Deterritorialising to Reterritorialising the Curriculum Discourse in African Higher Education in the Era of the Fourth Industrial Revolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Fourth Industrial Revolution is upon us, and it comes with implications for the higher education curriculum and organisations within Africa. Technology that was ubiquitous in previous decades, is now becoming obsolete. Artificial intelligence and digitization, which are features of the Fourth Industrial Revolution, are now the order of the day. Organisations are moving with such technological advancement by adopting newly created technologies of the Fourth Industrial Revolution. Without doubt, the currently used curriculum in Africa is obsolete; and does not capture the changes being ushered in by the Fourth Industrial Revolution. Therefore, the higher education curriculum must be responsive to the Fourth Industrial Revolution, as this will prepare students in Africa for the challenge ahead. This study theorises on, and has concluded, that deterritorialization and reterritorialization are useful in making the African higher education responsive to the curriculum. The study recommends the introduction of Science, Technology, Engineering, and Mathematics (STEM) education into the African higher-education curriculum in Africa. STEM will produce students who are technically savvy, helping students in Africa to acquire the needed skills to perform seamlessly in organisations operating within the Fourth Industrial Revolution era.
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.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it