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. 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.
Keywords
- Student modeling
- Engineering students
- Eye gaze
- Anxiety detection system
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Acknowledgements
This work was supported by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah Saudi Arabia and Information Technology Department, Politeknik Negeri Jember. The authors, therefore, gratefully acknowledge the DSR technical and financial support.
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Agustianto, K., Riskiawan, H.Y., Setyohadi, D.P.S., Wiryawan, I.G., Mansur, A.B.F., Basori, A.H. (2022). Eye Gaze Based Model for Anxiety Detection of Engineering Students. In: Liatsis, P., Hussain, A., Mostafa, S.A., Al-Jumeily, D. (eds) Emerging Technology Trends in Internet of Things and Computing. TIOTC 2021. Communications in Computer and Information Science, vol 1548. Springer, Cham. https://doi.org/10.1007/978-3-030-97255-4_14
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