| Introduction to This Special Issue on Context in Design | | BIB | 1-2 | |
| Thomas P. Moran | |||
| Borderline Issues: Social and Material Aspects of Design | | BIBA | 3-36 | |
| John Seely Brown; Paul Duguid | |||
| The shared use of artifacts is, we argue, supported by latent border resources, which lie beyond what is usually recognized as the canonical artifact. These unnoticed resources are developed over time as artifacts are integrated into ongoing practice and stable conventions or genres grow up around them. For a couple of reasons, these resources may now deserve increased attention. First, because they lie outside conventional frames of reference, many new designs and design strategies inadvertently threaten to remove resources on which users rely. Second, because of the increasingly rapid proliferation of new technologies, users have less time to develop new border resources. Consequently, we suggest, designers now need to understand more fully the role border resources play and to work more directly to help users develop them. Meeting these goals will require more than an intensification of user-centered design. It will require a fundamental redirection of the way many designers look at both artifacts and users. | |||
| Commentary on Borderline Issues | | BIB | 37-135 | |
| Thomas P. Moran | |||
| Patrolling the Border: A Reply | | BIB | 137-149 | |
| John Seely Brown; Paul Duguid | |||
| Representations and Requirements: The Value of Ethnography in System Design | | BIBA | 151-182 | |
| R. J. Anderson | |||
| For a number of reasons, systems designers have recently shown considerable interest in ethnography. For the most part, this has been used as a method for the specification of end-user requirements for systems. In this article, I argue that most of this interest is predicated in a misunderstanding of ethnography's role in social science. Instead of focusing on its analytic aspects, designers have defined it as a form of data collection. They have done this for very good, design-relevant reasons, but designers do not need ethnography to do what they wish to do. In the central part of this article, I introduce and illustrate an approach to analytic ethnography in human-computer interaction. In the latter sections I take this approach and show how it opens up the play of possibilities for design. These possibilities are illustrated by counterpoising a summary logic of organizational structure such as that associated with the calculus of efficiency and productivity with the local logics of daily organizational life. | |||
| The Role of Visual Fidelity in Computer-Based Instruction | | BIBA | 183-223 | |
| Michael G. Christel | |||
| New digital video technologies provide a wide spectrum of multimedia interface capabilities for educational courses running on personal computers. A formal experiment was conducted using a digital video course on code inspection to determine the effects of such capabilities on recall performance and attitude. The findings suggest that the presentation of material as motion video rather than as a slide show within an interactive video course leads to better recall performance. In addition, the presence of motion video in the interfaces and the use of surrogate travel for navigation promote better student opinions toward the subject matter. | |||
| What Does Pseudo-Code Do? A Psychological Analysis of the Use of Pseudo-Code by Experienced Programmers | | BIBA | 225-246 | |
| Rachel K. E. Bellamy | |||
| The use of pseudo-code and pen and paper are prevalent within the task of programming. However, few studies examine the use of informal notations or the use of the paper medium. In this article, I offer a psychological analysis of the use of pseudo-code and pen and paper by experienced programmers. In particular, I investigate how such informal notations and the paper medium support the cognitively complex task of programming. The basis of the investigation is an analysis of the notes that programmers make during programming. These notes were collected from eight experienced programmers, who were all programming in different languages with different programming environments. Interviews and questionnaires were used as supplementary data. In the analysis based on these data, I describe the kinds of tasks done using pseudo-code and pen and paper, and I offer an account of why these tasks are done using these particular notations and this medium. This study suggests that programmers use pseudo-code and pen and paper to reduce the cognitive complexity of the programming task. | |||
| Introduction to This Special Issue on Exploratory Sequential Data Analysis | | BIB | 247-250 | |
| Penelope M. Sanderson; Carolanne Fisher | |||
| Exploratory Sequential Data Analysis: Foundations | | BIBA | 251-317 | |
| Penelope M. Sanderson; Carolanne Fisher | |||
| Human-computer interaction (HCI) investigators must consider the sequential nature of interaction and must often weigh behavioral, cognitive, and social factors when studying and designing today's increasingly complex systems. In many cases, laboratory experimentation is inappropriate and formal modeling intractable; instead, observational data analysis is frequently the only appropriate empirical approach. Diverse approaches to observational data analysis already exist, which we synthesize as instances of exploratory sequential data analysis (ESDA). In this article, we outline fundamental ESDA characteristics that might help HCI investigators using sequential data make better conceptual and methodological choices. ESDA owes a philosophical debt to exploratory data analysis but focuses on exploring sequential data. Important issues for ESDA are finding an appropriate temporal band for analysis, finding an effective semantics for encoding, and completing an analysis in an acceptable time frame. We survey temporal factors and introduce analysis time:sequence time ratios, which describe the time cost of conducting different types of ESDA. We also introduce the "Eight Cs" -- different general transformations that can be performed on sequential data. We conjecture that the Eight Cs, and their combinations, are critical for supporting scientific inference in ESDA. Distinctions are made among three principal ESDA traditions that are relevant for HCI -- behavioral, cognitive, and social. We indicate how each ESDA tradition has been used in HCI and describe one technique from each tradition. Last, we outline major practical problems for investigators using observational data and, following our framework, suggest ways such problems might be overcome. | |||
| Sequences of Actions for Individual and Teams of Air Traffic Controllers | | BIBA | 319-343 | |
| O. U. Vortac; Mark B. Edwards; Carol A. Manning | |||
| Air traffic controllers participated in high-fidelity simulations of en route air traffic, either singly or with a second team member. The observed stream of time-stamped behaviors and communication events was analyzed using the Pathfinder scaling algorithm, which provides a directional graph of the latent structure in the data. The graphs were found to be similar across levels of traffic complexity, and the triggers for frequently co-occurring activities were equivalent for the individuals and the teams. This suggests that numerous aspects of air traffic control performance are robust and transcend some powerful situational variables. The implications for interface design and automation are discussed. | |||
| Developing Process Models as Summaries of HCI Action Sequences | | BIBA | 345-383 | |
| Frank E. Ritter; Jill H. Larkin | |||
| We describe the utility of process models for summarizing the sequential actions of individuals. Such models describe why users did what they did, what information they used from the outside environment, and what knowledge they used to perform the task. These detailed explanations of users' thoughts and actions can enhance interface design by offering behavior summaries that are inspectable and transferable to new interfaces. Sequential data sets and models for human-computer interaction are often large and complex. We present a computer-supported methodology for developing these models as summaries of sequential data. We illustrate that this methodology can make building and using such models tractable by applying it to an existing model for using an on-line database. | |||
| Management of Repair in Human-Computer Interaction | | BIBA | 385-425 | |
| David Frohlich; Paul Drew; Andrew Monk | |||
| This article reports an investigation of the initiation and management of repair in human-computer interaction from a conversation-analytic perspective. It describes some ways in which pairs of novice users deal with what they see as "trouble" in the operation of a multiwindow database system called Sales and Marketing Information (SAMi). A typical sequence has the character of a user request followed by a pause or computer granting, leading to user repair in initial or third position. Three components of repair are identified: The user attempts to get the computer to undo a previous granting, redo a previous request, or grant a new request. Some common ways in which these components are combined, ordered, and performed are illustrated with reference to transcripts of actual sequences of recorded interaction. The relevance of these findings for design is discussed, together with the future potential of the approach that generated them. | |||
| Characterizing the Sequential Structure of Interactive Behaviors Through Statistical and Grammatical Techniques | | BIBA | 427-472 | |
| Gary M. Olson; James D. Herbsleb; Henry H. Rueter | |||
| Statistical and grammatical techniques are reviewed as an integrated approach to exploratory sequential data analysis (ESDA) for categorical data. The first step is the identification and validation of the categories to be analyzed. The main statistical techniques discussed are log-linear modeling and lag sequential analysis. These methods allow for the statistical evaluation of a wide range of general and specific hypotheses about sequential structure. Grammatical techniques based on definite-clause grammars are described and illustrated, and the complex issue of measuring the goodness of fit of a set of patterns is discussed. Throughout the article, examples from our own research illustrate how the various techniques are used, especially in concert, while carrying out ESDA. In section 6, several other human-computer interaction and computer-supported cooperative work applications of these techniques are discussed. | |||