Automatic Formative Assessment of Programming Tasks


The onset of Covid-19 has impacted educational processes, particularly assessment, in a way never seen before. Automatic Programming Assessment (APA) can be unfair and inaccurate when used for summative assessment. This paper aimed to investigate to what extent the students had to adapt to automatic assessment and to determine the value of APA as a formative assessment tool. During a practical session in the computer lab, seven tasks were assigned to the students. The tasks resembled a step-by-step guide for writing a complete program that takes a user-specified number of integers, determines the minimum and maximum of these values, and performs calculations involving the minimum and maximum. The code that the students had written was uploaded to the APA system, allowing students to resubmit their work and improve their solutions as they went along. The analysis included marks per task, final marks of students, number of uploads per task, and the total number of uploads per student. General trends of these metrics were also observed. It was established that the majority of the students could successfully complete small programming tasks when re-acting to about two feedback comments per task. APA systems can be instrumental in supporting learning and are useful as a formative assessment tool. As a result of this study, we can point the way to develop systems which are smarter and more flexible.

Author Information
Janet Liebenberg, North-West University, South Africa

Paper Information
Conference: PCE2023
Stream: Assessment Theories & Methodologies

This paper is part of the PCE2023 Conference Proceedings (View)
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To cite this article:
Liebenberg J. (2023) Automatic Formative Assessment of Programming Tasks ISSN: 2758-0962 The Paris Conference on Education 2023: Official Conference Proceedings
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Posted by James Alexander Gordon