Development of Training-Based Spelling Strategies for Female EFL Students: Case Study of a Saudi University
Bibliographic record
Abstract
Spelling is a major challenge for EFL learners and students in their process of learning the English language. The aim of this study is to investigate the effectiveness of a training program based on certain spelling strategies to help EFL learners improve their spelling achievement. To do this, the differences between the experimental group and the control group, before and after the treatment, were examined. The participants were university students who were selected from a large sample and divided, and studied, in two experimental and control groups based on a spelling production pre-test. The first aim of this study is to examine whether significant differences occurred in spelling-related language learning strategies and English language spelling post-test between the control and experimental groups. The second aim is to examine whether significant differences exist between the mean scores of pre- and post-test of the English language spelling test and spelling-related language learning strategies. Spelling-related language learning strategies were measured using Kristine F. Anderson’s “spelling survey” strategies (1987). The spelling test and the spelling program were both prepared by the researchers. The research was conducted for three months, including the proposed program. Data from pre-post instruments was used to investigate the impact the intervention had on EFL in the development of spelling and the use of spelling strategies to learn English. Data from pre- and post- test instruments showed that there were statistically significant differences between the experimental group and the control group in the post-test spelling test as well as the spelling strategies questionnaire. The implemented treatment resulted in a significant improvement in the spelling skill of the experimental group. The results also revealed statistically significant differences between the pre-test and post-test results for the experimental group in the spelling test and the spelling strategies and also the fact that the experimental group improved in spelling skills after their participation in the program, as can be seen in the post-test. In light of these results, the study proposes a number of procedural recommendations that may contribute to raising awareness regarding the importance of teaching spelling strategies for EFL students.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".