Effectiveness of end-user debugging software features

Abstract

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.

Why-oriented end-user debugging of naive Bayes text classification

“…Females came into the study with lower self-efficacy (measured via a self-efficacy question set [Compeau and Higgins 1995]) than males, scoring an average of 38 out of a possible 50, compared to 42 for males (Wilcoxon Rank-Sum Test: Z = -2.64, p < .01). This is consistent with similar self-efficacy differences for end users engaging in other complex computer tasks [Beckwith et al 2005, Subrahmaniyan et al 2008]. As we show in the next section, our results about differences in barriers are consistent with prior research in another aspect as well: these prior works showed gender differences in both features used and the strategies end users employed to find and fix errors in spreadsheets.…”

“…Although our data are sparse, our female participants tended to have more questions about UI features than male participants ( research [Beckwith et al 2005] has investigated gender differences in the adoption of debugging features for traditional programs. In that work, females were hesitant about adopting new features; they adopted them less frequently and later in the process than familiar features, and this had repercussion on new bugs introduced through their debugging activities.…”

Cultural Differences and End-User Computing

“…The system used in the study will be Forms/3 with WYSIWYT [2]. Initially a think-aloud study will be carried out.…”

“…Verbalizations and end users' interaction with the application will be recorded for qualitative analysis, similar to procedures done in [3]. If cultural differences appear in feature acceptance and use, a large quantitative study will be carried out to confirm the results [2].…”

“…In addition, Beckwith et al [2] discovered that males and females were different in spreadsheet feature acceptance and use, which significantly impacted their effectiveness in debugging.…”