Exploring the use of Assistive Digital Resources in Enhancing Learning for Students with Intellectual Disabilities in Cross River and Akwa Ibom States, Nigeria
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».