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Václav Šimandl; Jirí Vanícek; Václav Dobiáš – Informatics in Education, 2025
Research on collaborative learning of computer science has been conducted primarily in programming. This paper extends this area by including short tasks (such as those used in contests like the Bebras Challenge) that cover many other computer science topics. The aim of this research is to explore how problem-solving in pairs differs from…
Descriptors: Cooperative Learning, Problem Solving, Computer Science, Computer Science Education
Arif Ainur Rafiq; Mochamad Bruri Triyono; Istanto Wahyu Djatmiko; Ratna Wardani; Thomas Köhler – Informatics in Education, 2023
In today's world, the ability to think computationally is essential. The skillset expected of a computer scientist is no longer solely based on the old stereotype but also a crucial skill for adapting to the future. This perspective presents a new educational challenge for society. Everyone must have a positive attitude toward understanding and…
Descriptors: Computation, Thinking Skills, Bibliometrics, Computer Science
Tobias Kohn; Jacqueline Staub – Informatics in Education, 2024
The choice of programming language for education is an intensely debated topic. On the one hand, the programming language is supposed to be "relevant" in that its organisation, structures, and paradigms adhere to current standards and best practices in industry and academia. On the other hand, the programming language is expected to be…
Descriptors: Computer Science Education, Programming, Data Processing, Philosophy
Juraj Hromkovic; Regula Lacher – Informatics in Education, 2025
The design of algorithms is one of the hardest topics of high school computer science. This is mainly due to the universality of algorithms as solution methods that guarantee the calculation of a correct solution for all potentially infinitely many instances of an algorithmic problem. The goal of this paper is to present a comprehensible and…
Descriptors: Algorithms, Computer Science Education, High School Students, Teaching Methods
Antoni Wilinski; Joanna Olkowicz; Sebastian Agata; Alicja Szostkiewicz; Szymon Guzik; Arkadiusz Wojtak; Pawel Tomkiewicz – Informatics in Education, 2025
This paper presents survey results involving students from three fields of study (computer science, business, and pedagogy), positing that computer science students exhibit distinct patterns in the spectrum of multiple intelligences compared to students in social sciences disciplines. The study involved over 300 students, revealing statistically…
Descriptors: Computer Science Education, Intellectual Disciplines, Majors (Students), Multiple Intelligences
Paul Biberstein; Thomas Castleman; Luming Chen; Shriram Krishnamurthi – Informatics in Education, 2024
CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…
Descriptors: Data Science, Secondary School Students, Programming, Open Source Technology
Lutz Terfloth; Vivien Lohmer; Friederike Kern; Carsten Schulte – Informatics in Education, 2025
Transcripts play a crucial role in qualitative research in computing education, with significant implications for the credibility and reproducibility of findings. However, unreflective and inconsistent transcription standards may unintentionally introduce biases, potentially undermining the validity of research outcomes and the collective progress…
Descriptors: Phonetic Transcription, Computer Science Education, Educational Research, Credibility
Ivanilse Calderon; Williamson Silva; Eduardo Feitosa – Informatics in Education, 2024
Teaching programming is a complex process requiring learning to develop different skills. To minimize the challenges faced in the classroom, instructors have been adopting active methodologies in teaching computer programming. This article presents a Systematic Mapping Study (SMS) to identify and categorize the types of methodologies that…
Descriptors: Foreign Countries, Undergraduate Study, Programming, Computer Science Education
Walter Gander – Informatics in Education, 2024
When the new programming language Pascal was developed in the 1970's, Walter Gander did not like it because because many features which he appreciated in prior programming languages were missing in Pascal. For example the block structure was gone, there were no dynamical arrays, no functions or procedures were allowed as parameters of a procedure,…
Descriptors: Computer Software, Programming Languages, Algorithms, Automation
Felix Winkelnkemper; Lukas Höper; Carsten Schulte – Informatics in Education, 2024
When it comes to mastering the digital world, the education system is more and more facing the task of making students competent and self-determined agents when interacting with digital artefacts. This task often falls to computing education. In the traditional fields of computing education, a plethora of models, guidelines, and principles exist,…
Descriptors: Digital Literacy, Computer Uses in Education, Models, Computer Science Education
Lukas Höper; Carsten Schulte – Informatics in Education, 2024
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…
Descriptors: Student Empowerment, Data Use, Computer Science Education, Artificial Intelligence
Michael Kolling – Informatics in Education, 2024
The principles of programming language design for learning and teaching have been described and discussed for several decades. Most influential was the work of Niklaus Wirth, describing principles such as simplicity, modularity, orthogonality, and readability. So why is this still an area of fundamental disagreement among educators? Why can…
Descriptors: Programming Languages, Design, Novices, Computer Science Education
Marjahan Begum; Pontus Haglund; Ari Korhonen; Violetta Lonati; Mattia Monga; Filip Strömbäck; Artturi Tilanterä – Informatics in Education, 2024
There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating…
Descriptors: Foreign Countries, College Students, Prerequisites, Computer Science Education
Deise Monquelate Arndt; Ramon Mayor Martins; Jean Carlo Rossa Hauck – Informatics in Education, 2025
Critical thinking is a fundamental skill for 21st-century citizens, and it should be promoted from elementary school and developed in computing education. However, assessing the development of critical thinking in educational contexts presents unique challenges. In this study, a systematic mapping was carried out to investigate how to assess the…
Descriptors: Critical Thinking, Elementary Secondary Education, Computer Science Education, 21st Century Skills
Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
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…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education

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