Creating Personae for Personalising a Visual Programming Tool for Children with Autism Spectrum Condition: A Proposed Methodology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Designing and developing accessible educative and entertaining technologies for children with Autism Spectrum Condition is no easy task due to their diverse needs and capabilities. In theory, accessibility can be achieved by personalising technologies based on the unique capabilities and needs of each individual. However, that requires knowledge of the capabilities and needs of each individual. A potential solution to this challenge is to use Personae; a persona provides a detailed description of a user in addition to the user’s capabilities, needs, challenges and goals. In this paper, we propose a method of creating personae for children with Autism Spectrum Condition to be used for personalising a visual programming tool. This method will take advantage of existing personae by extending them to fit the needs of our current context
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it