Attitudes toward English among AL-Quds Open University Students in Tulkarm Branch
Bibliographic record
Abstract
The aim of this study is to identify the attitudes toward English among AL-Quds Open University students inTulkarm Branch, Palestine. To achieve this purpose, the researcher used a questionnaire composed of 30 itemsdistributed to 70 male and 110 female students in four faculties: Education, Social Development, AdministrativeSciences and Technology and Applied Sciences in AL- Quds Open University, Tulkarm Branch. These students arein different study levels (years). This study was conducted during the first semester of the academic year 2014-2015.The researcher used different statistical procedures which fit the collected data. The results of the study revealed thatmost of the students in AL- Quds Open University, Tulkarm Branch have positive attitudes towards English.Moreover, the attitude of females toward English is more positive than the attitude of males. There are significantdifferences in attitudes towards English among students due to academic level. There are no significant differences inattitudes toward English among students due to faculty. Based on the results, the researcher recommends thefollowing: First, universities are requested to offer a reasonable number of English communication courses to givestudents a chance to practice and improve their language so as to make the language favorable for them and have agood attitude toward it. Second, teachers are required to encourage students to get engaged in co-curricular Englishactivities in special meetings among themselves to use English in speaking and writing.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".