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Record W1870720787 · doi:10.5430/ijhe.v4n3p33

Evaluation of Critical Thinking in Higher Education in Oman

2015· article· en· W1870720787 on OpenAlex
Renjith Kumar R., Rajani James

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

VenueInternational Journal of Higher Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsArgument (complex analysis)Critical thinkingInterpretation (philosophy)WatsonInferenceMathematics educationPsychologyHigher educationComputer scienceMedicineArtificial intelligencePolitical science

Abstract

fetched live from OpenAlex

The study aims to identify the critical level thinking of students in higher education. It is focused to evaluate the level of critical thinking variables among the students in Nizwa College of Technology and to determine whether these variables are influenced by gender and department. The data for the research is collected from 281 diploma students from Engineering, Information Technology and Business departments of Nizwa College of Technology, Sultanate of Oman. The statements for the instrument are adopted from Watson-Glaser Critical Thinking model consisting of the five variables, namely Inference, Assumptions, Deduction, Interpretation and Arguments. Male students show more of inference and interpretation skills than female students. It is proved that gender has no relationship on assumption and deduction. Females show more argument skills than male students. Students in Engineering department have a high inference level and deduction level than other departments. Business and Information Technology department students have high assumption level than Engineering students. Business department students have high evaluation of arguments than other departments. Students of Information Technology department are high in interpretation than other students.

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)0.005
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.479
Teacher spread0.361 · 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