RT conference output
T1 Analysis of Learning Records to Detect Student Cheating on Online Exams: Case Study during COVID-19 Pandemic
A1 Balderas Alberico, Antonio
A1 Caballero Hernández, Juan Antonio
A2 Ingeniería Informática
K1 Virtual Learning Environments
K1 Learning Analytics
K1 Cheating
K1 Online Exams
AB In March 2020, due to the Covid19 pandemic, higher education had to switch from face-to-face to exclusively virtual mode overnight. In this unexpected scenario, supervisors also had to adapt the assessment procedures, including the exams. This caused a significant controversy, as, according to many students, supervisors were more concerned about how to prevent students from cheating, than actually measuring their learning. This paper introduces an experience that implemented several of the students' requests in an online exam and conducts a comprehensive analysis of students’ behavior according to the virtual learning environment records. Different existing software tools are used for the analysis, complemented with a Python application ad-hoc developed. The objective indicators gathered provide evidence that some students cheated and invite focusing on evidence-based assessment.
PB ACM
YR 2020
FD 2020-10
LK http://hdl.handle.net/10498/25799
UL http://hdl.handle.net/10498/25799
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 21-sep-2026