Home Variables as Predictor of Students’ Achievements in Social Studies in Junior Secondary Schools in Osun State, Nigeria
Bibliographic record
Abstract
The study investigated the relationship between home variables and students’ achievement in Social Studies. This is with a view of enhancing students’ better performance in Social Studies. The study employed the survey research design. The population consisted of the Junior Secondary School Students in Osun State. Stratified sampling technique was employed in selecting 500 students in five purposively selected local governments in Osun State. Two instruments titled “Home Variables Questionnaire” (HVQ) and “Social Studies Achievement Test” (SSAT) were constructed by the researcher to elicit information from the subjects. The two instruments yielded 0.71 and 0.84 respectively using Cronbach alpha. Seven out of the nine variables were found to be significant predictors of students’ achievement in Social Studies; (Sex β = 1.98; t = 4.93; p<0.05, age β=-1.16, t=-3.42; p<0.05, ethnic group β=0.51; t=-6.95; p<0.05, religion β=-2.86, t=-6.95; <0.05 parent living pattern β=-2.66; t=-2.92 p<0.05, number of fathers’ wives β=5.25; t=4.21; p<0.05, mother’s position among wives β=-3.39; t=-4.718; p<0.05) whereas the two other variables were not predictors of students’ achievement (mother’s no of children β=0.19; t=1.78; p>0.05, and position in the family β=0.01, t=0.010, p>0.05). Also, there was significant difference in male and female students’ achievement in Social Studies (t=9.991, p <0.05). Furthermore, there was a significant relationship between home facilities and students’ achievement in Social Students (r=0.180; p<0.05) whereas there was no significant relationship between birth order and students’ achievement (r=0.050, p>0.05). The study recommended among others that government should provide schools with adequate infrastructures and facilities that will enhance effective 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 | 0.001 | 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 | 0.001 |
| 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".