Load-Rhythm Misalignment and the Ethics of Capacity in Artificial Intelligence-Driven Educational Technology

Abstract

Against the backdrop of continuous iteration in artificial intelligence and the accelerating expansion of computational power, education has gradually developed a technology-centered narrative of “empowerment”, in which enhanced technical capacity is often implicitly equated with improved educational quality. From a structural perspective, this paper argues that algorithmic systems are inherently oriented toward continual acceleration and optimization, whereas individual development depends on limited cognitive bandwidth, affective thresholds, and multi-temporal integrative rhythms. To systematically account for the internal tension between the two, the paper proposes the Load-Rhythm Misalignment Model and constructs a four-dimensional analytical framework consisting of capacity, rhythm, field, and sedimentation. In response to the broader trend of structural contraction and the concentration of evaluation, the paper further advances a capacity-first ethical framework of load and introduces the concept of Computational Constructivism. Through design principles such as cognitive topological visualization, rhythm-protection mechanisms, and cross-domain transfer mapping, it seeks to reconstruct the generative conditions of education. At the macro level, the study delineates the structural characteristics of the era of contraction and the existential risks it may generate. At the micro level, it proposes the dynamic constructs of the Developmental Capacity Band and the Compression Threshold, arguing that the formation of self-structure depends on an integrable zone of tension and the maintenance of a Delayed Closure Loop mechanism.