Relationships between Kinarm Standard Tests and School Success in Secondary Students
Bibliographic record
Abstract
The complex nature of neurodiverse high school students requires access to information on many fronts. One area for assessment which has been largely ignored in the Ontario public school system is assessment of co-ordination and movement tasks. A diagnosis of developmental coordination disorder has been shown, in research, to consistently share a comorbidity of 50% with many common learning differences (Zwicker et al., 2012), despite this very few students will receive this diagnosis (Blank et al., 2019). This is partly due to the lack of standard assessment tools and criteria (Ricci et al., 2019). The Kinarm, a robotic assessment tool of upper body coordination, is a quick and objective measure of sensory, motor and cognitive functions (Dukelow et al., 2010). This research explores the use of the Kinarm as an assessment tool for high school students by examining: 1) how do Kinarm task parameters correlate to each other, 2) if there is a relationship between Kinarm task parameters and school success measures, and 3) if there is a relationship between Kinarm task parameters and a previously diagnosed learning disability or neurological disorder. Thirty-eight high school students completed the Kinarm assessment between April and December 2019. Data were also collected through a series of cognitive tasks as well as academic and testing scores from the participants’ Ontario Student Record. Visual exploratory analysis was conducted along with Pearson correlations (1-tailed). Despite a small sample size and limited number of neurodiverse participants this research showed moderate correlation between a variety of co-ordination tasks and cognitive/school scores. Kinarm tasks which showed the highest correlations were Ball on Bar, Object Hit, Object Hit and Avoid, and Trail Making. The two school measures with highest correlations were Rapid Digit Naming and TOWRE Word Reading. The correlations remained moderate after controlling for speed and continued to be evident after an adjustment for false discovery rate. Overall, this research confirms a relationship between co-ordination and measures of school success. It confirms the feasibility of using a robotic assessment with high school students. Future studies can explore the use of Kinarm with a larger sample size and larger number of exceptional learners. More detailed physical profiles of coordination for exceptional learners could focus movement interventions on specific areas of need, in order to increase their effectiveness.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".