Personal Variables and Students' Academic Performance of Virtual Classroom Learners of Social Studies in Secondary Schools in Uyo Local Government Area, Akwa Ibom State
Bibliographic record
Abstract
The study examines the factors of age, gender and location of social studies students and their performance on a virtual classroom platform. The study adopted the quasi-experimental design. A specific class arm of 50 Junior Secondary School (JSS) 3 students that were treated to a social studies lesson on family. The researcher developed a Social Studies Achievement Test (SSAT) with a reliability coefficient of .861; Cronbach Coefficient Alpha Statistics was administered to elicit student performance. The data collected were grouped based on age, gender and location. Mean (X ) score analysis indicated variance in performance based on personal factors, but, there was no significant correlation with academic performance of social studies students when taught using a virtual classroom platform, It was concluded that age and gender significantly influence students' academic performance in social studies using virtual classroom platform. The state government and education stakeholders adopted a virtual classroom strategy and teachers should be trained to use virtual classroom platforms for instruction for optimum educational effect in the study area.
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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 | 0.002 |
| 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".