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Addressing student fatigue in computer architecture courses

Abstract: Understanding the architecture of a processor can be uninteresting and deterring for computer science students, since low-level details of computer architecture are often perceived to lack real-world impact. These courses typically have a strong practical component where students learn the fundamentals of the computer architecture and the handling of input/output operations through the development of simple programs in a low-level assembly programming language. Since these practical sessions require a strong involvement, student attendance and withdrawal rates are poor, lowering academic results and introducing a negative feedback loop that preconditions students to dislike them. This article introduces a new methodology for the practical sessions of Computer Organization and Design courses. This methodology disavows the use of simulators and focuses on actual hardware to promote a feeling of proximity to the execution and outcome of the programs. The proposed setup uses Raspberry Pi devices to encourage students to work autonomously, due to their low cost, capability of running an OS, and rich ecosystem of simple hardware devices. The setup is completed with RISC OS, which combines a simple window-based graphical interface with a low-level management of the hardware without requiring software abstraction layers. The article presents the methodology and the UCDebug tool, developed to help students debug their codes in RISC OS. After the introduction of the new setup at the University of Cantabria, academic results and student satisfaction have improved. The setup has also allowed to sustain a similar organization of the courses throughout the COVID-19 pandemic.

 Autoría: Fuentes P., Camarero C., Herreros D., Mateev V., Vallejo F., Martinez C.,

 Fuente: IEEE Transactions on Learning Technologies, 2022, 15(2), 238-251

 Editorial: IEEE

 Año de publicación: 2022

 Nº de páginas: 14

 Tipo de publicación: Artículo de Revista

 DOI: 10.1109/TLT.2022.3163631

 ISSN: 1939-1382,2372-0050

 Proyecto español: TIN2016-76635- C2-2-R

 Url de la publicación: https://doi.org/10.1109/TLT.2022.3163631