Higher Education Challenges in the Era of Covid-19, from the Perspective of Educators and Students (Ghana, Georgia and Pakistan Cases) – A literature 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
For the last three years, the entire world has faced a colossal phenomenon - the covid-19 pandemic. All sectors and areas of life have been affected, forcing rapid and radical changes towards adaptation in its wake. Inevitably, the unexpected pandemic’s mark and impact on education is more severe and longer lasting than imagined. It disrupted education provision at an unprecedented scale. This article is intended as a review of literature on the experience of different countries and education systems during the Covid-19 pandemic. Based on the analysis of the existing literature and research on this issue, from the perspective of educators and students, including the experience of different countries around the world, the pandemic has had a great impact on higher education and pushed it to digital transformation, implicitly overcoming important challenges. The review uses particular examples of higher education in the era of Covid-19 in Georgia, Ghana and Pakistan, exposing measures taken to continue educating in spite of the pandemic. However challenging this phenomenon proved to be, it equally gave way to enormous opportunities for creativity within progress. Discussed are barriers that students and academics faced during online teaching-learning, the pros and cons of online teaching-learning, as well as the quality of teaching-learning and the state of preparedness for future education.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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 it