Do Our Hands See What Our Eyes See: Investigating the Relationships Between Spatial and Haptic Abilities
Bibliographic record
Abstract
Introduction Spatial abilities (SA) are the cognitive ability to manipulate mental images of objects to problem solve and are linked to comprehension of three‐dimensional (3D) spatial knowledge in gross anatomy and in learning clinical procedures. Similarly, haptic abilities (HA) refer to translating tactile information from the immediate environment into mental images and are involved in handling anatomical specimens and technical skill acquisition common to clinicians. Both abilities independently play an important role in learning anatomy, yet the relationships between SA and HA are unknown. The objective of this study is to explore SA‐HA interactions. Methods The Mental Rotations Test (MRT) and the newly developed haptic abilities test (HAT) respectively quantified SA and HA in undergraduate students. The HAT, modelled after the MRT, consisted of untimed, matching questions utilizing MRT‐styled 3D handheld wooden objects (~10cm3) under three sensory conditions using sight (S), haptics (H) and the combination of both sight and haptics (SH). While HAT condition scores and response times determined accuracy, video recorded subject gaze and haptic behaviours on a question‐by‐question basis. Scores for MRT are presented as mean ± SD and HAT scores as median (Q1‐Q3). Results Subjects (n=16, 10F, 20‐28yrs) completed the MRT and HAT and were categorized into high (n=9, 4F, MRT: 14.8±3) and low (n=7, 6F, MRT: 6.3±3) (H/LSA) groups ( p<0.0001 ). Scores obtained in the H condition [14 (13‐15) vs 14 (14‐14), p=0.0031 ] were significantly lower than in the S [15 (15‐15) vs 14 (14‐15)] and SH conditions [15 (15‐15) vs 14 (14‐15)] in H/LSA groups respectively. Spearman’s correlation coefficient illustrated MRT scores were moderately related in the S condition (r=0.506, p=0.038 ), but unrelated in the SH and H conditions (SH: r=0.325, p=0.203 ; H: r=0.162, p=0.534 ). The number of pupillary fixations per question was similar (S:6.0±3.0 vs 5.9±1.4, p=0.910 ; SH: 4.5±2.0 vs 6.7±2.0, p=0.099 ) for H/LSA groups respectively. Initial descriptive analyses of hand behaviours (n=4) suggest H/LSA objects differently. Discussion Despite significant difference in SA, when individuals are presented identical environmental 3D objects to view, view and touch, or touch alone, it is difficult to differentiate SA. These data suggest that the addition of haptic sensory information may aid LSA individuals completing spatial tasks. Although visual attention and timing of haptic behaviours may be similar between H/LSA subjects, further kinematic analysis of haptic strategies may be more meaningful to isolate how somatosensory inputs aid problem solving behaviours in LSA persons. This is some of the first data to simultaneously measure hand and gaze behaviour during spatially challenging tasks in individuals with divergent SA. Given recent migrations to online anatomy teaching and learning environments due to COVID‐19, understanding learner behaviour when sensory inputs, like haptics, are removed is valuable evidence that can inform future anatomy curriculum and resource development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".