The Relationship between the Use of Social Networking Sites (SNS) and Perceived Level of Social Intelligence among Jordanian University Students: The Case of Facebook
Bibliographic record
Abstract
This study aimed to investigate Jordanian university students’ use of Facebook and their perceptions of their social intelligence as well as the relationship between students’ use of Facebook and a self reported measure of their social intelligence. The participants in this study were 282 students from different colleges in a Jordanian public university. For the purpose of the study, the researchers used cross-sectional survey design in which a questionnaire was administrated and collected in-class by number of faculty members, who agreed to have their classes participating in this study. The questionnaire aimed to collect data regarding students’ use of Facebook as well as the perceptions of their social intelligence. The analysis of the collected data showed that the majority of the students were active Facebook users. Participants’ perceptions of their level of social intelligence were positive and at moderate level. The findings showed significant association between Facebook use and perceived level of social intelligence among Jordanian university students. The current study disagreed with the common negative reputation, in Arab World, of the effect of Facebook on students’ social life. The current research study showed that the use of Facebook might benefit students’ social competencies and intelligence, through providing them with electronic platform that they can use to freely express themselves.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".