The Digital Divide and its Impact on Quality of Education at Jordanian Private Universities Case Study: Al-Ahliyya Amman University
Bibliographic record
Abstract
The study aimed to identify the Impact of digital divide in its dimensions (Technological dimension, Knowledge dimension, and Legislation & laws dimension) on the quality of education (University presidency's commitment to quality, Academic reputation and published scientific research) at Al-Ahliyya Amman University.To achieve this goal, the researcher used the descriptive and analytical approach, the study tool for collecting information and data was a questionnaire distributed to all employees, whose number is (630).The study questions and hypotheses were analyzed and tested through the Statistical Package for Social Sciences (SPSS) program. This study has found many results, the most important is:The digital divide in its combined dimensions has a statistically significant impact on the quality of education at Al-Ahliyya Amman University. It concluded with many recommendations, the most important is that a strategic plan be drawn up for universities to develop its infrastructure, improve and develop it continuously in order to enable digital access and bridge the digital divide among researchers and academics.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".