Optimizing Cognitive Load in Digital Mathematics Textbooks: A Mixed-Methods Study on Content Organization and Application Models

This paper examines the grain of content in junior high mathematics digital textbooks from People’s Education Press (PEP) using Cognitive Load Theory (CLT) in a sequential explanatory mixed-methods design: (1) bibliometric analysis of 2008-2023 142 publications found substantial gaps in cognitive-aligned pedagogical design; then, (2) large-scale surveys of 231 teachers and 102 students found critical gaps in navigation intuitiveness (71.3%), interactive affordance deficiency (68.9%), and personal pathway rigidity (76.5%). (3) Interviews with 6 teachers and 3 developers further revealed these deficiencies lay in: (1) content fragmentation serving procedural skills at the expense of conceptual integration; (2) sequence disruption violating CLT’s intrinsic load tenets; and (3) passive multimodal serving static text/images (82% of resources) limiting germane processing. We thus innovated a CLT-driven framework to reduce intrinsic load by animating schema builders chunking complex concepts, minimize extraneous load by Gestalt-principled UI redesign serving spatial consistency, and enhance germane load by adaptive analytics serving personal pathways. Empirical results showed 34% more knowledge retention (p<0.01, d=1.87) and 28% less perceived cognitive load (NASA-TLX) relative to conventional textbooks. Our work contributed both a theoretically grounded resource optimization model and an advancement of CLT in technology-enhanced mathematics instruction.