Automated grading software tool with feedback process to support learning of hardware description languages

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Andrés Francisco Corso Pinzón
Jhon J. Ramírez-Echeverry
Felipe Restrepo-Calle

Abstract

Hardware Description Languages (HDL) have gained popularity in the field of digital electronics design, driven by the increasing complexity of modern electronic circuits. Consequently, supporting students in their learning of these languages is crucial. This work aims to address this need by developing an automated assessment software tool with feedback process to support the learning of HDL and making an educational intervention to support the learning process of students. The tool’s features were selected based on similar developments, and a prototype was designed and implemented. Additionally, an educational intervention was conducted over a five-week period in a Digital Electronics course at the National University of Colombia. Through analyzing students’ interactions with the tool and their perceptions of its usage, the study examined their learning experiences. Among the features highlighted by students as most beneficial for their HDL learning process were the online availability of the tool, the feedback system that helped them identify and correct errors in their code, the provision of immediate feedback, the online editor with syntax highlighting, and the graphical user interface. This work makes two significant contributions to the field of HDL teaching in engineering. Firstly, a publicly accessible HDL grading tool has been developed, offering students immediate formative and summative feedback through an automated grader. Secondly, empirical evidence has been provided regarding the benefits of using such a tool in enhancing students’ learning process.

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How to Cite
Corso Pinzón, A. F., Ramírez-Echeverry, J. J., & Restrepo-Calle, F. (2024). Automated grading software tool with feedback process to support learning of hardware description languages. Research and Practice in Technology Enhanced Learning, 19, 015. https://doi.org/10.58459/rptel.2024.19015
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