A Comparative Study for Understanding the Problems Faced by Male and Female Undergraduate Students in Acquisition of Speaking Skill Competence, While Learning English as a Foreign Language in Karachi, Pakistan
Bibliographic record
Abstract
Pakistan is one of the developing countries where English is taught from primary to graduation level as a compulsory subject, but it is observed and quoted by a number of researchers in their research that the EFL learners are found weak in one of the basic language learning skill i.e., speaking. Keeping in view this issue of learners this research study was conducted to investigate the types of difficulties the male and female learners of EFL face in acquisition of speaking skills competence and to get their suggestions, which they expect from teachers or authorities to do in their endeavors of improving speaking skill competence in overcoming the difficulties faced by them. The sample consisting of 120 undergraduate students from 10 universities was selected. A questionnaire having 10 close-ended and 05 open-ended items was distributed among the participants. The analysis of quantitative data suggests that comparatively males give more importance to skill for success in career than female, moreover they are more hesitant than females because of lack of confidence, afraid of mistakes and of being criticized, etc. while analysis of qualitative data reveals that only 27% participants are satisfied by their speaking skills competence, 51% were unable to reason what is important for mastering speaking skills, 20% said, they are unable to speak because of lack of confidence, 38% feel speaking skill is the most difficult skill, while 35% favored classroom activities for improving speaking skill competence. On the basis of findings from the suggestions of the participants, it is concluded that if teachers arrange classroom activities, then there will be a positive impact on students’ confidence as activities will improve the speaking skill competence of the learners.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".