Adaptive Teaching Strategies in the Post-Pandemic Era: Navigating the Shift to a ‘New Normal’ in Language and Linguistics Education With Case Studies From Oman and the UAE
Bibliographic record
Abstract
The pre-pandemic era saw the integration of educational technology into traditional classroom pedagogy as a supplementary tool, enhancing hands-on and interactive teaching approaches. While there was a general acknowledgment that information technology was transforming learning, its centrality in education was not fully realized until the COVID-19 pandemic. During the pandemic, the physical presence of learners was replaced by virtual engagement, compelling both educators and students to adapt to a new learning paradigm. This shift necessitated the development of adaptive teaching strategies to preserve the interactive, collaborative and inclusive nature of conventional classrooms while elevating the role of educational technology from a peripheral to a central position. In the post-pandemic world, educational practices are divided between those who favor a return to traditional, human-centered models and those who advocate AI-integrated, technology-driven learning. This study examines the teaching of language and linguistics before, during, and after the pandemic, focusing on approaches in Oman and the United Arab Emirates (UAE).
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How this classification was reachedexpand
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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".