Pedagogical Application of Corpus on EFL of Children with Autism Spectrum Disorders (ASD): The Function of Visualization on Attention Deficit Problem
Bibliographic record
Abstract
Statistics reveals that Autism Spectrum Disorders (ASD) becomes prevalent in recent years. Among 68 children, 1 is reported as being on the spectrum. Children with ASD often encounter a variety of challenges in their academic life, most of which are supposed to be attributed to the core symptoms of ASD. This study attempts to explore the effects of the pedagogical application of corpus on children with ASD by analyzing the visualization function of corpus tools on children with ASD. This research involves 30 children (aged 8–10) who have been diagnosed as being with ASD on the mild side. They have spontaneous utterances in their L1 and most of which are of pragmatic functions. Compared with the normally developed peers, these 30 children have shown difficulties in learning a foreign language. This article assesses the visualizing function of the pedagogical application of corpus on helping them overcome the difficulties: they can be seated longer during the class; they pay more attention to the instructor and peers; and they respond more frequently to the instructor and peers. Hopefully, this article can provide some constructive suggestions for foreign language teaching and learning for children with ASD.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".