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Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
Ronit Shmallo; Adi Katz – Computer Science Education, 2024
Background and Context: Gender research shows that women are better at reading comprehension. Other studies indicate a lower tendency in women to choose STEM professions. Since data modeling requires reading skills and also belongs in the areas of information systems and computer science (STEM professions), these findings provoked our curiosity.…
Descriptors: Gender Differences, Transfer of Training, Databases, Models
Xie, Benjamin; Loksa, Dastyni; Nelson, Greg L.; Davidson, Matthew J.; Dong, Dongsheng; Kwik, Harrison; Tan, Alex Hui; Hwa, Leanne; Li, Min; Ko, Andrew J. – Computer Science Education, 2019
Background and Context: Current introductory instruction fails to identify, structure, and sequence the many skills involved in programming. Objective: We proposed a theory which identifies four distinct skills that novices learn incrementally. These skills are tracing, writing syntax, comprehending templates (reusable abstractions of programming…
Descriptors: Programming, Skill Development, Computer Science Education, Instructional Design
Becker, Brett A.; Glanville, Graham; Iwashima, Ricardo; McDonnell, Claire; Goslin, Kyle; Mooney, Catherine – Computer Science Education, 2016
Programming is an essential skill that many computing students are expected to master. However, programming can be difficult to learn. Successfully interpreting compiler error messages (CEMs) is crucial for correcting errors and progressing toward success in programming. Yet these messages are often difficult to understand and pose a barrier to…
Descriptors: Computer Science Education, Programming, Novices, Error Patterns
Nutbrown, Stephen; Higgins, Colin – Computer Science Education, 2016
This article explores the suitability of static analysis techniques based on the abstract syntax tree (AST) for the automated assessment of early/mid degree level programming. Focus is on fairness, timeliness and consistency of grades and feedback. Following investigation into manual marking practises, including a survey of markers, the assessment…
Descriptors: Programming, Grading, Evaluation Methods, Feedback (Response)
Hughes, Michael C.; Jadud, Matthew C.; Rodrigo, Ma. Mercedes T. – Computer Science Education, 2010
In Java, "System.out.printf" and "String.format" consume a specialised kind of string commonly known as a format string. In our study of first-year students at the Ateneo de Manila University, we discovered that format strings present a substantial challenge for novice programmers. Focusing on their first laboratory we found…
Descriptors: Foreign Countries, Computer Science Education, Programming Languages, Introductory Courses
Jadud, Matthew C. – Computer Science Education, 2005
Syntactically correct code does not fall from the sky; the process that leads to a student's first executable program is not well understood. At the University of Kent we have begun to explore the "compilation behaviours" of novice programmers, or the behaviours that students exhibit while authoring code; in our initial study, we have…
Descriptors: Introductory Courses, Programming, Student Behavior, Educational Technology