The Impact of Diglossia on the Language Development and Educational Achievement of Saudi Students in Primary Schools
Bibliographic record
Abstract
Arabic is a diglossic language. Two variants of Arabic are widely used. H (the High variant) is Classical Arabic, now referred to as Modern Standard Arabic (MSA). The L (Low) variant is the colloquial dialects (DA), which are mostly spoken. The H variant is used in education, press, and other formal correspondence. The Low version is associated with informal contexts. Interestingly, the two versions are completely different from each other in terms of vocabulary, syntax, and even structure. Given the social and cognitive aspects of the language, children go to primary schools with almost no knowledge of MSA. Despite the prolific literature on the linguistic features of Arabic diglossia, very little has been done on the impact of diglossia on academic and educational achievement. In light of this argument, this paper seeks to investigate the teachers' perceived impact of diglossia on the language development and educational achievement of primary school students from a linguistic and anthropological perspective. Interviews were conducted with selected primary school teachers from the Riyadh region of Saudi Arabia to elicit their opinions and perception on how diglossia should be tackled when students arrive in a classroom. The data collection tool was an interview comprising close and open-ended questions. The interview questions explored three areas: teachers’ perception of diglossia; perceived challenges that students faced with teaching and study material; and how teachers addressed these challenges. Findings indicate that diglossia poses serious sociolinguistic challenges to most young learners in Saudi schools. Both teachers and learners face difficulties in using only MSA in classrooms as the formal and official medium of instruction in Saudi schools. It is recommended thus the colloquial and vernacular dialects (L varieties) of Arabic should be integrated into the instruction mode to reflect the linguistic reality of the Arab countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".