Assessing the environmental quality of an adapted, play-based LEGO <sup>®</sup> robotics program to achieve optimal outcomes for children with disabilities
Bibliographic record
Abstract
Purpose This study assessed the environmental quality of an adapted, play-based LEGO® robotics program for children and youth with disabilities to determine the degree to which the activity setting supports the therapeutic goals of the program.Materials and methods We measured the environmental qualities of a robotics program held at a paediatric rehabilitation hospital. We observed and coded video-recordings of the robotics program, specifically one session from each of five different rooms where the program took place. Using the 32-item Measure of Environmental Qualities of Activity Settings (MEQAS), we described the place- and opportunity-related qualities of these settings.Results Our observations revealed that, across all five settings, the environments support the therapeutic goals of the program, including providing opportunities for social interaction with peers and adults to a great extent. We also identified several environmental features of the robotics program that support optimal outcomes for children and youth with disabilities.Conclusions Our findings lend support for the value of examining environmental opportunities and affordances of play-based therapy within rehabilitation.IMPLICATIONS FOR REHABILITATIONAssessing the environmental opportunities and affordances of play-based activities using the Measure of Environmental Qualities of Activity Settings (MEQAS) is valuable for supporting positive outcomes in rehabilitation.The settings of an adapted LEGO® robotics program offer children with disabilities opportunities to engage in social interactions with peers and adults, to learn a new skill, and to develop a sense of self-identity.Optimal therapeutic outcomes of an adapted LEGO® robotics program can be supported by environmental features, including: large tables with sufficient space for two youth and one or two adult volunteers to interact at eye-level, arranged separately with enough space to invite movement between tables, in such a way that children may also interact across tables.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".