Research Trends in Critical Thinking: Bibliometric Analysis Using VosViewer (1994–2023)
Bibliographic record
Abstract
Critical thinking skills have emerged as a prominent aspect of 21st-century competencies over the past three decades. The authors have shown a growing interest in investigating these skills in recent years. This research employs bibliometric analysis through the VOSviewer application, spanning the period from 1994 to 2023, to scrutinize the current trends and status of critical thinking skills research. Utilizing Scopus data, a total of 16,011 journal articles were considered for bibliometric mapping analysis. The findings reveal that in 2022, there is a peak of publications is 1602. The most commonly used keywords include critical thinking, education, and higher education. Noteworthy papers by Anderson T. et al., Andrews-Hanna J.R. et al., and Carini R.M are identified as the most frequently cited documents. Prolific authors such as Hwang, Pascarella, and Oxman are highlighted, and journals like Nurse Education Today, Thinking Skills and Creativity, and Journal of Nursing Education stand out. Leading institutions include the University of Toronto, State University of Malang, and Monash University, while the most active countries in this field are the US, UK, and Australia. The findings from the science mapping reveal an increasing focus on the development of critical thinking abilities, particularly within the realms of Health and Education. This indicates that the subject is likely to remain a prominent discussion point in the future, given its significance in enhancing both work quality and educational standards.
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 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 | 0.031 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.162 | 0.201 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".