AI, Biometric Analysis, and Emerging Cheating Detection Systems: The Engineering of Academic Integrity?

Colleges of Education at Arizona State University and the University of South Florida. c/o Editor, USF EDU162, 4202 East Fowler Avenue, Tampa, FL 33620-5650. Tel: 813-974-3400; Fax: 813-974-3826; Web site: https://epaa.asu.edu/ojs/index.php/epaa

Y

18

Artificial Intelligence; Bibliometrics; Cheating; Identification; Integrity; Higher Education; Foreign Countries; Technology Uses in Education; Accountability; Educational Policy; Outsourcing; Resistance (Psychology)

United States; United Kingdom

1068-2341

Cheating behaviors have been construed as a continuing and somewhat vexing issue for academic institutions as they increasingly conduct educational processes online and impose metrics on instructional evaluation. Research, development, and implementation initiatives on cheating detection have gained new dimensions in the advent of artificial intelligence (AI) applications; they have also engendered special challenges in terms of their social, ethical, and cultural implications. An assortment of commercial cheating-detection systems have been injected into educational contexts with little input on the part of relevant stakeholders. This paper expands several specific cases of how systems for the detection of cheating have recently been implemented in higher education institutions in the US and UK. It investigates how such vehicles as wearable technologies, eye scanning, and keystroke capturing are being used to collect the data used for anti-cheating initiatives, often involving systems that have not gone through rigorous testing and evaluation for their validity and potential educational impacts. The paper discusses accountability- and policy-related issues concerning the outsourcing of cheating detection in institutional settings in the light of these emerging technological practices as well as student resistance against the systems involved. The cheating-detection practices can place students in a disempowered, asymmetrical position that is often at substantial variance with their cultural backgrounds.

As Provided

2023

EJ1374195