Optimizing cognitive load in nursing digital education requires an evidence-based understanding of cognitive engagement patterns across various learning material modalities. However, the current literature lacks psychophysiological evidence regarding aptitude-by-modality interactions within nursing learning contexts. A 2 × 3 factorial psychobehavioural experiment was conducted with 58 undergraduate nursing students, stratified by pre-academic performance (high and low) and exposed to three digital material modalities (text, text-graphic composite and video-based). Cognitive load was assessed using subjective measures (National Aeronautics and Space Administration Task Load Index, NASA-TLX) and oculometric indices of visual attention. Learning performance were measured through achievement scores and knowledge acquisition efficiency metrics. Data were analysed using two-way analysis of covariance within the general linear model, with Bonferroni corrections applied to adjust for multiple comparisons. Pearson correlation analyses were performed to examine associations between cognitive load and learning performance. The analysis included 55 valid cases. Key findings showed that learners with high pre-academic performance exhibited significantly lower subjective cognitive load (P < 0.001 in two of the three knowledge modules) and superior learning performance (P < 0.05 in all three knowledge modules) compared to their low-performance counterparts. Learners with low pre-academic performance experienced cognitive overload, particularly in text-based conditions (P < 0.05 in all three knowledge modules). While video-based materials induced the lowest cognitive load (P < 0.05 in all three knowledge modules), and text-graphic composites achieved optimal learning efficiency despite moderate cognitive load (P < 0.05 in two of the three knowledge modules). No significant interaction effects between pre-academic performance and material modality were observed. These findings highlight that lower perceived load does not necessarily translate into more effective learning and underscore the importance of aligning instructional modality with learners’ cognitive characteristics. A cognitive-material alignment framework integrating knowledge typology, multimedia design principles, individual learning analytics, and dynamic material adaptation mechanisms should be implemented to prevent cognitive overload in at-risk learners.
Li et al. (Sat,) studied this question.