Obstacles in Distance Learning at the Secondary Level According to the Class and Gender Variables in the Light of Corona Pandemic, from the Students' Point of View, in Directorate of Education / Tafila Region
Bibliographic record
Abstract
The study aims to identify the obstacles that face students in the distance e-learning according to the class and gender variables in the Corona pandemic in Tafila region in Jordan. The study population consists of a sample of 200 high school students who were selected randomly. A questionnaire consisted of two main areas was distributed to the study sample. The results reveal that there were no statistically significant differences at the level of significance (0.05 0.0α) between the estimates of the study sample for the obstacles of technical technologies and the e-learning infrastructure distance, and the student interaction for e-learning. In addition, the study shows that there were no statistically significant differences at the level of significance (0.05 0.0α) between the estimates of the study sample of the obstacles to distance learning in secondary level according to the class and gender variables in the Corona pandemic. The study recommends to hold workshops for male and female teachers on the ways to deal with remote e-learning, and to improve the work of Darsak platform in cooperation with teachers within the field. The study also recommends to conduct studies on continuity of work through learning and e-learning and that each school has to have its platform.
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.
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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".