The Level of Critical and Analytical Thinking Skills among Electrical and Electronics Engineering Students, UKM
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.
Bibliographic record
Abstract
The high demand by the industry for graduates capable to critically analyze the causes, content and quality of information and using them effectively to identify and solve engineering problems, has been constantly and incessantly discussed. The inability to think analytically and critically contributes to the increased percentage of unemployed graduates. Additionally, the Malaysian students resort to memorizing and rote learning to find an easy way to get a degree and then find a job. This paper investigates the level of critical and analytical thinking skills among the students in the Department of Electrical, Electronics and Systems Engineering (EESE), Faculty of Engineering and Built Environment (FEBE), UKM. This study was conducted on a group of third year students in Semester 1 2010/2011 using three instruments; the analytical component of MTest model questions by the Malaysian Ministry of Education (MOE) in the selection of prospective students for Teachers College throughout the country, Marbach-Ad and Sokolove's taxonomy (MST) for student questions on a topic discussed in the lecture and the open-ended question posed in the final examination for the microprocessor and microcontroller course. Analysis based on these three techniques provide a rough estimation on the level of analytical and critical thinking skills among students and in this study, it was learned that the critical and analytical thinking skills among these students are at a very moderate level despite their high academic achievement.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it