Speed of Processing: Tests and Factor Structure
Bibliographic record
Abstract
In the present study we examined Speed of Processing derived from a number of cognitive tests; the response speeds were nearly automatic for tests with minimal cognitive load. The tests were given to students across ages from 8 to 20 in schools and colleges located in various parts of India. The structure of the constellation of the test responses was determined by factor analyses. We report one stable factor of speed for ages 8-10 that splits into two separate but correlated factors for ages 11-14,15-17, and 18-20 representing speed of response to tests that contain letters and numbers versus colour stimuli. Developmental changes in response speed across the four adjacent age groups were examined; the trajectory was not consistently incremental, especially for naming colours that did not increase beyond age 11-14.In conclusion, a fairly reasonable deconstruction of the concepts of RAN has been presented in this report. The major components are encoding and articulation, and the necessity of distinguishing alpha-numeric naming time and colour naming. The later requires the additional time for semantic access. At the end, we suggest that in a follow-up research RAN(alpha-numeric&colour) should be viewed as a part of a broader cognitive speed of processing.Our objective is to determine the association between tests of basic executive processes such as cognitive flexibility,attention &inhibition and working memory on the one hand and speed on the other.Consequently not to search for the tests that would not involve speed, but be aware of the value of the correlation of an executive test with sp eed.This will be useful information or example in investigations into the effect of ageing on executive functions. A worthy agenda for future research. Keywords: Rapid Automatic Naming(RAN),Developmental Changes, Executive Functions DOI: 10.7176/JEP/13-30-11 Publication date: October 31 st 2022
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".