Designing Online Conversations to Engage Local Practice
Bibliographic record
Abstract
In this chapter we present a model for the design of a conversation space to support knowledge-building. While we focus on online environments, the model has much greater generality. The model, an expansion and adaptation of Nonaka’s work, considers knowledge as consisting of complementary explicit and tacit dimensions. It argues that these two dimensions of knowledge are mutually reinforcing, inseparable and irreducible and thus in order to build robust knowledge we must attend to both dimensions and, most critically, the relationship between them. Our model conceptualizes the development of knowledge as a spiral between the complementary processes of Externalization (through collective online reflection) and Internalization (through conscientious local practice) and discusses eight principles for designing online conversations to foster effective Externalization, thus promoting the knowledge-building spiral. The broader message of this chapter is that designers need to expand their frame for thinking about “online” learning to include not only the virtual space but also the local spaces which learners inhabit in order to create useful and engaging learning experiences. All of the eight design principles presented here support this consideration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".