The Attitude of Students of The University of Jordan Towards The “Social Media Networks” Subject
Bibliographic record
Abstract
This study aims to search the students’ attitudes in The University of Jordan towards the “Social Media Networks” subject, and in order to reach the study’s goals, a descriptive surveyor methodology was adopted, the study sample consisted of (198) students of bachelor degree who enrolled the subject for the second semester; academic year 2014/2015 from both genders in a random cluster way. A tool was designed to measure the students’ attitude towards “Social Media Networks” subject; the tool paragraphs targeted five dimensions: course content, faculty members, school applications, evaluation methods and laboratories offered by the university. The study results showed that the students’ attitude towards “Social Media Networks” subject, were positive in general levels and in medium degree. The course content and the school applications obtained the highest average respectively, followed by laboratories offered by the university and evaluation methods, faculty members took the last position. The results also show that there are no differences of statistical indications regarding the gender, educational level or experience options in the use of networks while a difference occurred regarding faculty’s type in favor of scientific faculties.
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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 | 0.001 | 0.002 |
| 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".