The Effect of Using Prezi on Al Zaytoonah University Students’ Performance in French Language Reading Skills
Bibliographic record
Abstract
The purpose of this study is to investigate the effect of using Prezi on Al Zaytoonah students’ performance in French Language reading skill. To achieve the purpose of the study, a pre/post-test was constructed to measure students’ performance in French language reading skill. The sample of the study comprised 128 students from Al Zaytoonah University and was distributed into two sections, which were selected purposefully. The sample of the study was distributed into two groups (one experimental and one control groups). The experimental group’s students were taught the reading skill using Prezi while the control groups’ students were taught using the traditional way. The sample of the study was 64 students in the experimental group and 64 students in the control group. Those groups were distributed into two purposefully selected sections in public schools in Amman. The results of the study showed a variance in the means of the achievement test according to group, it also showed that there were statistically significant differences on the achievement test due to the Strategy variable. There were statistically significant differences between using Prezi Strategy and the Current Strategy in favor of the Prezi Strategy, and there was no statistically significant difference in the students’ achievement due to gender. There was no statistically significant difference due to the interaction between gender and group. The researchers recommend that researchers focus on new teaching strategies and conduct more studies related this topic. They also recommend that other researchers conduct studies and focus on the role play strategy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".