Supporting Group Coursework Assessment in Large Computing Classes through an Open-Source Web Application

Group coursework in computing often suffers from uneven workload distribution, poor communication, and limited visibility for staff, especially in large cohorts. We present an open-source web application that addresses these challenges through automated team allocation (via genetic algorithms), student skill self-assessment, meeting tracking, peer review, and supervisor tools. The system is embedded in a year-long second-year undergraduate module on software design and development (with 300 students in 2025/26) and is replacing manual, ad-hoc processes with structured, data-driven support. Informal trials suggest it helps staff identify struggling teams early and supports fairer marking. Data collection from the first cohort is ongoing. We share findings, reflect on design choices, and discuss implications for adoption in other computing courses.

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Published
2025-12-17
DOI
https://doi.org/10.1145/3772338.3772348
Primary Topic
Information Systems Education and Curriculum Development
Type
article
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article

Supporting Group Coursework Assessment in Large Computing Classes through an Open-Source Web Application

Adriana Wilde, Richard Gomer, S. L. Kitson
Information Systems Education and Curriculum Development
article

Supporting Group Coursework Assessment in Large Computing Classes through an Open-Source Web Application

Adriana Wilde, Richard Gomer, S. L. Kitson
article en

Abstract

Group coursework in computing often suffers from uneven workload distribution, poor communication, and limited visibility for staff, especially in large cohorts. We present an open-source web application that addresses these challenges through automated team allocation (via genetic algorithms), student skill self-assessment, meeting tracking, peer review, and supervisor tools. The system is embedded in a year-long second-year undergraduate module on software design and development (with 300 students in 2025/26) and is replacing manual, ad-hoc processes with structured, data-driven support. Informal trials suggest it helps staff identify struggling teams early and supports fairer marking. Data collection from the first cohort is ongoing. We share findings, reflect on design choices, and discuss implications for adoption in other computing courses.

University of Southampton (GB)
Openalex Percentile: Top 47%
Information Systems Education and Curriculum Development
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