Bibliographic record
Abstract
Developing the ability to think critically is vital component of real, meaningful teaching and learning. Critical thinking helps us solve problems, make decisions and reach our goals. Thinking is not a passive but an active process. If students’ critical thinking skills are activated, for example while writing, very successful results can be attained. It can be said that critical thinking can be considered in two respects: to achieve a goal and to make a decision. As for teaching, there is very little evidence that students at universities acquire the skills of critical thinking in their learning and teaching activities. In accordance with its important place of in learning and teaching periods, it has been a concept recently highlighted in the field of EFL, like in many other fields of education such as mathematics, history and geography. The skill of critical thinking plays a great role and it has been accepted as an important step in every area of teaching and learning, particularly nowadays due to developments cognition and intelligence. So, in order to understand the awareness of the students for critical thinking, an experiment was performed in the fall of AY 2017-18, with 79 students in Karabuk University, Turkey. In this study, the significance of critical thinking and result of the experiments were discussed in detail, it also shed light on the students’ perceptions of it.
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 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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".