EFL Learning Styles Used by Female Undergraduate Students and Its Relationship to Achievement Level
Bibliographic record
Abstract
The aim of the study was to investigate the preferred learning styles of undergraduate Saudi students at King Khalid University, Saudi Arabia and to examine the influence of achievement level on the choice of learning styles. A total of 110 undergraduate students participated in the study. They were in their third year of study and were majoring in English. Data was collected by means of a questionnaire and by an English achievement test. Reid’s (1987) questionnaire was used to determine the students’ preferred learning styles. It identifies six learning styles referred to as perceptual learning styles; they are visual learners, auditory learners, kinesthetic learners, tactile learners, group learners and individual learners. An English achievement test was conducted to classify students according to their academic grade. The results showed the preferred learning styles used by undergraduate Saudi students at KKU. The order of the preferred learning styles based on sensory channels was as follows: visual, tactile, kinesthetic and finally the least frequent one was auditory, furthermore, the results revealed that students prefer individual learning more than group learning. Besides that, the findings also indicated that there was no statistically significant relationship between the learning styles and achievement level except with the group learning style which was used by students who got grade Excellent or Very Good. The study concluded by providing some possible implications of the study for English teachers.
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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".