Strategies for Learning Arabic from Home at Islamic Boarding Schools During the Covid-19 Pandemic
Bibliographic record
Abstract
The current pandemic situation, which requires the learning process to be carried out from home online, makes it a challenge to learn Arabic. Initially, this policy was very much accepted by learners and educators with excitement. However, the reality is that this policy makes the learning process difficult to implement optimally. This research uses a qualitative descriptive method by collecting all data sources. Data source collection is carried out by interviewing teachers and students and documentation. Qualitative studies are carried out to analyze the problems faced by students and offer several possible recommendations to improve the quality of teaching Arabic as a foreign language based on student perceptions, taking into account the social context experienced during the learning process of the 2020-2021 academic year. The purpose of this research is to find problems that are being faced by students and educators in Islamic boarding schools during the pandemic and find the right solution to solve the problem so that the right strategy can be found for learning Arabic during this pandemic for a number of Islamic boarding schools.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".