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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
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Gregor Große-bölting; Dietrich Gerstenberger; Lara Gildehaus; Andreas Mühling; Carsten Schulte – ACM Transactions on Computing Education, 2023
The disciplinary identity as a computer science student has recently received increasing attention as a well-developed subject identity can help with increasing retention, interest, and motivation. Besides, identity theory can serve as an analytical lens for issues around diversity. However, identity is also often perceived as a vague, overused…
Descriptors: Computer Science, Computer Science Education, Students, Computer Uses in Education
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Alicia Garcia-Holgado; Andrea Vazquez-Ingelmo; Francisco Jose Garcia-Penalvo – IEEE Transactions on Education, 2024
Contribution: Gender mainstreaming in university teaching should be covered in all the knowledge areas. This work successfully introduces the gender perspective as part of the methodological approach to teaching and learning in Computer Science. Background: This study describes how gender mainstreaming has been introduced and matured during six…
Descriptors: Computer Science, Gender Differences, Equal Education, Inclusion
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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
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Josh Tenenberg; Donald Chinn – Computer Science Education, 2025
Background and context: We address the question of what computer science students take the discipline to be. How students conceive the discipline can influence whether a student pursues computer science, what particular area within computer science they focus on and whether they persist in the discipline. In this paper, we examine the epistemic…
Descriptors: Computer Science Education, Epistemology, Student Attitudes, Intellectual Disciplines
Nielsen Pereira; Sarah Bright; Zafer Ozen; Shahnaz Safitri; Hernan Castillo-Hermosilla; Brenda C. Matos; Tugce Karatas; Pedro Fonseca – Gifted Child Quarterly, 2025
Technology is an increasingly omnipresent and rapidly changing component of today's world. As a result, there is an urgency to develop talent in the field of computer science (CS). The purpose of this article is to examine ways that educational systems can develop students' talents to fill the need for skilled CS professionals. We provide an…
Descriptors: Computer Uses in Education, Computer Science, Computer Science Education, Talent Development
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Adriana Villavicencio; Wendy Martin; Cheri Fancsali; Maya Israel – Journal of Research on Technology in Education, 2025
Because of the rapid expansion of computer science (CS) education, educational leaders must consider how to recruit, prepare, and support teachers who typically do not have a background in CS. This study examines two professional development (PD) approaches used to introduce CS education to non-CS teachers. We aim to understand if/how each model…
Descriptors: Computer Science Education, Models, Faculty Development, Professional Autonomy
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Liargkovas, Georgios; Papadopoulou, Angeliki; Kotti, Zoe; Spinellis, Diomidis – IEEE Transactions on Education, 2022
Contribution: Determine and analyze the gap between software practitioners' education outlined in the 2014 IEEE/ACM software engineering education knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts. Background: Previous work has uncovered deficiencies in the coverage of computer…
Descriptors: Industry, Knowledge Level, Computer Software, Computer Science
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Hamer, Jessica M. M.; Kemp, Peter E. J.; Wong, Billy; Copsey-Blake, Meggie – International Journal of Science Education, 2023
Despite being in a digital age, the diversity of young people choosing to study and work in computing is of ongoing concern, especially low numbers of girls. This paper aims to determine the profile of students who are more likely to aspire to be computer scientists and provide insights into the key factors that shape their aspirations in this…
Descriptors: Foreign Countries, Secondary School Students, Student Attitudes, Occupational Aspiration
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Brayan Díaz; Collin Lynch; Cesar Delgado; Kevin Han – International Journal of STEM Education, 2025
Background: This paper describes research into two pedagogical approaches to foster transdisciplinarity in a graduate engineering course that involves education and computer science. Leveraging the Communities of Practice framework, we examine how students majoring in computer science can integrate new knowledge from education and computer science…
Descriptors: Graduate Study, Engineering Education, Computer Science, Interdisciplinary Approach
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El-Hamamsy, Laila; Bruno, Barbara; Avry, Sunny; Chessel-Lazzarotto, Frédérique; Dehler Zufferey, Jessica; Mondada, Francesco – ACM Transactions on Computing Education, 2023
Context: With the introduction of Computer Science (CS) into curricula worldwide, teachers' adoption of CS pedagogical content is essential to ensure the long-term success of reform initiatives. Continuing Professional Development (CPD) programs play a key role in this process. Unfortunately, adoption is seldom evaluated in CS-CPDs or CPDs in…
Descriptors: Elementary School Teachers, Computer Science Education, Computer Science, Adoption (Ideas)
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Manuel B. Garcia – Education and Information Technologies, 2025
The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…
Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning
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Saima Ritonummi; Valtteri Siitonen; Markus Salo; Henri Pirkkalainen – Journal of Workplace Learning, 2024
Purpose: The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work. Design/methodology/approach: This study was conducted by using a qualitative critical incident technique-inspired questionnaire. Findings: The findings suggest that workers in the software industry…
Descriptors: Barriers, Computer Software, Computer Science, Attention Control
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Atanu Bhattacharya; Kalyan Dasgupta; Binoy Paine – Journal of Chemical Education, 2024
In this paper, we present a computational chemistry project that demonstrates the quantum dynamics of a free particle, using both classical and quantum computing algorithms. This project can be used in a computational quantum chemistry course in which the instructor introduces quantum computing. Students write their own programs to simulate the…
Descriptors: Chemistry, Science Education, Quantum Mechanics, Computer Science
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Rico-Juan, Juan Ramon; Sanchez-Cartagena, Victor M.; Valero-Mas, Jose J.; Gallego, Antonio Javier – IEEE Transactions on Learning Technologies, 2023
Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…
Descriptors: Artificial Intelligence, Models, Student Behavior, Feedback (Response)
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