Investigating the English Language Needs of the Female Students at the Faculty of Computing and Information Technology at King Abdulaziz University in Saudi Arabia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the field of computer science, specific English language skills are needed to facilitate the students’ academic progress. Needs analysis is generally believed to be an important element in ESP/EAP context because it enables the practitioners and curriculum designers determine the learners’ needs in a particular academic context. In this regard, this paper, adopting a quantitative research design, reports on a survey conducted to investigate the English language needs of the female students studying in the Faculty of Computing and Information Technology (FCIT) at King Abdulaziz University (KAU). The study aims at identifying the students’ perceptions about the importance of the English language skills, the frequency of using those skills, their ability levels in performing such skills, and their preferences regarding the English language course. The participants in this study are 135 female undergraduates who are studying at the third, fourth, and fifth year at the FCIT, during the academic year 2013-2014. The study identifies the students’ English language necessities, lacks, wants, and their perceptions of the current English course. The paper concludes with several pedagogical implications which seek to improve the current course structure and contents so as to cater for the students’ academic English language needs.
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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 | 0.001 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it