Development of a novel, theoretically motivated scale to assess cognitive learning styles related to the autism spectrum
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
BACKGROUND: Although theoretical efforts have been made to address the cognitive learning styles of individuals on the autism spectrum, no instrument to measure such learning styles is currently available. The current study aimed to develop such a scale based on the learning style theory of Qian and Lipkin (Front Hum Neurosci 5:77, 2011). METHODS: Response data from total of 768 undergraduate students was used for this study. This sample was split into two subsamples of N = 460 and N = 308 for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. The correlations between the resulting new subscales and some other potentially related measures were examined. RESULTS: A three-factor structure with 19 items was obtained measuring need for task clarity/familiarity, susceptibility to cognitive load, and the grasping of conceptual relations. CONCLUSIONS: This newly developed measure can be used to help understand the nature of the individual differences in cognitive processing that are evident across both the autism spectrum as well as the overall population more generally.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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