In recent years, research into gender differences has established that individual differences in how people problem-solve often cluster by gender. Research also shows that these differences have direct implications for software that aims to support users' problem-solving activities, and that much of this software is more supportive of problem-solving processes favored (statistically) more by males than by females. However, there is almost no work considering how software practitioners—such as User Experience (UX) professionals or software developers—can find gender-inclusiveness issues like these in their software. To address this gap, we devised the GenderMag method for evaluating problem-solving software from a gender-inclusiveness perspective. The method includes a set of faceted personas that bring five facets of gender difference research to life, and embeds use of the personas into a concrete process through a gender-specialized Cognitive Walkthrough. Our empirical results show that a variety of practitioners who design software—without needing any background in gender research—were able to use the GenderMag method to find gender-inclusiveness issues in problem-solving software. Our results also show that the issues the practitioners found were real and fixable. This work is the first systematic method to find gender-inclusiveness issues in software, so that practitioners can design and produce problem-solving software that is more usable by everyone.

Although there has been significant research into gender regarding educational and workplace practices, there has been little awareness of gender differences as they pertain to software tools, such as spreadsheet applications, that try to support end users in problem-solving tasks. Although such software tools are intended to be gender agnostic, we believe that closer examination of this premise is warranted. Therefore, in this paper, we report an end-to-end investigation into gender differences with spreadsheet software. Our results showed gender differences in feature usage, feature-related confidence, and tinkering (playful exploration) with features. Then, drawing implications from these results, we designed and implemented features for our spreadsheet prototype that took the gender differences into account. The results of an evaluation on this prototype showed improvements for both males and females, and also decreased gender differences in some outcome measures, such as confidence. These results are encouraging, but also open new questions for investigation. We also discuss how our results compare to generalization studies performed with a variety of other software platforms and populations.

Little is known about the strategies end-user programmers use in debugging their programs, and even less is known about gender differences that may exist in these strategies. Without this type of information, designers of end-user programming systems cannot know the "target" at which to aim, if they are to support male and female end-user programmers. We present a study investigating this issue. We asked end-user programmers to debug spreadsheets and to describe their debugging strategies. Using mixed methods, we analyzed their strategies and looked for relationships among participants' strategy choices, gender, and debugging success. Our results indicate that males and females debug in quite different ways, that opportunities for improving support for end-user debugging strategies for both genders are abundant, and that tools currently available to end-user debuggers may be especially deficient in supporting debugging strategies used by females.

Although there have been a number of studies of end-user software development tasks, few of them have considered gender issues for real end-user developers in real-world environments for end-user programming. In order to be trusted, the results of such laboratory studies must always be re-evaluated with fewer controls, more closely reflecting real-world conditions. Therefore, the research question in this paper is whether the results of a gender HCI controlled study generalize - to real-world end-user developers, in a real-world spreadsheet environment, using a real-world spreadsheet. Our findings are that the concepts revealed by the original laboratory study appear to be quite robust, being demonstrated in multiple ways in this real-world environment.

There has been little research into how end-user programming environments can provide explanations that could fill a critical information gap for end-user debuggers - help with debugging strategy. To address this need, we designed and prototyped a video-based approach for explaining debugging strategy, and accompanied it with a text-only approach. We then conducted a qualitative empirical study with end-user debuggers. The results reveal the influences of the explanations on end-user debuggers' decision making, how users reacted to the video versus textual media, and the information gaps the explanations closed. The results also reveal issues of particular importance to explanations of this type.

Although researchers have begun to explicitly support end-user programmers' debugging by providing information to help them find bugs, there is little research addressing the right content to communicate to these users. The specific semantic content of these debugging communications matters because, if the users are not actually seeking the information the system is providing, they are not likely to attend to it. This paper reports a formative empirical study that sheds light on what end users actually want to know in the course of debugging a spreadsheet, given the availability of a set of interactive visual testing and debugging features. Our results provide in sights into end-user debuggers' information gaps, and further suggest opportunities to improve end-user debugging systems' support for the things end-user debuggers actually want to know.

Earlier research on gender effects with software features intended to help problem-solvers in end-user debugging environments has shown that females are less likely to use unfamiliar software features. This poses a serious problem because these features may be key to helping them with debugging problems. Contrasting this with research documenting males' inclination for tinkering in unfamiliar environments, the question arises as to whether encouraging tinkering with new features would help females overcome the factors, such as low self-efficacy, that led to the earlier results. In this paper, we present an experiment with males and females in an end-user debugging setting, and investigate how tinkering behavior impacts several measures of their debugging success. Our results show that the factors of tinkering, reflection, and self-efficacy, can combine in multiple ways to impact debugging effectiveness differently for males than for females.

We have been working to uncover gender differences in the ways males and females problem solve in end-user programming situations, and have discovered differences in males' versus females' use of several debugging features. Still, because this line of investigation is new, knowing exactly what to look for is difficult and important information could escape our notice. We therefore decided to bring data mining techniques to bear on our data, with two aims: primarily, to expand what is known about how males versus females make use of end-user debugging features, and secondarily, to find out whether data mining could bring new understanding to this research, given that we had already studied the data manually using qualitative and quantitative methods. The results suggested several new hypotheses in how males versus females go about end-user debugging tasks, the factors that play into their choices, and how their choices are associated with success

Although gender differences in a technological world are receiving significant research attention, much of the research and practice has aimed at how society and education can impact the successes and retention of female computer science professionals-but the possibility of gender issues within software has received almost no attention. If gender issues exist with some types of software features, it is possible that accommodating them by changing these features can increase effectiveness, but only if we know what these issues are. In this paper, we empirically investigate gender differences for end users in the context of debugging spreadsheets. Our results uncover significant gender differences in self-efficacy and feature acceptance, with females exhibiting lower self-efficacy and lower feature acceptance. The results also show that these differences can significantly reduce females' effectiveness.

Previous research has revealed gender differences that impact females' willingness to adopt software features in end users' programming environments. Since these features have separately been shown to help end users problem solve, it is important to female end users' productivity that we find ways to make these features more acceptable to females. In this paper, we draw from our ongoing work with users to help inform our design of theory-based methods for encouraging effective feature usage by both genders. This design effort is the first to begin addressing the gender differences in the ways that people go about problem solving in end-user programming situations.

End-user programmers, because they are human, make mistakes. However, past research has not considered how visual end-user debugging devices could be designed to ameliorate the effects of mistakes. This paper empirically examines oracle mistakes - mistakes users make about which values are right and which are wrong - to reveal differences in how different types of oracle mistakes impact the quality of visual feedback about bugs. We then consider the implications of these empirical results for designers of end-user software engineering environments.

Although researchers have begun to explicitly support end-user programmers' debugging by providing information to help them find bugs, there is little research addressing the proper mechanism to alert the user to this information. The choice of alerting mechanism can be important, because as previous research has shown, different interruption styles have different potential advantages and disadvantages. To explore impacts of interruptions in the end-user debugging domain, this paper describes an empirical comparison of two interruption styles that have been used to alert end-user programmers to debugging information. Our results show that negotiated-style interruptions were superior to immediate-style interruptions in several issues of importance to end-user debugging, and further suggest that a reason for this superiority may be that immediate-style interruptions encourage different debugging strategies.

A human-centric issue that has not been considered in the design of end-user programming environments is whether gender differences exist that are important to the design of these environments. Ignoring this issue would miss the opportunity of enhancing the effectiveness of end-user programmers by incorporating appropriate mechanisms to support gender-associated differences in decision making, learning, and problem solving. This paper takes a first step toward building a foundation for investigating this issue by surveying gender difference literature from five domains with an eye toward possible implications for end-user programming. We present a taxonomy of this literature, and derive a number of specific issues for each element of the taxonomy (stated as hypotheses). This foundation provides a starting point for organized investigations into issues that may be important for making breakthroughs in the effectiveness of end-user programmers

Emerging research has sought to bring effective debugging devices to end-user programmers. This research has largely focused on how well such devices bring genuine "functional" rewards to end users. However, emerging models of programming behavior indicate that another, often ignored, type of reward-perceivable rewards-can play an equally vital role in how well debugging devices serve end users. Using an empirically evaluated fault localization device, this paper investigates the impact such perceivable rewards can have on end-user debugging. Our results indicate that perceivable rewards alone can significantly improve the effectiveness and understanding of end users performing debugging tasks.

Despite their ability to help with program correctness, assertions have been notoriously unpopular---even with professional programmers. End-user programmers seem even less likely to appreciate the value of assertions; yet end-user programs suffer from serious correctness problems that assertions could help detect. This leads to the following question: can end users be enticed to enter assertions? To investigate this question, we have devised a curiosity-centered approach to eliciting assertions from end users, built on a surprise-explain-reward strategy. Our follow-up work with end-user participants shows that the approach is effective in encouraging end users to enter assertions that help them find errors.