Alibi: A Graph-Driven Algorithm for Attendance Capturing

Class attendance has been an instrument for measuring students' commitment to learning over the years. Educators often rely on capturing class attendance as it allows them to pinpoint under-performing students, determine the effectiveness of classes, and understand the root causes of chronic absenteeism using techniques such as traditional attendance forms or online portals. With the advancements in artificial intelligence and other new technologies, new techniques such as facial recognition have also been applied in attendance capturing. All techniques used for these tasks have one or more drawbacks (such as easy manipulation, ineffectiveness, increase administration efforts, untraceable attendance or missing attendance data), hence, there is a consistent need to device new and more effective techniques of capturing class attendances. In this paper we have proposed a new technique/algorithm called Alibi; inspired by the act of finding alibis in crime investigations. Alibi uses the proximity of students to construct undirected graphs and automatically implies which students are present at the location. We have implemented Alibi in two applications: one mobile application that students can use to find Alibis in the classroom, and the other is a web application that provides a dashboard to the instructor for managing their class attendances. We have evaluated Alibi and its effectiveness amongst students and educators, both categories of users stated that this is a very useful tool and technique for attendance capturing. Out of 101 students, 90.1 % of which suggested that they would use Alibi as an attendance capturing system due to it's ease of use and simplicity. The four educators who interacted with the tool also expressed a positive sentiment.