Development in Computer Curriculum in Saudi Arabia: Systematic Review
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 paper seeks to provide an overview of publications in Saudi Arabia in the field of computer curriculum in K-12. We applied a systematic review methodology to analyze publications through 2021. Out of 225 publications initially identified, 110 were included based on the inclusion and exclusion criteria. The findings show that the number of publications in the field of computer curriculum in K-12 increased until 2018 but started to decrease in 2019. In addition, computer curriculum research trends focused on the high school stage, followed by the intermediate stage, and most participants were teachers and students. Moreover, the qualitative approach was frequently used in empirical studies, while most methodologies were surveys and semi-experimental. The results show that most of the papers’ suggestions involved training teachers and developing the curriculum. Finally, the study presents some recommendations for computer curriculum research. It suggests developing a research center in the education ministry to encourage researching the curriculum and presents other suggestions in detail.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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