Eye Gaze Based Model for Anxiety Detection of Engineering Students

• Published in: Emerging Technology Trends in Internet of Things and Computing Vol. 1548; pp. 195 - 205
• Main Authors: Agustianto, Khafidurrohman, Riskiawan, Hendra Yufit, Setyohadi, Dwi Putro Sarwo, Wiryawan, I. Gede, Mansur, Andi Besse Firdausiah, Basori, Ahmad Hoirul
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2022; Springer International Publishing
• Series: Communications in Computer and Information Science
• Subjects: Anxiety detection system; Engineering students; Eye gaze; Student modeling
• ISBN: 3030972542; 9783030972547
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-030-97255-4_14

Education is a vital component for country development, particularly in the engineering or technology field. The engineering students must maintain their focus and attention due to the complexity of their study. The objective of this research is to observe student anxiety who is taking a course in engineering fields. Students with anxiety disorders show moderate interest in learning, have a weak performance on exams and assignments. Stress detected from the eye gaze. It has a pattern that represents the anxiety condition of engineering students. The main contribution of our paper is providing an observation result on how to deal with the anxiety experienced by engineering students using eye gaze by identifying eye movement patterns from students. The eye gaze pattern divided into 16 areas (A1, A2, A3, A4, B1, B2, B3, B4, C1, C2, C3, C4, D1, D2, D3, and D4). The research results show 85.5% accuracy. These results provide a guideline for how teachers can rapidly comprehend students’ anxiety condition and perform a particular action to help students gain their optimum learning result.