Publication Type : Book Chapter
Publisher : Lecture Notes in Networks and Systems, Springer Singapore
Source : Lecture Notes in Networks and Systems, Springer Singapore, Volume 120, Singapore, p.391-405 (2020)
ISBN : 9789811533259
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2020
Abstract : Identifying and classifying based on expertise in an objective manner is a challenge as it is difficult to distinguish between ability to solve with and without stress. Ability to complete the task in a comfortable manner results in a more productive and healthier workforce by eliminating competency-related stress at work. We use cognitive load as an indicator of stress while understanding the skill and comfort level of software testers in an industrial setting as a case study. We conducted our study using eye tracking techniques. Our findings are reported, and they were corroborated by interacting the participants of the study pre- and post-eye-tracking experiments. The results are encouraging to extend such exercises for additional use cases, e.g., trainer effectiveness evaluation.
Cite this Research Publication : K. R. Chandrika, Amudha J., and Sudarsan, S. D., “Identification and Classification of Expertise Using Eye Gaze–-Industrial Use Case Study with Software Engineers”, in Lecture Notes in Networks and Systems, vol. 120, J. Chand Bansal, Gupta, M. Kumar, Sharma, H., and Agarwal, B., Eds. Singapore: Springer Singapore, 2020, pp. 391-405.