Dialogue and connectivism: A new approach to understanding and promoting dialogue-rich networked learning
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
Connectivism offers a theory of learning for the digital age that is usually understood as contrasting with traditional behaviourist, cognitivist, and constructivist approaches. This article will provide an original and significant development of this theory through arguing and demonstrating how it can benefit from social constructivist perspectives and a focus on dialogue. Similarly, I argue that we need to ask whether networked social media is, essentially, a new landscape for dialogue and therefore should be conceived and investigated based on this premise, through considering dialogue as the primary means to develop and exploit connections for learning. A key lever in this argument is the increasingly important requirement for greater criticality on the Internet in relation to our assessment and development of connections with people and resources. The open, participative, and social web actually requires a greater emphasis on higher order cognitive and social competencies that are realised predominantly through dialogue and discourse. Or, as Siemens (2004) implies, in his call to rethink the fundamental precepts of learning, we need to shift our focus to promoting core evaluative skills for flexible learning that will, for example, allow us to actuate the knowledge we need at the point that we need it. A corollary of this is the need to reorient educational experiences to ensure that we develop in our learners the ability “to think, reason, and analyse.” In considering how we can achieve these aims this article will review the principles of connectivism from a dialogue perspective; propose some social constructivist approaches, based on dialectic and dialogic dimensions of dialogue, which can act as levers in realising connectivist learning dialogue; demonstrate how dialogue games can link the discussed theories to the design and performance of networked dialogue processes; and consider the broader implications of this work for designing and delivering sociotechnical learning.
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 | 0.019 | 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 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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