A VISUALIZATION ANALYSIS ON THE RESEARCH FRONTS AND KNOWLEDGE BASE OF EDUCATIONAL GAMES
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
A visualization analysis is carried out by means of CiteSpace II on the documents of educational games in SCI, SSCI, and A&HCI between 2003 and 2013. Important journals, authors, institutions, countries, key words, and key papers are identified. The research fronts and knowledge base of this field are discovered. It reveals that this field is still at its initial stage. It needs to absorb knowledge from education science, psychology, behaviour science, as well as cognitive science, etc. At the same time, it needs to do deep and extensive theoretical and applied research so as to form its own unique knowledge system gradually. It also demonstrates that one should guarantee the quality of input data and verify pivotal points while using CiteSpace II.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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