Evaluation of Critical Thinking in Higher Education in Oman
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".