The Cambridge Handbook of Computing Education ResearchSally A. Fincher, Anthony V. Robins This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers. |
Other editions - View all
The Cambridge Handbook of Computing Education Research Sally A. Fincher,Anthony V. Robins Limited preview - 2019 |
The Cambridge Handbook of Computing Education Research Sally A. Fincher,Anthony V. Robins No preview available - 2019 |
The Cambridge Handbook of Computing Education Research Sally A. Fincher,Anthony V. Robins No preview available - 2019 |
Common terms and phrases
abstract ACM Press ACM Technical Symposium activities algorithms analysis approach assessment Australian Computer Society behavior BlueJ chapter classroom cognitive load cognitive science computational thinking Computer Science Education Computing Education Research concept inventory concepts context contract cheating course curriculum debugging discussion effect efficacy engage Engineering Education Research environments evaluation example experience explore feedback Fincher focus gender goal Guzdial ICER IEEE impact instruction instructors interaction International Computing Education introductory programming ITiCSE knowledge learners Learning Sciences machine learning math mathematics mental models methods motivation notional machine novice programmers pair programming participation pedagogic peer instruction plagiarism practice problem Proceedings programming languages Psychology qualitative quantum computing questions Retrieved Science Education SIGCSE skills solving specific strategies structure student learning Symposium on Computer Tangible Computing teachers teaching Technology in Computer theory understanding visual York
