COGNITIVE LOAD OPTIMIZATION IN AUGMENTED REALITY ASSISTED VOCABULARY ACQUISITION FOR NEURODIVERGENT LANGUAGE LEARNERS

Neurodivergent language learners, including those with differences in attention regulation, sensory processing, and other measures, typically experience higher levels of intrinsic and extraneous cognitive load during vocabulary acquisition, leading to poorer vocabulary retention and slower semantic integration. The proposed study applies the Cognitive Load Optimization (CLO) framework, leveraging Augmented Reality (AR), to improve vocabulary learning efficiency and reduce cognitive overload. The results are a combination of adaptive multimedia presentation, dual-channel input balancing, and real-time monitoring of cognitive load that uses performance-based proxies, as well as a subjective rating scale. A controlled experimental study was conducted involving 120 neurodivergent learners, who were divided into a traditional digital learning group and an AR-assisted CLO group for 6 weeks. A modified NASA-TLX scale was used to measure cognitive load, and immediate and delayed post-tests were used to assess vocabulary retention. The findings show that the AR-CLO group showed 27.8% improvement in immediate recall and 34.5% improvement in delayed retention compared with the control group (p < 0.01). Extraneous cognitive load was reported to have decreased by 22.3%, with a corresponding increase in germane load of 18.7%, suggesting that schema-building efficiency may be enhanced. Processing fluency was also indicated by a 16.4% reduction in learning time per vocabulary set. Regression analysis revealed that the decrease in cognitive load explained 41% of the variance in retention performance (R2 = 0.41). The findings are consistent with the hypothesis that adaptive AR environments can systematically configure cognitive load distribution, thereby improving vocabulary acquisition among neurodivergent learners. The proposed design offers a scalable framework for inclusive language teaching focused on cognitive personalization and interface design with sensory consideration.

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