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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
Changming Liang; Lei Du – Journal of Educational Computing Research, 2025
This study delved into the impact of educational robotics, virtual coding, and unplugged coding on the problem-solving, computational thinking (CT), and coding skills of English as a Foreign Language (EFL) learners. Employing a pretest-posttest experimental design, the study encompassed 351 EFL students distributed across four groups to compare…
Descriptors: Foreign Countries, College Students, English (Second Language), Second Language Learning
David P. Bunde; John F. Dooley – PRIMUS, 2024
We present a detailed description of a Cryptography and Computer Security course that has been offered at Knox College for the last 15 years. While the course is roughly divided into two sections, Cryptology and Computer Security, our emphasis here is on the Cryptology section. The course puts the cryptologic material into its historical context…
Descriptors: Technology, Coding, Computer Security, Mathematics Education
Michael E. Ellis; K. Mike Casey; Geoffrey Hill – Decision Sciences Journal of Innovative Education, 2024
Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…
Descriptors: Artificial Intelligence, Programming Languages, Programming, Homework
Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
Sinan Onal; Derya Kulavuz-Onal; Marie Childers – Journal of Educational Technology Systems, 2025
This study investigates the integration and application of ChatGPT among U.S. higher education students across various academic disciplines. Given the recent introduction of ChatGPT in educational contexts, this research aims to understand the specific ways students utilize this tool for academic tasks and their perceived impact on their academic…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Academic Achievement
Robert J. Mills; Emily R. Fyfe; Tanya Beaulieu; Maddy Mills – Instructional Science: An International Journal of the Learning Sciences, 2024
Teachers form expectations that can influence their students' performance, and there are a variety of ways these expectations can be communicated. In the current study, we tested a novel method for communicating expectations via examples of student work--examples that contain basic, entry-level work and communicate low, but manageable expectations…
Descriptors: Teacher Expectations of Students, Academic Achievement, Teaching Methods, Communication (Thought Transfer)
Tarling, Georgie; Melro, Ana; Kleine Staarman, Judith; Fujita, Taro – Pedagogies: An International Journal, 2023
Coding bootcamps targeting diverse learners are increasingly popular. However, little research has focused on the student experience of these courses: what pedagogic practices make learning coding meaningful for them and why. In a previous paper, we proposed a conceptual framework outlining three dimensions of learning opportunities in relation to…
Descriptors: Student Attitudes, Coding, Programming, Computer Science Education
Wang, Xuefei; Wang, Zhuo – Journal of Chemical Education, 2022
Electrochemistry is a branch of chemistry concerned with the interrelation of electrical and chemical effects, in which mathematical equations are employed to describe the fundamental principles of electrode processes and measurement methods. In this work, we present a graphical simulation that provides visual observations of dynamical behavior…
Descriptors: Chemistry, Simulation, Equations (Mathematics), Observation
Chun-Ying Chen – ACM Transactions on Computing Education, 2025
This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…
Descriptors: Models, Learning Motivation, Cognitive Processes, Difficulty Level
Fowler, Max; Smith, David H., IV; Hassan, Mohammed; Poulsen, Seth; West, Matthew; Zilles, Craig – Computer Science Education, 2022
Background and Context: Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective: This study aims to replicate a…
Descriptors: Programming, Computer Science Education, Correlation, Introductory Courses
Hüseyin Çakir – Journal of Learning and Teaching in Digital Age, 2025
This study aims to understand students' views on project development in coding and robotics courses. Focusing on student study groups in this field seeks to provide a broad view using qualitative and quantitative methods. The study group consists of students taking the coding and robotics course. A semi-structured interview form developed by the…
Descriptors: Student Attitudes, Program Development, Coding, Robotics
Schembari, N. Paul – PRIMUS, 2020
Ciphers based on rotor machines were the state-of-the-art in the mid-1900s, with arguably the most famous being the German Enigma. We have found that students have great interest in the Enigma and its cryptanalysis, so we created our own rotor cipher that is simulated with shifting tables and can be cryptanalyzed. Ours and the historic rotor…
Descriptors: Mathematics Instruction, Equipment, Technology, Teaching Methods

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