Scheduling online oral assessments using an iterative algorithm: A profound software for educational continuity

Abstract

In response to the socioeconomic effects of the global COVID-19 pandemic, including the disruption of educational continuity, an online oral assessment solution is proposed. While the next pandemic is unpredictable, the need for effective student assessment during lockdown is essential. This paper presents an iterative algorithm for scheduling online oral examinations as a profound software innovation capable of securely assessing students remotely while adhering to COVID-19 safety requirements. The efficacy of the software was tested by university tutors and undergraduate students for 60 days on local and web hosts. The results show that the algorithm offers optimal performance despite extraneous factors such as bandwidth capacity, operating system type, and client-side web browsers. The software manages the systematic random pairing of examiners, sessions, courses, and candidates, as well as the automated generation of question papers with a marking rubric. This invention would largely provide assessment entities with significant pedagogical, financial, and technological benefits while ensuring educational continuity regardless of the pandemic's status.

Keywords

• orex
• online oral assessment
• software algorithm
• online examination
• covid-19