ArticleFrontiers in psychology2026
Can explainable AI scaffolding reduce cognitive load and enhance embodied expression? A quasi-experimental study of multilingual vocal learning in Bel Canto education.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Exploring how artificial intelligence technology can effectively support music education has become a critical issue in the digital era. This study addresses the high cognitive load and embodied expression difficulties faced by bel canto students when learning multilingual vocal works, designing and validating the educational effectiveness of an explainable AI scaffolding learning system. The study employed a 2 × 3 mixed-factor quasi-experimental design, with 64 college students from the Conservatory of Music allocated to the XAI scaffolding group and the traditional AI-assisted group through stratified assignment for a 16-week intervention on the learning of vocal music works in Italian, German, and French. Data collection integrated multimodal measurements including cognitive load scales, expert ratings, motion capture, and eye-tracking, with analysis using repeated-measures mixed-factor ANOVA, Bootstrap-based mediation analysis, and thematic analysis. The study found that the XAI scaffolding group's cognitive load reduction reached 38.9%, significantly higher than the control group's 17.0% (
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