Sortica: A VR Serious Game to Teach Scheduling Algorithms to Undergraduate Students

Abstract

Scheduling algorithms are an important part of the Computer Science curriculum as these algorithms control how resources are handled and shared within the operating system. Outside the realm of Computer Science, scheduling algorithms are a critical part of project management, enabling the translation of project plans into realistic and efficient operating time tables. Scheduling algorithms are often hard to understand by undergraduate students who struggle to visualise them and understand the practicalities of their implementation. Immersive Serious Games (iSG) have been shown to be an effective approach to visualise abstract concepts and immerse and engage students in practical tasks that require hands-on intervention. This paper presents the case study of “Sortica” a prototype iSG aimed at introducing students unfamiliar with scheduling algorithms to the foundational algorithms of the subject, such as last-in-first-out (LIFO) and first-in-first-out (FIFO). Within “Sortica” students took on the role of a robot worker tasked to rebuild town street buildings using the LIFO and FIFO algorithms. “Sortica” was developed following a human centred iterative approach and was tested through four data collection sessions for a total of 26 undergraduate participants from three modules in programmes that do not teach scheduling algorithms. A pre-test post-test method was used to test knowledge acquisition, the post-test also included questions regarding engagement, perceived learning and the NASA-TLX scale. Additionally, in-game analytics were collected to measure student performance within the iSG. Students were observed during the gameplay and interviewed to collect feedback regarding different aspects of the game. After data cleaning a preliminary data analysis shows that despite a high starting baseline (39% achieved perfect pre-test scores) participants felt that the iSG was highly engaging and helped solidify their understanding of the subject. Preliminary analysis of the NASA-TLX scale shows that the cognitive load was moderately high for the tasks, which could help explain why 4.35% of the valid responses showed a score decrease in the post-test. This work shows that the translation of abstract concepts of scheduling algorithms into mundane tasks makes “Sortica” an engaging tool for introduction and consolidation of basic scheduling algorithms knowledge and understanding. Furthermore, analysis of user friction reveals critical design considerations regarding diegetic interfaces, false affordances, and cognitive load in educational VR