Yogyakarta, January 26, 2026 – Online shopping is not only an economic activity but also involves complex cognitive processes. However, identifying cognitive load during online shopping activities is often inconsistent. To address this, a research team from Universitas Gadjah Mada (UGM) has developed an Artificial Intelligence (AI)-based technology to classify users’ cognitive load levels while shopping online.
The findings of this study were published in the journal Array, Vol. 29, 100669, in an article titled “Cognitive load classification during online shopping using deep learning on time series eye movement indices.” The article was authored by Sunu Wibiarna, Muhammad Ainul Fikri, Iman Kahfi Aliza, Kristian Adi Nugraha, Syukron Abu Ishaq Alfarizi, Noor Akhmad Setiawan, Ahmad Riznandi Suhari, and Sri Kusrohmaniah.
This research focuses on user experience (UX) in e-commerce by analyzing consumers’ eye movements during online shopping activities. The eye movement data are processed as time series to distinguish between low and high cognitive load conditions.
The novelty of this study lies in the application of a deep learning model using an Attention-based Long Short-Term Memory–Fully Convolutional Network (ALSTM-FCN). This approach enables accurate classification of cognitive load without requiring exclusive software or intrusive physiological measurements that may disrupt user comfort. The ALSTM-FCN model outperformed other machine and deep learning models, achieving an average accuracy of 97.70%. It also demonstrated strong alignment with subjective cognitive load measurements obtained using the NASA-TLX instrument. This alignment highlights the importance of integrating both objective and subjective measures in understanding cognitive load during online shopping.
These findings have the potential to be applied in designing more adaptive, efficient, and user-friendly online shopping platforms, while also helping industry practitioners better understand consumers’ cognitive load in decision-making processes. This publication underscores UGM’s contribution to interdisciplinary research that bridges psychology, AI technology, and consumer behavior at the international level.
Article link: https://doi.org/10.1016/j.array.2025.100669
Congratulations to Sri Kusrohmaniah and colleagues.
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