Demotivating Factors Affecting EFL Learning of Iranian Seminary Students
Bibliographic record
Abstract
In the present study, an attempt has been made to determine the demotives affecting EFL learning of Iranian Islamic seminary students and also to distinguish the motivated and demotivated EFL learners in terms of their EFL learning as the major focus of this study. Fifty Iranian EFL seminary students were investigated using two validated questionnaires. First a modified version of The Attitude/Motivation Test Battery Questionnaire (AMTB) originally developed by Gardner (2004) was used to determine the degree of learners’ motivation. Second a modified version of Warrington's (2005) questionnaire was administered to determine the demotivating factors from the students' point of view. Then, the IOPT (Interchange Objective Placement Test) was administered to measure the general proficiency of the subjects under study. The comparison of the IOPT score means of the two groups revealed a significant difference in the results of IOPT of students with higher scores in the AMTB and those with lower scores. That is, the more motivated the students were, the higher their IOPT scores were. Furthermore, factors such as the improper method of English teaching, frequency of classes in a week, problems in understanding listening materials and lack of use of English in students’ real life were found to be the essential demotivating factors among Iranian seminary students. Having known the barriers of learning, the teachers and Islamic Propagation Office materials developers can organize their activities so that they would lead to better understanding of the lessons and improvement of teaching programs.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".