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Niloofar Mansoor; Cole S. Peterson; Michael D. Dodd; Bonita Sharif – ACM Transactions on Computing Education, 2024
Background and Context: Understanding how a student programmer solves different task types in different programming languages is essential to understanding how we can further improve teaching tools to support students to be industry-ready when they graduate. It also provides insight into students' thought processes in different task types and…
Descriptors: Biofeedback, Eye Movements, Computer Science Education, Programming Languages
Thin-Yin Leong; Nang-Laik Ma – INFORMS Transactions on Education, 2024
This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in…
Descriptors: Spreadsheets, Simulation, Teaching Methods, Computer Science Education
Gabriela de Carvalho Barros Bezerra; Wilk Oliveira; Ana Cláudia Guimarães Santos; Juho Hamari – ACM Transactions on Computing Education, 2024
Despite recent high interest among researchers and practitioners in learning programming, even the most dedicated learners can struggle to find motivation for studying and practicing programming. Therefore, in recent years, several strategies (e.g., educational games, flipped classrooms, and visual programming languages) have been employed to…
Descriptors: Gamification, Programming, Computer Science Education, Workshops
Fatima Abu Deeb; Timothy Hickey – Computer Science Education, 2024
Background and Context: Auto-graders are praised by novice students learning to program, as they provide them with automatic feedback about their problem-solving process. However, some students often make random changes when they have errors in their code, without engaging in deliberate thinking about the cause of the error. Objective: To…
Descriptors: Reflection, Automation, Grading, Novices
Andrew Millam; Christine Bakke – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper is part of a multi-case study that aims to test whether generative AI makes an effective coding assistant. Particularly, this work evaluates the ability of two AI chatbots (ChatGPT and Bing Chat) to generate concise computer code, considers ethical issues related to generative AI, and offers suggestions for how to improve…
Descriptors: Coding, Artificial Intelligence, Natural Language Processing, Computer Software
Mark Monnin; Lori L. Sussman – Journal of Cybersecurity Education, Research and Practice, 2024
Data transfer between isolated clusters is imperative for cybersecurity education, research, and testing. Such techniques facilitate hands-on cybersecurity learning in isolated clusters, allow cybersecurity students to practice with various hacking tools, and develop professional cybersecurity technical skills. Educators often use these remote…
Descriptors: Computer Science Education, Computer Security, Computer Software, Data
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Agnieszka Kwapisz; Brock J. LaMeres – IEEE Transactions on Education, 2024
Contribution: This study synthesizes insights into the thematic focuses and linguistic attributes that resonate most in engineering faculty collaborations aimed at fostering entrepreneurial mindsets (EMs). It provides a roadmap for educators and institutions to effectively communicate and encourage entrepreneurial thinking in engineering.…
Descriptors: Engineering Education, Entrepreneurship, College Faculty, Teacher Collaboration
Stephanie Yang; Miles Baird; Eleanor O’Rourke; Karen Brennan; Bertrand Schneider – ACM Transactions on Computing Education, 2024
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects--negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and…
Descriptors: Computer Science Education, Troubleshooting, Programming, Teaching Methods
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
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
Catalina Cortázar; Iñaki Goñi; Andrea Ortiz; Miguel Nussbaum – ACM Transactions on Computing Education, 2024
Integrating graduate education with professional skills development is still a challenge. People's beliefs about learning impact their learning processes. Therefore, we need to understand the mindset of graduates to determine best practices for promoting professional skills development. In this study, we explore the perspective of computing…
Descriptors: Computer Science Education, Graduate Students, Computer Literacy, Job Skills
Amanda Nolte; Hilary Mead; Chrystalla Mouza; Rosalie Rolón-Dow; Sotheara Veng; Lori Pollock – Journal of Technology and Teacher Education, 2024
Teachers' lack of knowledge abound computational thinking (CT) and limited opportunities to incorporate CT in existing curricula pose unique challenges at the elementary level. Despite the crucial role of professional development (PD) in preparing elementary school teachers to integrate CT in classroom instruction, there is little research…
Descriptors: Computation, Interdisciplinary Approach, Faculty Development, Computer Science Education
Rong, Wenge; Xu, Tianfan; Sun, Zhiwei; Sun, Zian; Ouyang, Yuanxin; Xiong, Zhang – IEEE Transactions on Education, 2023
Contribution: In this study, an object tuple model has been proposed, and a quasi-experimental study on its usage in an introductory programming language course has been reported. This work can be adopted by all C language teachers and students in learning pointer and array-related concepts. Background: C language has been extensively employed in…
Descriptors: Models, Introductory Courses, Programming, Computer Science Education
Hawlitschek, Anja; Berndt, Sarah; Schulz, Sandra – Computer Science Education, 2023
Background and Context: Pair programming is an important approach to fostering students' programming and collaborative learning skills. However, the empirical findings on pair programming are mixed, especially concerning effective instructional design. Objective: The objective of this literature review is to provide lecturers with systematic…
Descriptors: Cooperative Learning, Programming, Computer Science Education, College Students