Bibliographic record
Abstract
On the tenth anniversary of the networked learning conference I am looking back at developments in identifying the sites of learning in networked learning design and praxis. Beginning with McConnell’s (1998) premise that collaboration is central to the development of democratic ‘learning communities’ and Jones’ (2000) relational perspective on the role of technologies in connecting learners, tutors, and learning resources, I examine early critiques of community and the implications of those critiques for design, tutoring, and assessment practices. I then turn to a discussion of interrelated human and technological agencies and a historical trajectory of design foci at the resource, task, and activity levels. Tensions between research orientations that focus on individual learning and those that focus on collective learning are traced to associated theoretical perspectives and methodological choices. The construct of the individual mind and the notion of connectivism are critiqued. The agencies of socially constructed technologies to distribute learning capacities across networks are examined for insights into and implications of differing approaches to collective coordination of social-material practices. In concluding this retrospective, I return to the critical and humanistic roots of networked learning and introduce Hodgson, de Laat, McConnell, and Ryberg’s (2014) call to “transcend the dualism between abstract mind and concrete material social practice” (p. 3). I use discourse analysis to critique contemporary cognitivist, computational conceptualizations of the individual mind and the resultant focus on instructionalist underpinnings in broader educational technology approaches to design. I argue that this perspective on cognition is reductive: focused on teacher-designer-researcher control, hierarchical perceptions of learning contexts, and suggest the quest for designed orchestrations of learning processes has led to an assumption that the efficaciousness of learning can simply reside in resources. The computational, cognitivist perspective on design is contrasted with Conole’s (2006) rejection of resource-level foci on design and with Goodyear, Carvalo, and Dohn’s (2014) distinctions among designable tasks and emergent activities; situated conceptualizations of affordances and mutually constitutive perspectives on the relationships among material social practices and learning. The “reclaiming” section of the paper examines three pre-computational conceptualizations of distributed cognition as embodied, integrated with socio-material artifacts, and enacted through practices. I conclude with looking forward to a time where pre-computational conceptualizations of distributed cognition provide links to networked learning theory, a route to transcending dualisms, and opens new examinations and problematizations.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.050 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".