Defining a New 21st Century Skill-Computational Thinking: Concepts and Trends
Bibliographic record
Abstract
Computational Thinking is a skill that guides the 21th century individual in the problems experienced during daily life and it has an ever-increasing significance. Multifarious definitions were attempted to explain the concept of Computational Thinking. However, it was determined that there was no consensus on this matter in the literature and several different concepts were mentioned in the definitions found in the literature. It was considered that this fact made it difficult to understand the concept of Computational Thinking. To establish a more comprehensive approach, the present study aimed to identify the concepts that are included in the Computational Thinking definitions that were presented in previous studies. It also aimed to reveal trends in the identified concepts throughout the years. As a result of the search, a total of 59 definitions were identified and a content analysis was conducted on these definitions. Analysis results demonstrated that Computational Thinking was defined based on several concepts such as problem solving, technology, thinking, individual and social qualities. Furthermore, it was determined that statements on thinking were prominent before 2006, and today, emphasis on problem solving and technology became more significant. It was considered that the present study would contribute to a better understanding of the Computational Thinking concept. At the end of the study, certain suggestions were presented for further research.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.008 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".