Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/52844
Title: An experimental analysis of assessor specific bias in a programming assessment in multi-assessor scenarios utilizing an eye tracker
Contributor(s): Debnath, Tanmoy (author); Paul, Manoranjan (author); Chakraborty, Subrata  (author)orcid ; Podder, Pallab Kanti (author); Gururajan, Raj (author); Hafeez-Baig, Abdul (author)
Publication Date: 2016
Handle Link: https://hdl.handle.net/1959.11/52844
Abstract: 

It has been experienced and reported by academic institutions around the globe that marking of most subject’s assessment scripts vary when different assessors are utilized for a given subject. To understand the difference, we capture and analysis cognitive response of assessors through the visual pattern while they are marking the scripts. For this, a Java programming assessment from a real life university examination is marked by independent assessors. The assessors marked the scanned assessment scripts on a computer screen in front of an Eye tracker machine and their eye gaze data were recorded real time. Data indicate that different assessors marked the same answer script differently and their visual pattern are also varied although they were given the exact same instructions which demonstrates bias to a degree. For quality marking, several findings including the number of assessors needed are also presented in this manuscript.

Publication Type: Conference Publication
Conference Details: LICE 2016: London International Conference on Education, London, United Kingdom, 14th - 17th November, 2016
Source of Publication: London International Conference on Education (LICE- 2016), p. 135-141
Publisher: London International Conference on Education (LICE)
Place of Publication: United Kingdom
Fields of Research (FoR) 2020: 460105 Applications in social sciences and education
460902 Decision support and group support systems
461199 Machine learning not elsewhere classified
Socio-Economic Objective (SEO) 2020: 160199 Learner and learning not elsewhere classified
280115 Expanding knowledge in the information and computing sciences
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Publisher/associated links: https://infonomics-society.org/lice-2016/lice-abstract-30/
https://liceducation.com/past-conferences/
Appears in Collections:Conference Publication
School of Science and Technology

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