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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".