Programmer/nonprogrammer differences in specifying procedures to people and computers
Papers presented at the first workshop on empirical studies of programmers on Empirical studies of programmers
What best predicts computer proficiency?
Communications of the ACM
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Constructivism in computer science education
Journal of Computers in Mathematics and Science Teaching
Wanted: CS1 students. no experience required
Proceedings of the 35th SIGCSE technical symposium on Computer science education
Interacting factors that predict success and failure in a CS1 course
Working group reports from ITiCSE on Innovation and technology in computer science education
A multi-national study of reading and tracing skills in novice programmers
Working group reports from ITiCSE on Innovation and technology in computer science education
Factors affecting the success of non-majors in learning to program
Proceedings of the first international workshop on Computing education research
Students' alternative standards for correctness
Proceedings of the first international workshop on Computing education research
Software engineering as a model of understanding for learning and problem solving
Proceedings of the first international workshop on Computing education research
An investigation of potential success factors for an introductory model-driven programming course
Proceedings of the first international workshop on Computing education research
What do beginning students know, and what can they do?
Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education
Commonsense computing: what students know before we teach (episode 1: sorting)
Proceedings of the second international workshop on Computing education research
Predictors of success in a first programming course
ACE '06 Proceedings of the 8th Australasian Conference on Computing Education - Volume 52
Commonsense computing: using student sorting abilities to improve instruction
Proceedings of the 38th SIGCSE technical symposium on Computer science education
Education: Paving the way for computational thinking
Communications of the ACM - Designing games with a purpose
Commonsense computing (episode 5): algorithm efficiency and balloon testing
ICER '09 Proceedings of the fifth international workshop on Computing education research workshop
A typology of CS students' preconditions for learning
Koli '08 Proceedings of the 8th International Conference on Computing Education Research
Work in progress - commonsense probability: preconceptions of entering engineering students
FIE'09 Proceedings of the 39th IEEE international conference on Frontiers in education conference
Commonsense understanding of concurrency: computing students and concert tickets
Communications of the ACM
Commonsense computing (episode 6): logic is harder than pie
Proceedings of the 10th Koli Calling International Conference on Computing Education Research
Introducing computational thinking in education courses
Proceedings of the 42nd ACM technical symposium on Computer science education
Computational Thinking in Elementary and Secondary Teacher Education
ACM Transactions on Computing Education (TOCE)
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As the third in a series of projects investigating commonsense computing -- the relevant knowledge that students have before any formal study of computing -- we examine students' commonsense understanding of concurrency. Specifically, we replicated (with modifications) an experiment by Ben-David Kolikant. [2] Ben-David Kolikant's data were gathered from high-school seniors who had previously studied computing, at the beginning of an advanced class in concurrent and distributed programming. Modifying one of her questions to reflect our students' lack of background, we asked students at five different institutions, in the first week of CS1, to describe in English the problems that might arise when more than one person is selling seats to a concert. Almost all students (97%) identified the problem of interest -- that a race condition may occur between sellers. 73% of students identified at least one possible solution. We found that the categorizations developed by Ben-David Kolikant were also meaningful when applied to our data, that our beginning CS1 students are more likely to give centralized solutions (as opposed to decentralized ones) than Ben-David Kolikant's concurrency students, and that the granularity of solutions is finer among the more experienced students.