Evaluation of User Performance in Interactive and Static 3D Maps

Interactive 3D visualizations of geospatial data are currently available and popular through various applications such as Google EarthTM and others. Several studies have focused on user performance with 3D maps, but static 3D maps were mostly used as stimuli. The main objective of this paper was to identify differences between interactive and static 3D maps. We also explored the role of different tasks and inter-individual differences of map users. In the experimental study, we analyzed effectiveness, efficiency, and subjective preferences, when working with static and interactive 3D maps. The study included 76 participants and used a within-subjects design. Experimental testing was performed using our own testing tool 3DmoveR 2.0, which was based on a user logging method and open web technologies. We demonstrated statistically significant differences between interactive and static 3D maps in effectiveness, efficiency, and subjective preferences. Interactivity influenced the results mainly in ‘spatial understanding’ and ‘combined’ tasks. From the identified differences, we concluded that the results of the user studies with static 3D maps as stimuli could not be transferred to interactive 3D visualizations or virtual reality.

THE AUTOMATED GENERATION OF ENGINEERING KNOWLEDGE USING A DIGITAL ENGINEERING TOOL: AN INDUSTRIAL EVALUATION CASE STUDY

In a knowledge-based economy, it will be crucial to capture expertise and rationale in working environments of all kinds as the need develops to understand how people are working, the intuitive processes they use as they carry out tasks and make decisions and trying to determine the most effective methods and rationales for solving problems. Key outputs from this will be the capability to automate decision making activities and supporting training and learning in competitive business environments. Knowledge capture in knowledge-based economies will also be important in a wide range of sectors from the financial and business domains through to engineering and construction. In traditional expert environments, current manual knowledge capture techniques tend to be time-consuming, turgid and, if applied during an activity, interrupt the "expert" whilst they are carrying out the task. The alternative is to do this after the event, which loses important information about the process due to the individual usually forgetting a great deal of the decisions and alternatives they have used during a task session. With the advent and widespread use of computerized technology within business, this paper contends that new opportunities exist with regard to user logging and subsequent data analysis which mean that there is considerable potential for automating or semi-automating this kind of knowledge capture. As a case study demonstrating the possibility of attaining automated knowledge capture, this work investigates product design. Within long lifecycle products of all kinds there is a need to capture the engineering rationale, process, information and knowledge created during a design session. Once these data has been captured, in an automated and unobtrusive manner, it must be represented in a fashion which allows it to be easily accessible, understandable, stored and reused at a later date. This can subsequently be used to inform experienced engineers of decisions taken much earlier in the design process or used to train and support inexperienced engineers while they are moving up the learning curve. Having these data available is especially important in long lifecycle projects since many design decisions are made early on in the process and are then required to be understood by engineers a number of years down the line. There is also the likelihood that if an engineer were to leave during the project, any undocumented design knowledge relating to their contribution to the design process will leave with them. This paper describes research on non-intrusively capturing and formalizing product lifecycle knowledge by demonstrating the automated capture of engineering processes through user logging using an immersive virtual reality (VR) system for cable harness design and assembly planning. Furthermore, several industrial collaborators of the project have been visited to determine what their knowledge capture practices are; these findings are also detailed. Computerized technology and business management systems in the knowledge-based economies of the future will require the capture of expertise as quickly and effectively as possible with minimum overhead to the company along with the formal storage and access to such key data. The application of the techniques and knowledge representations presented in this paper demonstrate the potential for doing this in both engineering and non-engineering domains.