Factors Affecting the Quality of English Language Teaching in Preparatory Year, University of Jeddah
Bibliographic record
Abstract
Several Universities in Saudi Arabia have recently made it their priority to pursuit excellence in effective EFL teaching-learning starting from the Preparatory Year Program (PYP). That is due to the rapid expansion of English as a lingua franca in tertiary education especially in science and technology, scientific and educational publication, technology, internet communication, etc. The present study will examine the current situation in EFL teaching and learning to identify the factors affecting the quality of English language teaching in the PYP at Jeddah University. When studying quality in EFL teaching, the concentration is usually put on the teacher where in fact the success of the operation is collaboration between three major constituents of the program triangle, the learners, the teachers and the institution. Therefore, these three constituents were asked to first identify what they think is important in regards to the quality of the EFL program, and what impedes achieving its goals. In order to identify and analyze the factors, this study applied the following survey: Quality in Language Teaching for Adults developed by Grundtvig Learning Partnership (2009-2011), on teachers, learners, and administrators. Slight variations in wording of the survey statements was implemented in order to suit each group. For data analysis, SPSS software was used. Recommendations and further fields of study presented were based on the findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".