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2020 | OriginalPaper | Buchkapitel

Automatic Generation and Assessment of Student Assignments for Parallel Programming Learning

verfasst von : Zhenxiao Luo, Zelong Wang, Di Wu, Xiaojun Hei, Yunfei Du

Erschienen in: Parallel Architectures, Algorithms and Programming

Verlag: Springer Singapore

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Abstract

The course of parallel programming is becoming more and more important for the education of students majoring in computer science. However, it is not easy to learn parallel programming well due to its high theory and practice requirements. In this paper, we design and implement an automatic assignment generation and assessment system to help students learn parallel programming. The assignments can be generated according to user behaviors and thus able to guide students to learn parallel programming step by step. Besides, it can automatically generate an overall assessment of student assignments by using fuzzy string matching, which provides an approximate reference score of objective questions. Subjective questions can be assessed directly by comparing the answer to the reference answer. This system also provides a friendly user interface for students to complete online assignments and let teachers manage their question database. In our teaching practice, students can learn parallel programming more effectively with the help of such an assignment generation and assessment system.

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Metadaten
Titel
Automatic Generation and Assessment of Student Assignments for Parallel Programming Learning
verfasst von
Zhenxiao Luo
Zelong Wang
Di Wu
Xiaojun Hei
Yunfei Du
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-2767-8_18

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