Measuring social and psychological factors through home-study setting towards improved academic performance
Bibliographic record
Abstract
This study determined the relationship among social and psychological factors through home -study setting of Grades 6 pupils in Liciada Elementary School, in Bustos, Bulacan during the first quarter of School Year 2022-2023. The main objective is to find the implications of social and psychological factors on the achievement of pupils and finding benefits of home-study setting. The method used in the study was t-test and pearson (r). Using descriptive correlational research as research design in the total population of 167 Grade 6 pupils as respondents of the study, the answers to the problems raised in this study were summarized as follows: The number of siblings and socio-economic status has a significant relationship between pupils’ demographic profile and social factor in home study setting with p-values 0.011 and 0.000 which is less than the level of significance at 0.05. Social factor in home-study setting and respondents’ academic achievement has a significant relationship with p-value of 0.001 which was less than the level of significance at 0.05. On the other hand, psychological factor in home study setting and respondents’ academic achievement has no significant relationship with p-value 0.220 which was greater than the level of significance at 0.05. The pupil’s achievement on this present research will be useful to the parents and policymakers in finding the benefits, policy framing, and advantages of home-study.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".