RELATIONSHIP BETWEEN SOCIAL MEDIA ADDICTION AND ACADEMIC PERFORMANCE AMONG UNDERGRADUATE STUDENTS OF AHMADU BELLO UNIVERSITY, ZARIA
Bibliographic record
Abstract
The study examined relationship between social media addiction and academic performance among undergraduate students of Ahmadu Bello University, Zaria. The study was guided by two null hypotheses. Correlational research design was employed in the study. The population of the study comprised of 5,490 undergraduate students of the Faculty of Eucation, Ahmadu Bello University, Zaria. The study has a sample of 357 students in congruence with Research Advisors (2006). Social Media Addiction Student Form was the instrument for data collection while students’ CGPA was used as a measure of their academic performance. The hypotheses were tested using Pearson Product Moment Correlation Coefficient (r) and t-test statistics. The findings of the study revealed that significant inverse relationship exists between social media addiction and academic performance r=-.755; p=.001 and significant difference exists between social media addiction of male and female undergraduate of Ahmadu Bello University, Zaria with the mean of 79.40 for female students and 50.48 for male student, p=.005 indicating female students having higher social media addiction. It is recommended that undergraduate students should be sensitized on negative impact of social media academic performance.Gender Difference in Internet Use and Internet Problems among Quebec High School Students
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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 | 0.000 | 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 | 0.000 |
| 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".