Trends of Graduate Theses with the Subject of Education and Training Conducted on Creativity
Bibliographic record
Abstract
The aim of this research is to examine the trends of the studies that address the education-training dimension of creativity in Turkey. The research was conducted using a qualitative research pattern. The data was collected and analyzed through document analysis. In the analysis of the data, the thesis analysis form developed by the researchers was used. One hundred and forty-five graduate theses studied between 2005 and 2019 in the field of education, which were allowed access by their authors, constitute the study group of this research. 114 of these works consist of graduate theses and 31 of them consist of doctoral theses. The graduate theses in the Council of Higher Education database were examined under a total of 10 titles according to their distribution over the years-educational levels, university distributions, institute distributions, branch distributions, methods and sub-methods, data collection tools, sampling/study groups, sampling methods, education level of the study group and thesis titles. As a result of the research, it was observed that although studies addressing the educational-educational dimension of creativity have increased at a certain level over the years, they are not at the desired point and have not been studied adequately. In addition, it was determined that the studies carried out in terms of the discipline, the methods used and the variety of topics studied had similarities, that no studies on creativity were conducted in some departments, that the study group usually consists of a single level of education, that this situation does not allow to look at creativity from a broad perspective, and that there are many aspects of creativity that have not been studied for those who will work in the educational dimension.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".