If We Build It – Who Will Come? Mary Beth Rosson The Pennsylvania State University 330D IST Building, University Park, PA 16802 [email protected] +1 814 863 2478 tors [21, 23]. But even as these tools emerge, there is the lurking question of this position paper: who are we trying to support with EUP on the web (WebEUP)? If we build it, who will come?

ABSTRACT

This workshop paper raises a question that lurks behind the emerging work on web end-user programming (EUP): who are the users we expect to reach, and are there other users we can reach with a little more effort? I briefly review studies of individual characteristics that may predict EUP adoption, and consider the implications for designing tools and resources to attract the interest and meet the needs of the diverse population of people currently using the web. Informal web development, end-user programming, attention investment model, active learning.

My admittedly rhetorical question subsumes two concerns. First, if we can predict which individuals are most likely to adopt new WebEUP tools, designers can tune the tools and resources to these users’ needs and preferences, increasing the chance of adoption and impact. But even more importantly, we need to understand how to reach beyond those first adoptors, so that novel WebEUP tools can impact the everyday lives of the broadest end-user population possible.

INTRODUCTION

IDENTIFYING PROSPECTS FOR WEB EUP

Author Keywords

A simple answer to the question of who will adopt novel WebEUP tools can quickly be provided through simple logic – the new adopers will be those users who have needs that can be satisfied, and who are able to understand how to use the new tools. But this casual (and so logical!) response misses a critical motivation assumption, namely that these users will recognize their needs, understand that these needs require computational support, and be able and willing to find the tools that can provide this support. Studies of users in other learning situations suggest that many users will not respond in this way, but rather will prefer to just keep doing things as they have always done, even if a new tool might enhance their activities [8].

The diversity and frequency of information-centric web activities have exploded over the past few years. Increasingly, users are active participants in web activities, acting as both consumers and producers of informaton [24]. However, for most end users, programming is still absent from their everyday web activity repertoire. This should be no surprise. Traditionally, programming has been an approach to problem-solving that people choose to be trained in, a skill that depends on multiple and interrelated levels of abstraction and problem decomposition, algorithmic thinking, data analysis and so on [1]. But in recent history, end user programming (EUP) has emerged as an option - interactive tools or specalized languages (e.g., spreadsheets) that hide or scaffold the “programming” that must be done, so that more people can bring computational thinking into their everyday lives [10,13].

How do we break through the pervasive satisficing of end users? I can see several possibilities. We might develop a business case that persuades companyies to require their employees to use our tools. Alternatively, we might take a marketing approach, hiring celebrities as models in a tool adoption movement. Or, we can “tune” our tools to be just interesting enough, to offer just the right services in just the right way, such that users will find and adopt the tools on their own. Once they do so, they will have jumped off the “programming cliff” and may be more likely to consider and apply computational techniques in other settings. As a researcher I vote for this third approach.

In the context of the web, EUP is still in its infancy. The opportunity for impact is huge, given the enormous resources that are available and the size of the web user population. And researchers have begun to make progress, for example with script-recording tools [12] and mashup edi-

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To implement a “right time, right place, right tools” design approach, we must first investigate the WebEUP landscape, to find out who is out there and what they are currently doing, so that we can infer how to insert the appropriate tools into the appropriate contexts.

1

Web Activity Context

One factor likely to influence adoption of WebEUP tools is people’s activity context. In a survey of informal web developers (defined as people who have learned to develop web applications through informal mechanisms) we found intriguing differences between users who were doing web development in work and non-work settings [16,18]. For instance, an experimental scale assessing personal style suggested that people’s tendency to be “fixer-uppers” was predictive of informal development skills in nonwork but not work settings. Instead a “carefulness” index played a bigger role in work settings. We also found that nonwork informal developers are more likely to identify themselves as “nonprogrammers,” perhaps suggesting that their learning activities are driven more by personal interest than by the specific task demands of their web activities. We can see a related pattern in the results of our more recent survey probing end-users’ expectations for future use of web mashups [24]. In that work, after first introducing nonprogrammers to the basic concept of a mashup (using a description and two simple examples), we assessed their initial expectations about difficulty, usefulness, and likely future use of mashup creation. We found that usefulness but not difficulty predicted future expectations of mashup creation; this may indicate that users who have little basis for thinking through a new computational paradigm like mashups are best “attracted” by examples that map to their own personally goals. We also found that end users who pursue their hobbies online are more likely to see mashups as something that they might do in the future. One way to respond to findings such as these is to consider a role for novel WebEUP tools (like mashup builders) within a niche market aimed at the needs of hobbyists. As documented by a recent survey from the Pew Internet and American Life Project [11], hobby interests account for an increasing proportion of American’s online activity. For most people, hobbies are pursued in one’s spare time, and it is in just these situations that users may have the time and energy to look into novel information sources and tools that could enhance their hobby experience. It seems quite reasonable to hope that skills acquired in a hobby context may subsequently be adapted more broadly to other contexts. Technology Initiative

Many of us have anecdotes about the “technology curious” people in our everyday lives – the ones who always show up with the new gadgets, follow the technology blogs, and are first to download and try out new tools that emerge. We often go to these people first when we have a question and are often able to resolve our own just-in-time technology learning needs with their help. Thus it should come as no surprise that like online hobbies, self-reported technology initiative is a predictor of future mashup creation [24]. End users who consider themselves to be the “go to” people for new tools and concepts predict a greater frequency of future mashup creation. These results

complement the curiosity literature, which has shown that surprise motivate humans to look for more information [12; it may be that users who are high on technology initiative are in the habit of looking for technology surprises. With respect to WebEUP design, these patterns suggest that we should further probe technology initiative as an individual differences dimension. Users with high initiative may find and use new tools regardless of where and how we present the tools. But can we attract those with lower initiative? Are there less “technology-centric” views of emerging tools and services that might attract them as well? Computer Attitudes

A user variable that seems clearly related to technology initiative, but one that may be rooted more in society than in personal characteristics, is attitudes toward computing. The open-ended comments in our web survey of informal web developers offered many glimpses of this, with some of these informal tool users making it very clear that they were not programmers and never wanted to be seen as programmers. Software development as a career seems to have a bad reputation with a significant portion of the end user population! Such attitudes have often been called out as causal factors in the remarkably low proportion of women and minority students who pursue careers in information and computer science and technology [2]. In a set of summer workshops with high school girls, we observed the expected effects of these attitudinal variations [17]. In these workshops, junior and senior students were given a scaffolded introduction to simple web development (building a website that connected to and could display queries from a database on a server). After the workshop, we gathered a range of feedback and comments, but one of these asked the girls to anticipate their future success with projects of this sort. We found that the single best predictor of expected success by these young women was the scores we had obtained on a pre-workshop survey of attitudes about computing careers. Wiedenbeck and her colleagues [22] report related results in a study of nonprogrammers in an introductory programming course. These researchers were interested in variable that predict learning outcomes for such a course (measured through a set of debugging questions included on the final exam); they found that initial self-reported computer interest as a reliable predictor of these outcomes. The prospect of influencing users’ general or specific attitudes about computing is daunting, as such attitudes are the product of many inter-related social and learning factors embedded within our everyday lives. However, our earlier comments about aiming novel tools at personal interests and hobby-based activities may be relevant here – if users see a new tool not as related to “programming” but rather as a way to enhance their pursuit of shopping, music, sports, and so on, they may try it out in spite of themselves!

Gender

MEETING IN THE MIDDLE

As mentioned earlier, gender is often raised as an issue for use of computational languages tools, both in the arena of professional practice (women and minorities are less likely to become programmers or IT professionals), and more recently in the arena of EUP [3,4,16]. A great deal of effort has recently been directed at mechanisms for addressing this participation gap, but the problem remains an open and active research topic.

Underlying the discussion presented here is a view of web users as active users – pursuing their everyday goas with whatever knowledge, skills, and resources that are conveniently accessible. The concepts of minimalist design [7] are relevant here, as this design paradigm encourages us to first understand the tasks the users are likely to be following and the mental models they are likely to be applying, and then build tools that leverage this understanding. We are intiating a design program of this sort in our work on web mashup tools for web-active users [24].

Burnett and her colleagues have compiled a series of systematic investigations into this issue, primarily in the domain of spreadsheet debugging [3,4]. A primary factor has been perceptions of self-efficacy with respect to new computing technologies, in other words the levels of achievement that men versus women estimate for specific computer-related tasks (in this case spreadsheet debugging). Women tend to report less self-efficacy, and these scores are related to their tendency to try out and succeed with novel features. In our own work on web development, we found a related effect, that women were less confident that their solutions to the task were sufficient [19]. Further work from the Burnett lab suggests that men and women may have different learning strategies that affects the way they respond to new settings, and that we might be able to design tools to support these different strategies [20].

In this work, we have already conducted two studies of prospective future users of web mashup tools, focusing on a population with the free time and diverse interests that might lead them to experiment with such tools – college students [24]. Working from these studies, we are developing ideas for tools – and importantly for paradigmatic informal learning examples – that may meet these users at just the point where they are able and willing to learn new computational concepts and skills. A related perspective can be found in the Attention Investment Model articulated by Blackwell and colleagues [5,6]. In that view, end users decide whether or not to learn about a novel device based on an assessment of costs, benefits, and risks. We will be able to influence such assessments only if we first understand the motivations and concerns that users are bringing to the table.

The design of WebEUP tools that appeal to both men and women is a challenge because these two subgroups vary on so many factors. Some preliminary results from a web development survey suggest that if women are given an orienting activity (mapping out the entities for an application) they may be more likely to work with the programming functionality a tool provides. But this is clearly a wide-open research problem in need of considerable more work.

CHAPTER IDEAS

If this workshop results in an edited book, I propose to write a chapter that follows up on the findings thus far concerning the likely users of WebEUP, and the associated design implications for building tools that attract and support a diverse population of end users. I would probably work with my PhD student Bernie Zang on such a writing project, illustrating the arguments within the EUP domain of web mashups that we are currently investigating.

Age

One final variable of interest is age. Studies have shown that younger people are more likely to learn informally about how to do web development [16]. This may be at least partly due to the evolution of users over the last generation, from people who learned to do work using noncomputer mechanisms to those to have grown up in a computer-rich context.

ACKNOWLEDGMENTS

I thank the many students who have helped me in my project on informal learning in software development for the past five years. I also thank support from The National Science Foundation through grants ITR CNS-0353309 and ITR CCF-0405612.

But as with gender, age is not a simple factor. Older users do have important contributions to make – namely they are often in the best position to recognize problems in need of solving and solution approaches. When we studied elderly users in a community computing context, we found that the older users were less likely to jump in and use EUP tools (we were studying simulation building in Stagecast Creator), but when they were given the role of “designer”, they were more than able to generate problems and solutions. Elsewhere we have argued for an “old is gold” paradigm where we find ways to combine the wisdom and reflective skills of older users with the youthful enthusiasm and “no fear” orientation of younger users [9].

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