Utilization of Social Media Networks for Teaching Effectiveness in Tertiary Institutions of Cross River State, Nigeria: Implications for Learning and Practice in an Environment of Students with Intellectual Disabilities
Notice bibliographique
Résumé
Aim: This study examines the use of social media networks for teaching effectiveness in public tertiary institutions of Cross River State, Nigeria: Implications for learning and practice in an environment of students with intellectual disabilities. Four study objectives were stated to guide the research. Four research questions were formulated, and one hypothesis statement was made. A literature review was carried out based on the variables under study, as research gaps were also stated. Method: The study utilize7d the descriptive survey research design. The study population comprised 2,800 academic staff of public tertiary institutions of Cross River State. The sampling techniques adopted for this study were the stratified random sampling technique and the accidental random sampling technique. A total sample of 560 respondents was selected from 2,800 academic staff of public tertiary institutions in Cross River State using 20% of the entire population. A validated 25-item four-point modified Likert scale questionnaire was the instrument used for data collection. The face and content validity of the instrument was established by experts in Test and Measurement from the University of Calabar, Calabar-Nigeria. The reliability estimates of 0.89 for the instruments were established using the Cronbach Alpha method. A descriptive analysis of frequency count, percentages, mean, and standard deviation was used to test the research questions. Results: The results obtained from the data analysis revealed that there was a statistically significant joint relationship between the predictor variables (Twitter, Facebook, WhatsApp) and teachers' teaching effectiveness in tertiary institutions in Cross River State, Nigeria. Conclusion: From the findings of this study, one can conclude that there was a statistically significant joint relationship between the predictor variables (Twitter, Facebook, WhatsApp) and teachers teaching effectiveness in tertiary institutions in Cross River State, Nigeria. Key statistical measures, including mean scores, standard deviation, and inferential tests such as Multiple Linear regression, indicate a positive correlation between social media utilization and improved instructional delivery. The findings suggest the need for inclusive digital strategies to maximize learning outcomes, emphasizing the importance of accessible and adaptive teaching approaches. These insights have critical implications for policy formulation, curriculum design, and pedagogical practices in higher education. Recommendation: Based on the result of the study, it was recommended that since the utilization of social sites by teachers improves teaching effectiveness, learning institutions should enact regulations that will govern the proper and positive use of the various types of social media sites among teachers in institutions to promote teachers' teaching effectiveness.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 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) | 0,003 | 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 ».