Motivation to Learn English Language: A Study of Shah Abdul Latif University, Khairpur, Sindh
Bibliographic record
Abstract
The present study aims to investigate the motivational factors which are directly involved in learning English language among Bachelor of Science (B.S) first year undergraduate students of Institute of English Language and Literature, Shah Abdul Latif University, Khairpur, Sindh Pakistan. The study focuses on intrinsic and extrinsic motivation factors, which motivate students to learn English language. The questionnaire has been administered among students (N=70) which are based on 30 Likert scale items. Attitude Motivation Test Battery/AMTB (Gardner, 2004 English version) has been used in this regard. SPSS has been used to quantify the data. The semi-structured interview has been conducted by using purposive sampling for in-depth study from (N= 6) students. The results reveal that the students have extrinsic reasons as dominant factors for motivation to learn the target language. The dominant extrinsic factors which were investigated among the students are to get a good job and to qualify exams. The intrinsic factors such as learning English for developing self-image and communication skills in English with proficiency in their daily routine work are responsible for motivating students to learn English language.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 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) | 0.002 | 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".