Embodying Design

Rethinking design through the lens of embodied cognition provides a novel way of understanding human interaction with technology. In this book, Christopher Baber uses embodied cognition as a lens through which to view both how designers engage in creative practices and how people use designed artifacts. This view of cognition as enactive, embedded, situated, or distributed, without recourse to internal representations, provides a theoretical grounding that makes possible a richer account of human interaction with technology. This understanding of everyday interactions with things in the world reveals opportunities for design to intervene. Moreover, Baber argues, design is an embodied activity in which the continual engagement between designers and their materials is at the heart of design practice. Baber proposes that design and creativity should be considered in dynamic, rather than discrete, terms and explores “task ecologies”—the concept of environment as it relates to embodied cognition. He uses a theory of affordance as an essential premise for design practice, arguing that affordances are neither form nor function but arise from the dynamics within the human-artifact-environment system. Baber explores agency and intent of smart devices and implications of tangible user interfaces and activity recognition for human-computer interaction. He proposes a systems view of human-artifact-environment interactions—to focus on any one component or pairing misses the subtleties of these interactions. The boundaries between components remain, but the borders that allow exchange of information and action are permeable, which gives rise to synergies and interactions

The human factors of automatic speech recognition in control room systems

This thesis addresses the viability of automatic speech recognition for control room systems; with careful system design, automatic speech recognition (ASR) devices can be useful means for human computer interaction in specific types of task. These tasks can be defined as complex verbal activities, such as command and control, and can be paired with spatial tasks, such as monitoring, without detriment. It is suggested that ASR use be confined to routine plant operation, as opposed the critical incidents, due to possible problems of stress on the operators' speech.  It is proposed that using ASR will require operators to adapt a commonly used skill to cater for a novel use of speech. Before using the ASR device, new operators will require some form of training. It is shown that a demonstration by an experienced user of the device can lead to superior performance than instructions. Thus, a relatively cheap and very efficient form of operator training can be supplied by demonstration by experienced ASR operators. From a series of studies into speech based interaction with computers, it is concluded that the interaction be designed to capitalise upon the tendency of operators to use short, succinct, task specific styles of speech. From studies comparing different types of feedback, it is concluded that operators be given screen based feedback, rather than auditory feedback, for control room operation. Feedback will take two forms: the use of the ASR device will require recognition feedback, which will be best supplied using text; the performance of a process control task will require task feedback integrated into the mimic display. This latter feedback can be either textual or symbolic, but it is suggested that symbolic feedback will be more beneficial. Related to both interaction style and feedback is the issue of handling recognition errors. These should be corrected by simple command repetition practices, rather than use error handling dialogues. This method of error correction is held to be non intrusive to primary command and control operations. This thesis also addresses some of the problems of user error in ASR use, and provides a number of recommendations for its reduction

Error by design: Methods for predicting device usability

This paper introduces the idea of predicting ‘designer error’ by evaluating devices using Human Error Identification (HEI) techniques. This is demonstrated using Systematic Human Error Reduction and Prediction Approach (SHERPA) and Task Analysis For Error Identification (TAFEI) to evaluate a vending machine. Appraisal criteria which rely upon user opinion, face validity and utilisation are questioned. Instead a quantitative approach, based upon signal detection theory, is recommended. The performance of people using SHERPA and TAFEI are compared with heuristic judgement and each other. The results of these studies show that both SHERPA and TAFEI are better at predicting errors than the heuristic technique. The performance of SHERPA and TAFEI are comparable, giving some confidence in the use of these approaches. It is suggested that using HEI techniques as part of the design and evaluation process could help to make devices easier to use