Connectivism in Learning Activity Design: Implications for Pedagogically-Based Technology Adoption in African Higher Education Contexts
Bibliographic record
Abstract
<p class="Style3">This paper examines the possible characteristics and the value of designing learning activities grounded in connectivism—an emerging learning theory. It is an exploratory attempt to connect the theory to the prevailing technology adoption archetypes used in African contexts with the aim of extracting influences that could shape pedagogical technology adoption in African higher education contexts. A reflection on the process of designing learning activities that employ <em>blogging</em> in an experimental training intervention provides a unique context in which to try and infuse connectivist principles while outlining the challenges that surface. The questions driving the argument in this paper include: What do connectivist perspectives offer learning activity design and practice? What can the prevailing technology adoption models used in African contexts offer to learning activity design? Can we combine connectivist perspectives and African-based technology adoption models to inform pedagogical technology adoption in African higher education contexts? These questions are exploratory and are based on one single subjective experience of the author. They are part of an argument put forward as a proposal which is yet to be tested in practice.</p>
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How this classification was reachedexpand
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".