Predicting Behaviour Patterns in Online and PDF Magazines with AI Eye-Tracking.

This study aims to improve college magazines, making them more engaging and user-friendly. We combined eye-tracking technology with artificial intelligence to accurately predict consumer behaviours and preferences. Our analysis included three college magazines, both online and in PDF format.

Exploring the Untapped Potential of Neuromarketing in Online Learning: Implications and Challenges for the Higher Education Sector in Europe.

This research investigates the impact of applying neuromarketing techniques to three practical examples of higher education (HE) branding: an official college website page, an official college Facebook page, and recorded online video lectures used for teaching at HE institutions. The study was conducted in three different HE institutions with a representative sample of 720 participants, with = 529 used for testing the CARE college website, = 59 for testing the HAZEF Facebook page, and = 132 for testing the emotional response of students studying online. To assess the participants' emotional responses, this study utilized automated facial coding through a webcam (15 Hz) and considered mood intensities.