Eye Gaze Based Model for Anxiety Detection of Engineering Students

Agustianto, Khafidurrohman and Riskiawan, Hendra Yufit and Setyohadi, Dwi Putro Sarwo and Wiryawan, I. Gede and Mansur, Andi Besse Firdausiah and Basori, Ahmad Hoirul (2022) Eye Gaze Based Model for Anxiety Detection of Engineering Students. In: Emerging Technology Trends in Internet of Things and Computing. Springer Nature Switzerland AG, pp. 195-205.

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Abstract

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. In this research, we took student anxiety as our research concentration. Students with anxiety disorders show moderate interest in learning, have a weak performance on exams and assignments. Stress can be detected from the eye gaze. It has a pattern that represents the anxiety condition of engineering students. This study aims to deal with the anxiety experienced by engineering students using eye gaze by identifying eye movement patterns from students. The eye gaze pattern is 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 novel, how teachers can comprehend the anxiety condition of students rapidly and perform a particular action to help student gain their optimum learning result.

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