A comprehensive bibliometric mapping of automated assessment literature in computer science, analysing publication trends, key authors, citations, and emerging themes.
Automated assessment systems have transformed computer science education by providing scalable evaluation and timely feedback on programming assignments. Over the past decades, research in this domain has expanded rapidly, yielding a vast body of literature across multiple venues and subdisciplines. This study performs a systematic bibliometric analysis of automated assessment literature in computer science education. We map publication activity over time, identify influential venues and core research groups, analyse co-citation networks, and extract key research clusters—ranging from source-code analysis and static/dynamic testing to gamification and formative feedback generation.
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Electronics
Automated assessment tools for programming assignments have become increasingly popular in computing education. These tools offer a cost-effective and highly available way to provide timely and consistent feedback to students. However, when evaluating a logically incorrect source code, there are…
International Journal of Data Science and Analytics
Abstract Clustering of source code is a technique that can help improve feedback in automated program assessment. Grouping code submissions that contain similar mistakes can, for instance, facilitate the identification of students’ difficulties to provide targeted feedback. Moreover, solutions with…
Electronics
Learning to program requires diligent practice and creates room for discovery, trial and error, debugging, and concept mapping. Learners must walk this long road themselves, supported by appropriate and timely feedback. Providing such feedback in programming exercises is not a humanly feasible task.…
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