The L2 Motivational Self System and Religious Interest among Saudi Military Cadets: A Structural Equation Modelling Approach
Bibliographic record
Abstract
This study surveyed the English language learning motivation of 384 Saudi military cadets. The researcher applied structural equation modelling to analyse how a set of motivational factors interact in shaping the motivation to learn English of this under-researched context. The study found that the language learning effort was determined by the students’ attitudes towards the language learning process as well as their Ought-to L2 Self. However, the Ideal L2 Self contributed to the language learning effort indirectly with the mediation of the students’ attitudes towards the language learning. The influence of the students’ parents was salient as the parental encouragement contributed to the students’ Ought-to L2 self as well as their language learning attitudes. Finally, the students’ perception of the benefit of learning English for religious purposes (religious interest) contributed to the enjoyment derived from the process of language learning, which in turn impact the effort they invest in their language learning.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".