Psycho-social Factors as Predictors of Disabled Students’ Academic Achievement in General Studies at the University of Ilorin, Nigeria
Bibliographic record
Abstract
For the Nigerian government to achieve a united, strong, and self-reliant nation, some variables like the socio-economic status of the parents, costly textbooks, the problem of feeding allowances for students, the low motivation of teachers due to low salaries, expensive tuition fees, the unemployment of qualified subject teachers, the lack of teaching aids, insecurity, and so on needs to be considered. Above all, psycho-social variables on the part of the students equally needs to be considered. In line with this, the researcher deemed it fit to investigate psycho-social factors as predictors of disabled students’ academic achievement in General studies at the University of Ilorin. The study adopted a descriptive survey research design. The population for this study was all disabled University of Ilorin undergraduates. A questionnaire was used for data collection. Demographic characteristics of the respondents were described using percentages and the research question generated was answered using mean and rank order. All of the hypotheses formulated for this study were tested using the Mean, Standard Deviation, t-value and ANOVA. The hypotheses were tested at a 0.05 level of significance. The findings of this study revealed that there were no significant differences in the influence of psycho-social factors on disabled students’ achievement in General Studies on the basis of gender. In addition, findings revealed that there was no significant difference in the influence of psycho-social factors on disabled students’ achievement in General Studies on the basis of age. It was also found that there was no significant difference in the influence of psycho-social factors on disabled students’ achievement in General Studies on the basis of educational level. Furthermore, findings revealed that there was no significant difference in the influence of psycho-social factors on disabled students’ achievement in General Studies on the basis of the mode of entry. Hence, it was recommended that counselling units in the university should be made more accessible and friendly to disabled students so that they can easily visit the centre for guidance. With regard to their physiological, psychological and social development, more publicity is needed to create awareness for the stakeholders. Government and school management should ensure harmonious relationships for every disabled student regardless of their level or class. Students should not see age as a barrier for interacting with their colleagues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".