Michael Pettitt

Factors of collaborative working: a framework for a collaboration model.

The ability of organisations to support collaborative working environments is of increasing importance as they move towards more distributed ways of working. Despite the attention collaboration has received from a number of disparate fields, there is a lack of a unified understanding of the component factors of collaboration. As part of our work on a European Integrated Project, CoSpaces, collaboration and collaborative working and the factors which define it were examined through the literature and new empirical work with a number of partner user companies in the aerospace, automotive and construction sectors. This was to support development of a descriptive human factors model of collaboration - the CoSpaces Collaborative Working Model (CCWM). We identified seven main categories of factors involved in collaboration: Context, Support, Tasks, Interaction Processes, Teams, Individuals, and Overarching Factors, and summarised these in a framework which forms a basis for the model. We discuss supporting evidence for the factors which emerged from our fieldwork with user partners, and use of the model in activities such as collaboration readiness profiling.

An extended keystroke level model (KLM) for predicting the visual demand of in-vehicle information systems

To assess the potential distraction of In-Vehicle Information Systems (IVIS), simple, low cost evaluation methods are required for use in early design stages. The occlusion technique evaluates IVIS tasks in interrupted vision conditions, aiming to predict likely visual demand. However, the technique necessitates performance-focused user trials utilising robust prototypes, and consequently has limitations as an economic evaluation method. HCI practitioners view the Keystroke Level Model (KLM) as a reliable and valid means of modelling human performance, not requiring empirical trials or working prototypes. This paper proposes an extended KLM, which aims to predict measures based on the occlusion protocol. To validate the new method, we compared results of an occlusion study with predictions based on the assumptions of the extended KLM. Analysis revealed significant correlations between observed and predicted results (R=0.93-0.98) and low error rates (7-13%). In conclusion, the extended KLM shows considerable merit as a first-pass design tool.

Visual Demand Evaluation Methods for In-Vehicle Interfaces

The primary aim of the research presented in this paper is developing a method for assessing the visual demand distraction afforded by in-vehicle information systems IVIS. In this respect, two alternative methods are considered within the research. The occlusion technique evaluates IVIS tasks in interrupted vision conditions, predicting likely visual demand. However, the technique necessitates performance-focused user trials utilising robust prototypes, and consequently has limitations as an economic evaluation method. In contrast, the Keystroke Level Model KLM has long been viewed as a reliable and valid means of modelling human performance and making task time predictions, therefore not requiring empirical trials or a working prototype. The research includes four empirical studies in which an extended KLM was developed and subsequently validated as a means of predicting measures relevant to the occlusion protocol. Future work will develop the method further to widen its scope, introduce new measures, and link the technique to existing design practices.

Curve shape and curvature perception through interactive sonification

In this article we present an approach that uses sound to communicate geometrical data related to a virtual object. This has been developed in the framework of a multimodal interface for product design. The interface allows a designer to evaluate the quality of a 3-D shape using touch, vision, and sound. Two important considerations addressed in this article are the nature of the data that is sonified and the haptic interaction between the user and the interface, which in fact triggers the sound and influences its characteristics. Based on these considerations, we present a number of sonification strategies that are designed to map the geometrical data of interest into sound. The fundamental frequency of various sounds was used to convey the curve shape or the curvature to the listeners. Two evaluation experiments are described, one involves partipants with a varied background, the other involved the intended users, i.e. participants with a background in industrial design. The results show that independent of the sonification method used and independent of whether the curve shape or the curvature were sonified, the sonification was quite successful. In the first experiment participants had a success rate of about 80% in a multiple choice task, in the second experiment it took the participants on average less than 20 seconds to find the maximum, minimum or inflection points of the curvature of a test curve.

Interactive Sonification of Curve Shape and Curvature Data

This paper presents a number of different sonification approaches that aim to communicate geometrical data, specifically curve shape and curvature information, of virtual 3-D objects. The system described here is part of a multi-modal augmented reality environment in which users interact with virtual models through the modalities vision, hearing and touch. An experiment designed to assess the performance of the sonification strategies is described and the key findings are presented and discussed.