Fixing the program my computer learned: barriers for end users, challenges for the machine
Proceedings of the 14th international conference on Intelligent user interfaces
What Is End-User Software Engineering and Why Does It Matter?
IS-EUD '09 Proceedings of the 2nd International Symposium on End-User Development
Males' and Females' Script Debugging Strategies
IS-EUD '09 Proceedings of the 2nd International Symposium on End-User Development
End-user mashup programming: through the design lens
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Gender differences and programming environments: across programming populations
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Gender HCI: what about the software?
Proceedings of the 28th ACM International Conference on Design of Communication
The state of the art in end-user software engineering
ACM Computing Surveys (CSUR)
Where are my intelligent assistant's mistakes? a systematic testing approach
IS-EUD'11 Proceedings of the Third international conference on End-user development
Why-oriented end-user debugging of naive Bayes text classification
ACM Transactions on Interactive Intelligent Systems (TiiS)
Gender pluralism in problem-solving software
Interacting with Computers
End-user debugging strategies: A sensemaking perspective
ACM Transactions on Computer-Human Interaction (TOCHI)
End-User Software Engineering and Why it Matters
Journal of Organizational and End User Computing
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Recent research has begun to report that female end-user programmers are often more reluctant than males to employ features that are useful for testing and debugging. These earlier findings suggest that, unless such features can be changed in some appropriate way, there are likely to be important gender differences in end-user programmers’ benefits from these features. In this paper, we compare end-user programmers’ feature usage in an environment that supports end-user debugging, against an extension of the same environment with two features designed to help ameliorate the effects of low self-efficacy. Our results show ways in which these features affect female versus male enduser programmers’ self-efficacy, attitudes, usage of testing and debugging features, and performance.