Exploring the use of Assistive Digital Resources in Enhancing Learning for Students with Intellectual Disabilities in Cross River and Akwa Ibom States, Nigeria
Bibliographic record
Abstract
Aim: Understanding how these digital resources are being utilized in special education contexts is essential to improving learning outcomes and bridging the digital divide for students with intellectual disabilities. The study examined the use of assistive digital resources to enhance learning for students with intellectual disabilities in Cross River and Akwa Ibom States, Nigeria. Five study objectives were stated to guide the research. Five research questions were formulated, and three hypotheses were stated. A literature review was conducted in line with the study variables. Method: This study adopted a descriptive survey research design. The area of the study is Cross River and Akwa Ibom States. The population of this study comprises all six special education and inclusive schools in Cross River and Akwa Ibom States—709 teachers, school heads, and education officers were directly involved in teaching or supporting students with intellectual disabilities—3,020 Students with intellectual disabilities (where possible, for observational data). A multi-stage sampling technique was used. A purposive sampling was used to select 4 LGAs, stratified sampling was used, and a simple random sampling technique was used. The instrument for data collection is a questionnaire, which was validated by experts in Measurement and Evaluation at the University of Uyo. The instrument was subjected to test reliability using the Cronbach Alpha reliability method. The test result revealed a reliability index of 0.81. Data from the questionnaire was analyzed using descriptive statistics (mean, frequency, percentage) and inferential statistics (Pearson correlation, independent t-test) to test the hypotheses. Results: The results revealed a significant relationship between the availability of assistive digital resources and their utilization level in teaching students with intellectual disabilities. There is also a significant relationship between the use of assistive digital resources and the learning outcomes of students with intellectual disabilities. There is a significant difference between urban and rural schools in the availability of assistive digital learning tools for students with intellectual disabilities. Conclusion: Based on the study's results, it was concluded that there is a significant relationship between the availability of assistive digital resources and their level of utilization in teaching students with intellectual disabilities. There is also a significant relationship between the use of assistive digital resources and the learning outcomes of students with intellectual disabilities. There is a significant difference between urban and rural schools in the availability of assistive digital learning tools for students with intellectual disabilities. Recommendation: Schools and disability support centers should implement peer-mentoring programs and anti-drug clubs that empower students to resist negative peer pressure.
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 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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".