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Oscar Karnalim – Informatics in Education, 2024
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…
Descriptors: Programming, Integrity, Academic Achievement, Plagiarism
Fowler, Megan; Hallstrom, Jason; Hollingsworth, Joseph; Kraemer, Eileen; Sitaraman, Murali; Sun, Yu-Shan; Wang, Jiadi; Washington, Gloria – Informatics in Education, 2021
Computer science students often evaluate the behavior of the code they write by running it on specific inputs and studying the outputs, and then apply their comprehension to a more general understanding of the code. While this is a good starting point in the student's career, successful graduates must be able to reason analytically about the code…
Descriptors: Computer Science Education, Coding, Computer Software, Abstract Reasoning
Daniele Traversaro; Giorgio Delzanno; Giovanna Guerrini – Informatics in Education, 2024
Concurrency is a complex to learn topic that is becoming more and more relevant, such that many undergraduate Computer Science curricula are introducing it in introductory programming courses. This paper investigates the combined use of Sonic Pi and Team-Based Learning to mitigate the difficulties in early exposure to concurrency. Sonic Pi, a…
Descriptors: Misconceptions, Programming Languages, Computer Science Education, Undergraduate Students
Ginat, David – Informatics in Education, 2021
The notion of algorithm may be perceived in different levels of abstraction. In the lower levels it is an operational set of instructions. In higher levels it may be viewed as an object with properties, solving a problem with characteristics. Novices mostly relate to the lower levels. Yet, higher levels are very relevant for them as well. We…
Descriptors: Problem Solving, Computation, Comparative Analysis, Competence
Source Code Plagiarism Detection in Academia with Information Retrieval: Dataset and the Observation
Karnalim, Oscar; Budi, Setia; Toba, Hapnes; Joy, Mike – Informatics in Education, 2019
Source code plagiarism is an emerging issue in computer science education. As a result, a number of techniques have been proposed to handle this issue. However, comparing these techniques may be challenging, since they are evaluated with their own private dataset(s). This paper contributes in providing a public dataset for comparing these…
Descriptors: Plagiarism, Computer Science Education, Comparative Analysis, Problem Solving
Gabriele, Lorella; Bertacchini, Francesca; Tavernise, Assunta; Vaca-Cárdenas, Leticia; Pantano, Pietro; Bilotta, Eleonora – Informatics in Education, 2019
In the last years, a growing trend in different educational contexts focused on Computational Thinking (CT) skills acquisition for both in-service teachers and students. But very low attention has been paid to pre-service teachers' education in regards to CT skills. To solve this issue, an empirical experimentation has been carried out with 141…
Descriptors: Foreign Countries, Lesson Plans, Computation, Thinking Skills