Boundary Crossing between Formal and Informal Learning Opportunities: A Pathway for Advancing e-Learning Sustainability
Bibliographic record
Abstract
In this article, third generation cultural historical activity theory (CHAT) (Engeström, 2011) will be the means for analyzing tensions and contradictions between formal and informal learning within a MOOC design. This article builds on previous work (Bradshaw, Parchoma & Lock, 2017) wherein cultural historical activity theory (CHAT) was used to establish formal and informal learning as activity systems. Formal and informal learning are considered in relation to designing learning for a MOOC environment. Findings from an in situ study specifically examining CHAT elements in the process of design are considered in a movement towards making visible what those tasked with designing courses normally do not see in relation to informal learning. Implications for practice are presented in a CHAT-Informed MOOC design model intended to augment typical approaches to instructional design. The outcome is an argument for CHAT-Informed MOOC design model can intentionally address both formal and informal opportunities for learning.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.016 | 0.024 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".