Alternatives to construct-based programming misconceptions
CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What we know about spreadsheet errors
Journal of End User Computing - End User Development
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
First Steps in Programming: A Rationale for Attention Investment Models
HCC '02 Proceedings of the IEEE 2002 Symposia on Human Centric Computing Languages and Environments (HCC'02)
Everyday Programming: Challenges and Opportunities for Informal Web Development
VLHCC '04 Proceedings of the 2004 IEEE Symposium on Visual Languages - Human Centric Computing
Proceedings of the 2005 international symposium on Wikis
Novice LISP errors: undetected losses of information from working memory
Human-Computer Interaction
Two studies of opportunistic programming: interleaving web foraging, learning, and writing code
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A framework and methodology for studying the causes of software errors in programming systems
Journal of Visual Languages and Computing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
File references, trees, and computational thinking
Proceedings of the fifteenth annual conference on Innovation and technology in computer science education
Cleanroom: Edit-Time Error Detection with the Uniqueness Heuristic
VLHCC '10 Proceedings of the 2010 IEEE Symposium on Visual Languages and Human-Centric Computing
Learning web development: challenges at an earlier stage of computing education
Proceedings of the seventh international workshop on Computing education research
OpenHTML: designing a transitional web editor for novices
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Hi-index | 0.00 |
As part of a larger research agenda to explore web development as a context for learning computational literacy skills, we investigate errors people make while writing code in HTML and CSS. We report on a lab-based study in which 20 participants were video recorded as they completed coding tasks. We have applied the skills-rules-knowledge framework to segment this data by the cognitive causes of errors they made, and present a taxonomy of these errors. Our findings demonstrate how the skills-rules-framework can be used to analyze coding errors, provide insight about the origins of these errors, and suggest ways that the design of web development tools can be improved to support learning and practice with HTML and CSS.