AI-Supported Therapy Shows Remarkable Improvements in Handwriting Skills for Children at Risk for DCD (Dyspraxia)

A boy writing

Groundbreaking New Research Demonstrates Extraordinary Effect Sizes in Randomised Controlled Trial

Fresh research just published in Research in Developmental Disabilities presents compelling evidence for the effectiveness of AI-supported occupational therapy in improving handwriting skills amongst children at risk for Developmental Coordination Disorder (DCD)/Dyspraxia.

Understanding Developmental Coordination Disorder

Developmental Coordination Disorder affects approximately 5-6% of school-aged children, presenting as significant difficulties with motor coordination that impact daily activities. For many children with DCD, handwriting represents a particular challenge, as it requires precise fine motor control, spatial awareness and sustained attention.

Handwriting difficulties in children with DCD typically manifest as:

• Poor letter formation and inconsistent sizing

• Irregular spacing between letters and words

• Reduced writing speed compared to peers

• Fatigue during writing tasks

These challenges can significantly impact academic performance and educational outcomes, making effective interventions crucial for supporting these children's development.

The AI-Supported Intervention

Researchers developed an occupational therapy programme incorporating artificial intelligence technology to address handwriting challenges in children at risk for DCD. The intervention was implemented over an 8-week period with twice-weekly sessions.

Study Design and Findings

This randomised controlled trial included 42 children aged 8-12 years who were identified as being at risk for DCD. Participants were randomly assigned to either an intervention group (n=21) receiving the AI-supported therapy or a control group (n=21) continuing with regular activities.

Measuring handwriting improvements with the Minnesota Handwriting Assessment

To objectively measure handwriting changes, researchers used the Minnesota Handwriting Assessment (MHA) - a standardised, norm-referenced instrument specifically designed to evaluate manuscript handwriting in young children.

The assessment evaluates six key areas of handwriting performance:

• Rate - writing speed

• Legibility - overall readability

• Form - letter shape quality

• Alignment - how well letters sit on lines

• Size - consistency of letter height

• Spacing - gaps between letters and words

Results showed substantial improvements in the intervention group:

Intervention Group (AI Therapy):

• Shape formation: Improved by an effect size of d = 2.279 (extraordinary)

• Letter alignment: Improved by d = 1.893 (extraordinary)

• Overall handwriting score: Improved by d = 2.291 (extraordinary)

Control Group:

• Only minimal improvements, with just alignment showing modest gains (d = 0.311)

Understanding the Effect Sizes

The effect sizes observed in this study are notably large when compared to typical educational and therapeutic interventions. In educational research, effect sizes are commonly interpreted using Cohen's benchmarks, where:

• Small effect: d = 0.2

• Medium effect: d = 0.5

• Large effect: d = 0.8

Contextualising these findings:

• Most educational interventions achieve effect sizes between 0.1-0.4

• Reading interventions typically show effects of 0.2-0.4

• Math tutoring programmes generally produce effects of 0.3-0.6

• Technology-based educational interventions often yield effects of 0.1-0.3

This study's effect sizes of 2.279 (shape) and 1.893 (alignment) are exceptionally large, representing improvements that place the average treated child well above 95% of untreated children. Such large effect sizes suggest the intervention produced clinically meaningful changes in handwriting performance.

Clinical and Educational Implications

The findings suggest several important considerations for practice and future research:

For Occupational Therapists:

• AI-supported interventions may enhance traditional therapy approaches

• Technology can provide consistent, objective feedback during practice sessions

• Data collection through AI systems may improve treatment planning and progress monitoring

For Educators:

• Early identification and intervention for handwriting difficulties may prevent cascading academic challenges

• Technology-enhanced interventions could be integrated into school-based support services

• Improved handwriting skills may facilitate better demonstration of academic knowledge

For Researchers:

• The large effect sizes warrant replication studies across different populations and settings

• Investigation of the specific AI components contributing to effectiveness is needed

• Long-term follow-up studies would help establish durability of treatment gains

Conclusion

This randomised controlled trial provides evidence for the effectiveness of AI-supported occupational therapy in improving handwriting skills amongst children at risk for DCD. The large effect sizes observed across multiple handwriting domains suggest this approach may offer significant advantages over traditional interventions.

However, these preliminary findings require replication and extension through larger, longer-term studies. The integration of artificial intelligence into therapeutic practice represents a promising development that warrants continued investigation and careful implementation.

For clinicians and educators working with children experiencing handwriting difficulties, these results suggest that technology-enhanced interventions may offer valuable tools for improving outcomes. As this field develops, attention to implementation science, cost-effectiveness and equitable access will be crucial for translating research findings into widespread clinical practice.

References: Demirci, O., Guney Yilmaz, G. & Köse, B. (2025). Artificial intelligence-supported occupational therapy programme on handwriting skills in children at risk for developmental coordination disorder: Randomised controlled trial. Research in Developmental Disabilities, 156, 105009.

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