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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
Hrishikesh Bhide – ProQuest LLC, 2024
The meteoric rise in software and technology has altered the paradigm of information security and privacy. Classified information, stored earlier behind locked doors, is now stored on the internet on servers that can be accessed from anywhere on the globe. As a result of these advancements, we are now vulnerable to cyber-attacks. Cyber-attacks are…
Descriptors: Game Based Learning, Learning Strategies, Computer Security, Computer Science Education
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
Prateek Shekhar; Heydi Dominguez; Pramod Abichandani; Craig Iaboni – IEEE Transactions on Education, 2024
Purpose: The presented study was conducted to unpack high school students' motivational influences in engineering/computer science project-based learning (PjBL), using the attention, relevance, confidence, and satisfaction (ARCS) model of motivation as a conceptual framework. Methods: A qualitative research approach was used with student focus…
Descriptors: High School Students, Student Projects, Student Motivation, Learning Motivation
Bayan Masarwa; Hagit Hel-Or; Sharona T. Levy – Journal of Research in Childhood Education, 2024
Computational thinking (CT) activities are increasingly being integrated into early childhood schools. We focus on studying children's learning using an "unplugged" (non-computational) learning unit that considers a teacher's knowledge and classroom space and affords seamless adaptation into the classroom given the objects used in the…
Descriptors: Kindergarten, Computation, Thinking Skills, Educational Games
Davis Krumins; Sandra Schumann; Veiko Vunder; Rauno Põlluäär; Kristjan Laht; Renno Raudmäe; Alvo Aabloo; Karl Kruusamäe – IEEE Transactions on Learning Technologies, 2024
Teaching robotics with the robot operating system (ROS) is valuable for instating good programming practices but requires significant setup steps from the learner. Providing a ready-made ROS learning environment over the web can make robotics more accessible; however, most of the previous remote labs have abstracted the authentic ROS developer…
Descriptors: Teaching Methods, Robotics, Programming, Computer Science Education
Mengning Mu; Man Yuan – Interactive Learning Environments, 2024
The necessity for students to clarify their own cognitive structure and the amount of their knowledge mastery for self-reflection is often ignored in building the student model in the adaptive model, which makes the construction of the cognitive structure pointless. Simultaneously, knowledge forgetting causes students' knowledge level to fall…
Descriptors: Individualized Instruction, Cognitive Processes, Graphs, Cognitive Structures