Evaluating complex digital resources

Squires (1999) discussed the gap between HCI (Human Computer Interaction) and the educational computing communities in their very different approaches to evaluating educational software. This paper revisits that issue in the context of evaluating digital resources, focusing on two approaches to evaluation: an HCI and an educational perspective. Squires and Preece's HCI evaluation model is a predictive model ‐ it helps teachers decide whether or not to use educational software ‐ whilst our own concern is in evaluating the use of learning technologies. It is suggested that in part the different approaches of the two communities relate to the different focus that each takes: in HCI the focus is typically on development and hence usability, whilst in education the concern is with the learner and teacher use

Systems, interactions and macrotheory

A significant proportion of early HCI research was guided by one very clear vision: that the existing theory base in psychology and cognitive science could be developed to yield engineering tools for use in the interdisciplinary context of HCI design. While interface technologies and heuristic methods for behavioral evaluation have rapidly advanced in both capability and breadth of application, progress toward deeper theory has been modest, and some now believe it to be unnecessary. A case is presented for developing new forms of theory, based around generic “systems of interactors.” An overlapping, layered structure of macro- and microtheories could then serve an explanatory role, and could also bind together contributions from the different disciplines. Novel routes to formalizing and applying such theories provide a host of interesting and tractable problems for future basic research in HCI

Practical Strategies for Integrating a Conversation Analyst in an Iterative Design Process

We present a case study of an iterative design process that includes a conversation analyst. We discuss potential benefits of conversation analysis for design, and we describe our strategies for integrating the conversation analyst in the design process. Since the analyst on our team had no previous exposure to design or engineering, and none of the other members of our team had any experience with conversation analysis, we needed to build a foundation for our interaction. One of our key strategies was to pair the conversation analyst with a designer in a highly interactive collaboration. Our tactics have been effective on our project, leading to valuable results that we believe we could not have obtained using another method. We hope that this paper can serve as a practical guide to those interested in establishing a productive and efficient working relationship between a conversation analyst and the other members of a design team.Comment: 11 page

Supporting ethnographic studies of ubiquitous computing in the wild

Ethnography has become a staple feature of IT research over the last twenty years, shaping our understanding of the social character of computing systems and informing their design in a wide variety of settings. The emergence of ubiquitous computing raises new challenges for ethnography however, distributing interaction across a burgeoning array of small, mobile devices and online environments which exploit invisible sensing systems. Understanding interaction requires ethnographers to reconcile interactions that are, for example, distributed across devices on the street with online interactions in order to assemble coherent understandings of the social character and purchase of ubiquitous computing systems. We draw upon four recent studies to show how ethnographers are replaying system recordings of interaction alongside existing resources such as video recordings to do this and identify key challenges that need to be met to support ethnographic study of ubiquitous computing in the wild

Smart labs and social practice: social tools for pervasive laboratory workspaces: a position paper

The emergence of pervasive and ubiquitous computing stimulates a view of future work environments where sharing of information, data and knowledge is easy and commonplace, particularly in highly interactive settings. Much of the work in this area focuses on tool development to support activities such as data collection, data recording and sharing, and so on. We are interested in this kind of technical development, which is both challenging and essential for science communities. But we are also interested in a broader interpretation of knowledge sharing and the human/social side of tools we develop to support this. We are keen to know more about how groups of different kinds of scientists can make their work understandable and shareable with each other in a multidisciplinary setting. This is a complex task because boundaries and barriers can emerge between disciplines engendered by differences in discourses and practices, which may not easily translate into other discipline areas. In the worst case, there may be some hostility between disciplines, or at least doubt and scepticism. Nevertheless, sharing approaches to research, research expertise, data and methods across disciplines can be a very fruitful exercise, and encouragement to engage in this activity is particularly pertinent in the digital era. Issues of privacy and security are also key aspects – knowing when and how to release data or information to other groups is crucial to providing a safe environment for people to work, and there are several sensitivities to be explored here. In this paper we describe an evolving situation that captures many of these issues, which we aim to track longitudinally