A PILOT STUDY OF THE SITUATED GAME FOR AUTISTIC CHILDREN LEARNING ACTIVITIES OF DAILY LIVING
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
Daily living skills are difficult for autistic children to learn because they have low motivation in learning new things. Some research had developed virtual environments to assist parents and teachers in teaching autistic children daily living skills. Educators still need to spend a lot of time in preparing personalized and more realistic tasks for children to practice in the virtual environments. The research team developed a situated game which is capable of generating personalized and non- repeated daily living activities for individual children. A small pilot had designed and conducted for verifying the effectiveness of the game and gathering the users’ (including parents and the autistic children) perceptions toward the game and the game-play. Questionnaire and interviews were used to collect user perceptions. While quantitative analysis method (with SPSS) was used to give readers an overview idea of what users felt, thematic analysis (with NVivo) was taken for analyzing interview transcripts and results could be the basis of our game’s future improvements. The results show that both of autistic children and their parents all gave positive feedback to the game. Suggestions for the game development for autistic children are also given based on the analysis results of questionnaire and parents’ interview.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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