AFTER-SCHOOL ACTIVITIES AND SECONDARY STUDENTS ACADEMIC PERFORMANCE IN SELECTED SCIENCE-RELATED SUBJECTS IN YALA LOCAL GOVERNMENT AREA OF CROSS RIVER STATE, NIGERIA: CURRICULUM IMPLICATION
Bibliographic record
Abstract
The study focused on after-school activities and secondary students’ academic performance in selected science-related subjects in Yala Local Government Area of Cross River State, Nigeria: Curriculum implication. The research design adopted for the study is the survey design and the population of this study comprised all Senior Secondary School One (SSS1) students in selected public Secondary schools in Yala Local Government Area. The population stood at 3,201, with males 1, 501 and 1, 700 females in ten (10) selected Secondary schools in the area. The simple random sampling technique was adopted to select the respondents in the study area thus, (111 males and 119 females). The instruments used for data collection were two questionnaires titled After-School Activities Questionnaire and Student’s Academic Performance Test in Chemistry, Physics, and Mathematics (ASAQAPTCPM), designed by experts in the chosen field of study, and the reliability was established with spilt-half reliability techniques result showed a high correlation value of 0.87 to 0.89 and this was considered high enough to use the instrument for data collection. The hypotheses formulated to guide the study were tested using the appropriate statistical technique at 0.05 level of significance using simple linear regression analysis and the findings revealed that engagement in playing after school, engagement in homework, and engagement in extra moral classes significantly predict students’ academic performance in Chemistry, Physics, and Mathematics. It was recommended that parents should encourage their children by providing the needed learning materials like textbooks, prompt payment of school fees, school uniforms, and engagement in extra-curricular activities to facilitate playing activities in the learning process, such as sports, drama music, scouting, dance, and various clubs which will promote harmony in learning.
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 | 0.001 | 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".