Academic Achievement Research in High School: A Bibliometric Analysis
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
This research aims to determine the important role of academic achievement at the senior high school level. The method used in this study is the bibliometric method assisted by the Scopus database with a quantitative approach. Data were analyzed using VOSviewer software to create co-authorship, keyword and citation maps. The results of the study show that the number of articles published on the topic of academic achievement research has increased from the period 2003 to 2021 with an average publication (1.94 or 2 articles per year). The record was in 2011, which was the highest record among those years. Procedia Social And Behavioral Sciences is the most relevant source and produces many publications related to academic achievement. The country with the largest contribution in the publication of the Academic Achievement study is the United States with 21 published documents. Followed by the Iranian state with 6 documents, Australia with 3 documents, Canada-China-Spain and United Kingdom each with 2 published documents, as well as Brazil-Chile and Ireland with 1 published document. Findings, there are 120 writers who contribute to writing Academic Achievement articles as writers or colleagues of the author in 37 publications. It is known that Kuo Y.L. and Shah, M. is a productive writer with 2 documents each. Although there are no significant differences in the publication document per author, the two researchers are slightly higher than other writers who only publish one document. Future topic trends according to Vosviewer's visualization show that the most appearing topics are related to students, schools, colleges and education
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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 | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.107 | 0.284 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it