Utilization of Digital Resources for Learning by Students with Intellectual Disabilities in Southern Nigeria
Bibliographic record
Abstract
Aim: This study investigated the use of digital resources for learning among students with intellectual disabilities in Southern Nigeria. Method: A descriptive survey design was adopted. The study involved 530 participants, including special education teachers, school administrators, and caregivers across six states in Southern Nigeria, selected through a multi-stage sampling technique. Data were collected using a structured questionnaire (DRUSEQ) with a reliability coefficient of 0.80. Descriptive statistics and Pearson's Product Moment Correlation were used for analysis. Results: Findings revealed moderate availability of digital tools, particularly Smart Boards and text-to-speech software, but low and inconsistent usage among students with intellectual disabilities. Infrastructural and financial constraints were key barriers, with teacher training and student motivation also playing roles. While most stakeholders valued digital tools, a notable minority expressed skepticism. A statistically significant but weak positive relationship was found between digital resource usage and educators’ perceptions of student learning outcomes. Recommendation: Greater investment is needed to provide assistive digital tools and address systemic issues such as funding, internet access, and technical support in special education settings.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".