The Effect of a Computer Program Based on Analysis, Design, Development, Implementation and Evaluation (ADDIE) in Improving Ninth Graders’ Listening and Reading Comprehension Skills in English in Jordan
Bibliographic record
Abstract
The study aimed to assess the effectiveness of a computer program based on Analysis, Design, Development, Implementation and Evaluation (ADDIE) Model on the achievement of Ninth Graders’ listening and Reading Comprehension Skills in English. The study sample comprised 70 ninth graders during the second semester of the academic year 2016/2017. The selected students were distributed into two groups: an experimental group and a control one. A computer program based on Analysis, Design, Development, Implementation and Evaluation (ADDIE) was prepared, and a 40-item listening test in addition to a 40-item reading comprehension test were designed according to modules outcomes which were presented in (Teachers’ Book Action Pack 9). Validity and reliability were ensured for both tests. The results showed a statistically significance difference at (α=0.05) between the mean scores of the control compared to the experimental group on both tests (listening achievement test and reading comprehension achievement test) due to the independent variable implementing a computerized program based on ADDIE Model in favor of the experimental group.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".