An Evaluative Study of “We Can1” English Textbook in Saudi Public Elementary Schools
Bibliographic record
Abstract
This study aimed at analyzing and evaluating the content of We Can1, which is published by Mc Graw Hill, edition 2021 for the first grade as a school curriculum for Saudi public schools. It is conducted in the public elementary schools in the Kingdom of Saudi Arabia, Riyadh. We Can1 is chosen for the current study, because it is used in the public elementary schools as an English curriculum. Thus, a deep evaluation of the textbook content is needed. However, the other elementary grades are using other We Can series. The purpose of the current study is to examine the content of We Can1 according to the curriculum layout and design, activities, and English skills. It also seeks to scrutinize the cultural appropriateness of We Can1 in association with the EFL Saudi students’ culture. Moreover, the study focuses on We Can1 curriculum to measure the extent in which it meets the students’ needs. Besides, the interpretation of the objectives of We Can1 as a curriculum in the learning process somehow. The Qualitative Content Analysis (QCA) is used for the current study as a research method to help the researcher in analyzing and evaluating the content. The researcher found that We Can 1 is an effective material in respect to layout and design. Moreover, all the English skills are included except reading skills. The researcher also concluded that We Can1 is culturally appropriate for EFL Saudi students in public elementary schools.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".