The Role of Languaging in Creating Zones of Proximal Development (ZPDs): A Long-Term Care Resident Interacts with a Researcher
Bibliographic record
Abstract
This article addresses the question: What is the role of languaging--the shaping and organizing of higher mental processes through language--in emerging zones of proximal development (ZPDs) co-created by two adults? The two adults are a resident in a long-term care facility (Mike) and a researcher. A ZPD is an ongoing cognitive/affective activity in which learning and development occur as participants interact. This process is mediated by languaging. Through a microgenetic analysis of selected representative excerpts from 11 one-on-one sessions, we illustrate how the interactions between Mike and the researcher create a positive affective context which affords multiple opportunities for ZPDs to emerge. During the emergent ZPDs, we observe how languaging brings together the cognitive and affective components essential for the participant's continued development. Over time, Mike reclaims lost expertise and takes on new complex cognitive challenges. Outcomes for Mike include both cognitive development and enhanced self-esteem.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".