A Comparative Study of the Quality of Teaching Learning Process at Post Graduate Level in the Faculty of Science and Social Science
Bibliographic record
Abstract
The study was intended to compare the quality of teaching learning process in the faculty of social science and science at University of Sargodha. This study was descriptive and quantitative in nature. The objectives of the study were to compare the quality of teaching learning process in the faculty of social science and science at University of Sargodha. Respondent, department and gender wise comparison was also done a sample of 92 students studying in post graduate programs and 30 teachers teaching to post graduate programs were taken from five social sciences and five science departments for data collection. Convenient sampling technique was used to select the sample. A questionnaire was developed and Pilot study was conducted to find out the reliability of the questionnaire. The reliability of the questionnaire was found to be 0.794. The results of the study proved that there is no significant difference between the quality of teaching learning process in Science and Social Science departments at University of Sargodha. It was also concluded that there is a significant difference between teachers and students responses about the quality of teaching learning process. The findings will help the teachers to improve their teaching and instructional plans. The findings of this study will be significant to the faculties of science and social science to improve their learning environment.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".