The Effectiveness of Using Facebook on the Ninth Grade Students’ Achievement of English in Jordan
Bibliographic record
Abstract
This study aimed at investigating the effectiveness of using Facebook on the English language achievement of the ninth grade students in Jordan. The study was applied in Asia Secondary School for Girls in Amman in the first semester 2014/2015, studying the effect of variables such as teaching method, the cumulative average and the interaction between them. The sample consisted of 68 students divided into two groups. One of them was an experimental group 33 students studied by the Facebook way and the other was control group 35 students studied the same unit in the traditional way. The study used two tools: First: educational material. Second: A comprehensive and reliable test was designed and applied as a pretest to both groups to ensure that they are equal; also they applied the same test after the completion of the study unit. The results showed statistically significant differences between the mean of students in the experimental group studied by the Facebook method and the mean of the control group, in favor of the experimental group. The results also showed statistically significant differences between the mean of students due to the cumulative average. On the other hand, there were significant differences regarding the interaction between the method and the cumulative average. Finally the researchers suggested some recommendations.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".