International Journal of Man-Machine Studies
Programming pedagogy—a psychological overview
ACM SIGCSE Bulletin
Building a rigorous research agenda into changes to teaching
ACSE '98 Proceedings of the 3rd Australasian conference on Computer science education
Constructive cognition in a situated background
International Journal of Human-Computer Studies
The effect of student attributes on success in programming
Proceedings of the 6th annual conference on Innovation and technology in computer science education
Computer
Self-efficacy and mental models in learning to program
Proceedings of the 9th annual SIGCSE conference 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
Constructing a core literature for computing education research
ACM SIGCSE Bulletin
The ability to articulate strategy as a predictor of programming skill
ACE '06 Proceedings of the 8th Australasian Conference on Computing Education - Volume 52
Predictors of success in a first programming course
ACE '06 Proceedings of the 8th Australasian Conference on Computing Education - Volume 52
Wireless Internet and student-centered learning: A Partial Least-Squares model
Computers & Education
Antecedents to End Users' Success in Learning to Program in an Introductory Programming Course
VLHCC '07 Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing
Computer science: a language of technology
ACM SIGCSE Bulletin
Expert Systems with Applications: An International Journal
No tests required: comparing traditional and dynamic predictors of programming success
Proceedings of the 45th ACM technical symposium on Computer science education
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In the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of predictors of programming success. Previous studies have identified a number of predictors. This study examined the effect of a combination of predictors (gender, learning styles, mental models, prior composite academic ability, and medium of instruction) on programming performance. Data were collected anonymously through a website from 131 secondary school students in Hong Kong who opted for computer programming in the Computer and Information Technology curriculum. Partial Least Squares (PLS) modelling was used to test a hypothesized theoretical structural model. All of the five aforementioned variables were either direct or indirect predictors of programming performance and the antecedents accounted for 43.6% of the variance in programming performance. While this study shows the influence of learner characteristics such as gender, learning styles, and mental models on programming performance, it highlights the effect that prior composite academic ability and medium of instruction exert on learning outcomes, which is uncommon among studies of similar purpose. These findings have significant implications for policy makers and educators alike.