HCJul 26, 2021

AutoGrad: Automated Grading Software for Mobile Game Assignments in SuaCode Courses

arXiv:2107.12244v110 citations
Originality Synthesis-oriented
AI Analysis

This addresses the need for efficient grading in online arts education, particularly in an African context, but it is incremental as it applies existing grading methodologies to a new domain and platform.

The paper tackles the problem of automatically grading mobile game assignments in online courses by presenting AutoGrad, a cross-platform system that uses static and dynamic analysis to evaluate graphical Processing programs on Android smartphones, and it was tested on over 1000 students, reducing grading time and effort for 4 assignments.

Automatic grading systems have been in existence since the turn of the half-century. Several systems have been developed in the literature with either static analysis and dynamic analysis or a hybrid of both methodologies for computer science courses. This paper presents AutoGrad, a novel portable cross-platform automatic grading system for graphical Processing programs developed on Android smartphones during an online course. AutoGrad uses Processing, which is used in the emerging Interactive Media Arts, and pioneers grading systems utilized outside the sciences to assist tuition in the Arts. It also represents the first system built and tested in an African context across over thirty-five countries across the continent. This paper first explores the design and implementation of AutoGrad. AutoGrad employs APIs to download the assignments from the course platform, performs static and dynamic analysis on the assignment to evaluate the graphical output of the program, and returns the grade and feedback to the student. It then evaluates AutoGrad by analyzing data collected from the two online cohorts of 1000+ students of our SuaCode smartphone-based course. From the analysis and students' feedback, AutoGrad is shown to be adequate for automatic assessment, feedback provision to students, and easy integration for both cloud and standalone usage by reducing the time and effort required in grading the 4 assignments required to complete the course.

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