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Direct linkTimothy Kluthe; Hannah Stabler; Amelia McNamara; Andreas Stefik – Computer Science Education, 2025
Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…
Descriptors: Programming Languages, Data Science, Statistical Analysis, Vocabulary
Tianxiao Yang; Jongpil Cheon – Computer Science Education, 2025
Background and context: There were few studies indicating if students' computational thinking (CT) self-efficacy and their CT performance were aligned with each other. Objectives: The study was to investigate if there was a discrepancy between students' CT self-efficacy and their CT performance. Method: Involving 104 non-CS undergraduate students…
Descriptors: Self Efficacy, Computer Science Education, Prediction, Teacher Expectations of Students
Aljumaily, Harith; Cuadra, Dolores; Laefer, Debra F. – Computer Science Education, 2019
Background: Conceptual models are an essential phase in software design, but they can create confusion and reduced performance for students in Database Design courses. Objective: A novel Relational Data Model Validation Tool (MVTool) was developed and tested to determine (1) if students who use MVTool perform better than those who do not, and (2)…
Descriptors: Models, Databases, Computer Science Education, Skills
Moskal, Adon Christian Michael; Wass, Rob – Computer Science Education, 2019
Background and Context: Encouraging undergraduate programming students to think more about their software development processes is challenging. Most programming courses focus on coding skill development and mastering programming language features; subsequently software development processes (e.g. planning, code commenting, and error debugging) are…
Descriptors: Computer Software, Undergraduate Students, Programming, Programming Languages
Touretzky, David S. – Computer Science Education, 2013
Modern robots, like today's smartphones, are complex devices with intricate software systems. Introductory robot programming courses must evolve to reflect this reality, by teaching students to make use of the sophisticated tools their robots provide rather than reimplementing basic algorithms. This paper focuses on teaching with Tekkotsu, an open…
Descriptors: Robotics, Computer Science Education, Programming, Science Curriculum
Sien, Ven Yu – Computer Science Education, 2011
Object-oriented analysis and design (OOAD) is not an easy subject to learn. There are many challenges confronting students when studying OOAD. Students have particular difficulty abstracting real-world problems within the context of OOAD. They are unable to effectively build object-oriented (OO) models from the problem domain because they…
Descriptors: Foreign Countries, Computer Science Education, Undergraduate Students, Computer Software
