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One area of research in the end-user development area is known as end-user software engineering (EUSE). Research in EUSE aims to invent new kinds of technologies that collaborate with end users to improve the quality of their software. EUSE has become an active research area since its birth in the early 2000s, with a large body of literature upon which EUSE researchers can build. However, building upon these works can be difficult when projects lack connections due to an absence of cross-cutting foundations to tie them together. In this chapter, we advocate for stronger theory foundations and show the advantages through three theory-oriented projects: (1) the Explanatory Debugging approach, to help end users debug their intelligent assistants; (2) the GenderMag method, which identifies problems with gender inclusiveness in EUSE tools and other software; and (3) the Idea Garden approach, to help end users to help themselves in overcoming programming barriers. In each of these examples, we show how having a theoretical foundation facilitated generalizing beyond individual tools to the production of general methods and principles for other researchers to directly draw upon in their own works.

Although there have been many advances in end-user programming environments, recent empirical studies report that programming still remains difficult for end users. We hypothesize that one reason may be lack of effective support for helping end-user programmers problem-solve their own way around barriers they encounter. Therefore, in this paper, we describe the Idea Garden, a concept designed to help end-user programmers generate new ideas and problem-solve when they run into barriers. The Idea Garden has its roots in Minimalist Learning Theory and problem-solving theories. Our proof-of-concept prototype of the Idea Garden concept in the CoScripter end-user programming environment currently targets three barriers reported in end-user programming literature. It does so using an integrated, just-in-time combination of scaffolding for problem-solving strategies, for design patterns, and for programming concepts. Our empirical results showed that this approach helped enduser programmers overcome all three types of barriers our prototype targeted.

Despite decades of research into how professional programmers debug, only recently has work emerged about how end-user programmers attempt to debug programs. Without this knowledge, we cannot build tools to adequately support their needs. This article reports the results of a detailed qualitative empirical study of end-user programmers' sensemaking about a spreadsheet's correctness. Using our study's data, we derived a sensemaking model for end-user debugging and categorized participants' activities and verbalizations according to this model, allowing us to investigate how participants went about debugging. Among the results are identification of the prevalence of information foraging during end-user debugging, two successful strategies for traversing the sensemaking model, potential ties to gender differences in the literature, sensemaking sequences leading to debugging progress, and sequences tied with troublesome points in the debugging process. The results also reveal new implications for the design of spreadsheet tools to support end-user programmers' sensemaking during debugging.

Although there are many systems designed to engage people in programming, few explicitly teach the subject, expecting learners to acquire the necessary skills on their own as they create programs from scratch. We present a principled approach to teach programming using a debugging game called Gidget, which was created using a unique set of seven design principles. A total of 44 teens played it via a lab study and two summer camps. Principle by principle, the results revealed strengths, problems, and open questions for the seven principles. Taken together, the results were very encouraging: learners were able to program with conditionals, loops, and other programming concepts after using the game for just 5 hours.

End-user programmers often get stuck because they do not know how to overcome their barriers. We have previously presented an approach called the Idea Garden, which makes minimalist, on-demand problem-solving support available to end-user programmers in trouble. Its goal is to encourage end users to help themselves learn how to overcome programming difficulties as they encounter them. In this paper, we investigate whether the Idea Garden approach helps end-user programmers problem-solve their programs on their own. We ran a statistical experiment with 123 end-user programmers. The experiment's results showed that, even when the Idea Garden was no longer available, participants with little knowledge of programming who previously used the Idea Garden were able to produce higher-quality programs than those who had not used the Idea Garden.

How can end-user programming environments better help their users overcome programming barriers? We have been investigating an approach called Idea Gardening, which addresses this problem by helping end users to help themselves overcome barriers in the context of “doing”. In this paper, we report on a qualitative empirical study of how effectively an Idea Garden prototype helped end users overcome programming barriers in the CoScripter environment, and the extent to which participants learned after interacting with our features. Our results showed that 9 out of 10 participants who encountered barriers and then used the Idea Garden, overcame their barriers. Further, all 9 went on to demonstrate evidence of having learned the programming concepts, patterns, and strategies relevant to overcoming these barriers.

Despite recent advances in supporting end-user programmers, empirical studies continue to report barriers that end users experience in problem solving with programming environments. We hypothesize that an important barrier that still needs to be overcome is the lack of support for nurturing end-user programmers' ideas on how a program should be written or on how to solve programming difficulties. Therefore, in this paper, we present a qualitative empirical investigation and triangulate the results with theories from problem solving and creativity. Moreover, we explore design opportunities and a design space for “idea gardening”, a new approach to nurturing end-user programmers' ideas and to helping them gradually gain expertise as they overcome barriers. Our results suggest that nurturing end-user programmers' ideas is a fertile area for research with an interesting, multidimensional design space.

In recent years, systems have emerged that enable end users to “mash” together existing web services to build new web sites. However, little is known about how well end users succeed at building such mashups, or what they do if they do not succeed at their first attempt. To help fill this gap, we took a fresh look, from a debugging perspective, at the approaches of end users as they attempted to create mashups. Our results reveal the end users’ debugging strategies and strategy barriers, the gender differences between the debugging strategies males and females followed and the features they used, and finally how their debugging successes and difficulties interacted with their design behaviors.

Programming has recently become more common among ordinary end users of computer systems. We believe that these end-user programmers are not just coders but also designers, in that they interlace making design decisions with coding rather than treating them as two separate phases. To better understand and provide support for the programming and design needs of end users, we propose a design theory-based approach to look at end-user programming. Toward this end, we conducted a think-aloud study with ten end users creating a web mashup. By analyzing users' verbal and behavioral data using Schon's reflection-in-action design model and the notion of ideations from creativity literature, we discovered insights into end-user programmers' problem-solving attempts, successes, and obstacles, with accompanying implications for the design of end-user programming environments for mashups. The contribution of our work is three-fold: 1) the methodology of using a design lens to view programming, 2) evidence, through insights gained, of the usefulness of this approach, and 3) the implications themselves.

In the field of Human-Computer Interaction, provenance refers to the history and genealogy of a document or file. Provenance helps us to understand the evolution and relationships of files; how and when different versions of a document were created, or how different documents in a collection build on each other through copy-paste events. Though methods for tracking provenance and the subsequent use of this meta-data have been proposed and developed into tools, there have been no studies documenting the types and frequency of provenance events in typical computer use. This is knowledge essential for the design of efficient query methods and information displays. We conducted a longitudinal study of knowledge workers at Intel Corporation tracking provenance events in their computer use. We also interviewed knowledge workers to determine the effectiveness of provenance cues for document recall. Our data shows that provenance relationships are common, and provenance cues aid recall.

End-user programmers may not be aware of many software engineering practices that would add greater discipline to their efforts, and even if they are aware of them, these practices may seem too costly (in terms of time) to use. Without taking advantage of at least some of these practices, the software these end users create seems likely to continue to be less reliable than it could be. We are working on several ways of lowering both the perceived and actual costs of systematic software engineering practices, and on making their benefits more visible and immediate. Our approach is to leverage the user's cognitive effort through the use of distributed cognition, in which the system and user collaboratively work systematically to reason about the program the end user is creating. This paper demonstrates this concept with a few of our past efforts, and then presents three of our current efforts in this direction.

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 programmerspsila benefits from these features. In this paper, we compare end-user programmerspsila 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 programmerspsila self-efficacy, attitudes, usage of testing and debugging features, and performance.

Real-time strategy games share many aspects with real situations in domains such as battle planning, air traffic control, and emergency response team management which makes them appealing test-beds for Artificial Intelligence (AI) and machine learning. End-user annotations could help to provide supplemental information for learning algorithms, especially when training data is sparse. This paper presents a formative study to uncover how experienced users explain game play in real-time strategy games. We report the results of our analysis of explanations and discuss their characteristics that could support the design of systems for use by experienced real-time strategy game users in specifying or annotating strategy-oriented behavior.