Attitudes of Students and Faculty Members at Israa University towards Distance Learning in Light of the Corona Pandemic
Bibliographic record
Abstract
This study aimed to identify students' attitudes and faculty members at Israa University towards distance learning in light of the Corona pandemic. A questionnaire was developed that included two pictures (student photo/faculty member photo). Each image in the questionnaire consisted of (30) items distributed into three areas: Learning and teaching, assessment and testing, and learning and communication management, where acceptable coefficients of validity and reliability were achieved for the two questionnaire images, and applying them to an available sample of Al-Isra University students and faculty members, consisted of (365) male and female students, and (119) faculty members during the first semester of the academic year (2020-2021 AD). The study results revealed that the attitudes of students and faculty members at Israa University towards distance learning in light of the Corona pandemic came at a medium level. The presence of statistical differences in students' attitudes at Israa University towards distance learning due to the gender variable and the differences were in favor of males. There were no statistically significant differences in Al Isra University students' attitudes towards distance learning due to the vari of college. The variablee results also revealed no statistically significant differences in the faculty members' attitudes at Al-Isra University towards distance learning due to the variable of academic rank. In light of the study results, the researchers recommended developing the values of self-awareness and twenty-first-century skills such as self and continuous learning, and interest in developing distance learning applications and platforms, and conducting future studies on distance learning and the effectiveness of educational platforms and electronic applications in light of various variables.
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 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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".