An Adaptive Scoring Framework for Attention Assessment in NDD Children via Serious Games

This paper introduces an innovative adaptive scoring framework for children with Neurodevelopmental Disorders (NDD) that integrates multiple metrics, such as spatial attention patterns, temporal engagement, and game performance data, to provide a comprehensive assessment of learning that extends beyond traditional game scoring. The framework employs a progressive difficulty adaptation method that focuses on specific stimuli at each level and dynamically adjusts weights to accommodate increasing cognitive load and learning complexity. Additionally, it includes capabilities for temporal analysis, such as detecting engagement periods, rewarding sustained attention, and implementing an adaptive multiplier framework based on performance levels. To avoid over-rewarding high performers while maximizing improvement potential for struggling students, the designed framework features an adaptive temporal impact framework that adjusts performance scales accordingly. We also established a multi-metric validation framework using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Pearson correlation, and Spearman correlation, along with defined quality thresholds, to assess deployment readiness in educational settings. This research bridges the gap between technical eye-tracking metrics and educational insights by explicitly mapping attention patterns to learning behaviors, enabling actionable pedagogical interventions.