Usability of a mobile, group communication prototype while rendezvousing

Mobile phones are increasingly being used collaboratively by social networks of users in spite of the fact that they are primarily designed to support single users and one-to-one communication. It is not well understood how services such as group SMS, SMS-based discussion lists and mobile instant messaging (IM) will be used by mobile groups in natural settings. Studying specific instances of common styles of in situ, group interaction may provide a way to see behavior patterns and typical interaction problems. We conducted a study of a mobile, group communication probe used during a rendezvousing activity in an urban environment. Usability problems relating to group usage, phone interface design and context were identified. Several major issues included: multitasking during message composition and reading; speed of text entry; excessive demand on visual attention; and ambiguity of intended recipients. We suggest that existing mobile device designs are overly-focused on individual users to the detriment of usability for mobile groups of users. We provide recommendations for the design of future mobile, group interfaces, used in similar situations to those explored here

Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.