The UTC Graduate School is pleased to announce that Menekse Adar will present Master’s research titled, Unsupervised Discovery and Validation of Affective Engagement States Using Synchronized EEG and Eye-Tracking During Digital Learning on 03\/06\/2026 at 10:00 AM in ESC 347B. Everyone is invited to attend.
Engineering Management
Chair: Serkan-Varol
Co-Chair:
Abstract:
This study explores affective engagement states in digital learning environments using synchronized EEG and eye-tracking data. EEG signals were collected from frontal channels and processed using sliding windows to extract band power features. Frontal Alpha Asymmetry (FAA, log alpha power difference F4\u2013F3) and a Beta\u2013Alpha ratio (BA, log beta\/alpha power ratio) were used as affective proxies. Instead of predefined emotion labels, unsupervised clustering methods were applied to discover latent engagement patterns directly from EEG features. To ensure robustness, non-overlapping parity analysis and hold-out validation were performed. Statistical tests were used to compare FAA and BA values across identified clusters. Results show consistent differences in arousal-related features across clusters, supporting the reliability of the discovered states. Eye-tracking data were synchronized with EEG windows to provide additional behavioral context. The findings demonstrate a robust multimodal framework for discovering and validating affective states during real classroom interactions.
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The UTC Graduate School is pleased to announce that Menekse Adar will present Master’s research titled, Unsupervised Discovery and Validation of Affective Engagement States Using Synchronized EEG and Eye-Tracking During Digital Learning on 03\/06\/2026 at 10:00 AM in ESC 347B. Everyone is invited to attend. Engineering Management Chair: Serkan-Varol Co-Chair: Abstract: This study explores affective engagement states in digital learning environments… <\/p>\n