Student Voice in an Extended Curriculum Programme in the Era of Social Media: A systematic Review of Academic Literature
Bibliographic record
Abstract
Student voice in this digital age and across higher learning institutions is increasing exponentially with the function of social media. Student voice provides a vibrant communication pathway to extended curriculum programme students in higher education institutions. Social media ensures active participation of extended curriculum programme students in generating views and ideas that define the higher learning environment and experience towards better learning conditions and outcomes. A systematic literature review was used in gathering scientific papers through trusted academic databases. The systematic literature review was conducted between the period of 1 April 2019 and 28 September 2019, by looking into the contents of articles covering the current research objectives. The study’s findings show that social media provides an effective and instant spread of the extended curriculum programme students’ voice across higher education learning institutions. It also allows the students in the extended curriculum programme to engage with each other and the institutional management promptly. Social media promotes extended curriculum programme students’ voice in reaching the right audience at the right time. The results of this study are key for extended curriculum programme students, lecturers, and university management in understanding and applying social media effectively and in bringing transformation to South African higher education institutions and beyond.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".