Children and embodied interaction: Seeking common ground
Bibliographic record
Abstract
As computation plays an ever larger role as an embedded part of the environment, research that seeks to understand the embodied nature of children's interactions with computation becomes increasingly important. Embodied interaction is an approach to understanding human-computer interaction that seeks to investigate and support the complex interplay of mind, body and environment in interaction. Recently, such a perspective has been used to discuss human actions and interactions with a range of computational applications including tangibles, mobiles, robotics and gesture-based interfaces. Physically-based forms of child computer interaction including body movements, the ability to touch, feel, manipulate and build sensory awareness of the relationships in the world are crucial to children's cognitive and social development. This workshop aims to critically explore the different approaches to incorporating an embodied perspective in children's interaction design and HCI research, and to develop a shared set of understandings and identification of differences, similarities and synergies between our research approaches. Copyright 2009 ACM.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".