Wondwosen Tesfamichael Ali, Zeleke Arficho Ayele

Bibliographic record

VenueJournal of Curriculum and Teaching · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Assessment and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsNonprobability samplingCognitionPsychologyEnglish languageInclusion (mineral)Language assessmentMathematics educationCognitive skillBloom's taxonomyTaxonomy (biology)Test (biology)Medical educationPedagogyMedicinePopulationSocial psychology

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate into university English language instructors’ inclusion of the revised Bloom's Taxonomy of Cognitive skills in testing undergraduate students’ language skills. The participants of the study were 32 English language instructors who were offering English language courses to undergraduate students. They were selected using a purposive sampling. All the participant-instructors were made to fill in a close-ended questionnaire and a semi-structured interview was held with four of them. Document analysis was also conducted using the judgments of the English language experts. Data collected by the questionnaire was analyzed quantitatively using frequency counts and percentages, whereas data gathered through the interview was analyzed qualitatively. The study employed a descriptive research design and mixed-methods approach. The study's findings revealed that the test items are hardly higher-level cognitive skills (analyzing, evaluating and creating); they are completely dominated by lower-level cognitions (remembering, understanding and applying). Hence, it is recommended that university ELT instructors should give due attention for the revised Bloom’s taxonomy of cognitive skills in testing their students’ language skills.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.304
Teacher spread0.292 · 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 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

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