worked on a task with a computerized partner that was named James or Julie. The task was gender-neutral, meaning that it was not directly relevant to being a man or woman. The results showed that subjects behaved the same way toward a computer named James or Julie. Despite these similarities in behavior, subjects estimated that a computer named James would cost them significantly more than one named Julie. The findings show gender shape user perceptions of their computers, which lack the human features that define the characteristic of gender. Confidence-related findings. For spreadsheet problem-solving tasks, (1) female end users had significantly lower self-efficacy than males and (2) women with low self-efficacy were significantly less likely to work effectively with problem-solving features available in the software. In contrast, males' self-efficacy did not impact their effectiveness with these features. In a study of the computer attitudes and self-efficacy of 147 college students, gender differences existed in self-efficacy for complex tasks (such as word processing and spreadsheet software), but not simpler tasks. Also, male students had more experience working with computers and reported more encouragement from parents and friends. Software feature related findings. In spreadsheet problem-solving tasks, female end users were significantly slower to try out unfamiliar features. Females significantly more often agreed with the statement, "I was afraid I would take too long to learn the [untaught feature]." Even if they tried it once, females were significantly less likely to adopt new features for repeated use. For females, unlike for males, self-efficacy predicted the amount of effective feature usage. There was no significant difference in the success of the two genders or in learning how the features worked, implying that females' low self-efficacy about their usage of new features was not an accurate assessment of their problem-solving potential, but rather became a self-fulfilling prophecy. Behavior related findings. In spreadsheet problem-solving tasks, tinkering (playfully experimenting) with features was adopted by males more often than females. While males were comfortable with this behavior, some did it to excess. For females, the amount of tinkering predicted success. Pauses after any action were predictive of better understanding for both genders. Males viewed machines as a challenge, something to be mastered, overcome, and be measured against. They were risk-takers, and they demonstrated this by eagerly trying new techniques and approaches. Females rejected the image of the male hacker as alienating and depersonalizing. Their approach to computers was