Background and Context: Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, such tools do not identify plagiarism, nor suggest what assignment submissions are suspicious of plagiarism. Source code plagiarism…

We have recently developed an automated approach to reduce students' rationalization of programming plagiarism and collusion by informing them about the matter and reporting uncommon similarities to them for each of their submissions. Although the approach has benefits, it does not greatly engage students, which might limit those benefits. To…

Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…

Programming students need to be informed about plagiarism and collusion. Hence, we developed an assessment submission system to remind students about the matter. Each submission will be compared to others and any similarities that do not seem a result of coincidence will be reported along with their possible reasons. The system also employs…

Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…

The transfer and teaching of programming and programming related skills has become, increasingly difficult on an undergraduate level over the past years. This is partially due to the number of programming languages available as well as access to readily available source code over the Web. Source code plagiarism is common practice amongst many…