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Workshop Automatische Bewertung von Programmieraufgaben

https://dl.gi.de/handle/20.500.12116/27934
Siehe auch https://www.abp-workshop.de/.
Auflistung nach:

Auflistung Workshop Automatische Bewertung von Programmieraufgaben nach Autor:in "Brocker, Annabell"

1 - 2 von 2
  • Konferenzbeitrag
    A Grammar and Parameterization-Based Generator for Python Programming Exercises
    (Proceedings of the Sixth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2023), 2023) Peeß, Philipp; Brocker, Annabell; Röpke, René; Schroeder, Ulrik
    As the importance of programming education grows, the demand for a sufficient number of practical exercises in courses also increases. To accommodate this need without significantly increasing the instructors' workload, a programming exercise generator capable of generating exercises for independent practice is considered. This research mainly focuses on determining suitable generation methods and creating a modular and extensible generator structure. The current generator implementation uses parameterization and a grammar-based generation approach in order to provide generated exercises directly to students in their programming environment. Furthermore, the generator can act as a foundation for further research and be extended with additional generation methods, creating the possibility of exploring artificial intelligence for the generation of programming exercises.
  • Konferenzbeitrag
    pycheckmate – Addressing Challenges in Automatic Code Evaluation and Feedback Generation for Python Novices
    (Proceedings of the Sixth Workshop "Automatische Bewertung von Programmieraufgaben" (ABP 2023), 2023) Brocker, Annabell; Schroeder, Ulrik
    In academic settings, code assessment differs from traditional software testing by encompassing not only functional correctness but also critical structural aspects like naming conventions and programming concepts. Conventional static analysis tools like Pylint and Flake8, along with input-output unit tests, are deemed inadequate for introductory Python courses. To address this gap, this paper introduces pycheckmate, a library, tailored for automatic testing and targeted feedback in introductory Python programming courses.