Bibliographic record
Abstract
The study looked into descriptive research to evaluate the existing conditions of the science laboratories in the government secondary schools of Hyderabad District. This study is concerned to identify the problems faced by the science teachers and students in teaching and learning of science due to non-functionality of science laboratories in government secondary schools. The study focused on the objectives; to find out the availability of facilities in the laboratories of government secondary schools for science teachers and students, to assess the current competencies of science subjects’ teachers in practical/laboratory work in government secondary schools and to find out the problems faced by science subject teachers in carrying out practical work in laboratories. The population for the research project comprised of science teachers, science students, headmasters and science lab staff of government secondary schools of Hyderabad District. The sample was randomly selected from four talukas (sub-divisions) Data was collected through questionnaire, interviews and observations. Both quantitative and qualitative data analysis approaches were used for data analysis. Main findings of the study were; there existed no good science laboratories in the government secondary schools, laboratories were not fully functional and science practicals seldom conducted, proper funds were not provided for the purchase of apparatus, teachers were not trained to conduct practicals, shortage of technical staff was also observed. science teachers should be trained to conduct science practicals, proper funds should be provided to the schools for purchase of science apparatus, shortage of technical staff should be overcome.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.889 | 0.884 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".