Trends and Research Issues of STEM Education: A Review of Academic Publications from 2007 to 2017
Bibliographic record
Abstract
Abstract STEM education (Science, Technology, Engineering, and Mathematic) research has been become more attractive area in science education for a decade. This study was aim to analyze research articles in a SCOPUS database and two journals which were not indexed in SCOPUS including Journal of STEM Teacher Education, and International Journal of STEM Education. The research articles during 2007 to 2017 were reviewed and analyzed according to the authors’ nationality, journals, STEM research topics. The research findings indicated that there were 56 published papers related to providing STEM learning activities in school setting, top three countries which published STEM papers over the decades were United States (46), Australia (2), Canada (2). Besides, the journal with the greatest number of published papers was Journal of STEM Teacher Education, with a total of 16 papers, and the second is International Journal of STEM education. The three popular topics which published in STEM papers were innovation for STEM learning, professional development and gender gap and Career in STEM, respectively.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.025 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".