Month: May 2018

Traditional person-to-person group brainstorming suffers from three major limitations: (1) free riding; (2) productivity blocking; and (3) evaluation apprehension. An ideal electronic brainstorming tool should address these shortcomings while retaining the dynamic, interactive nature of group brainstorming. Moreover, while the nominal goal of brainstorming is to maximize the number of ideas generated, a variety of secondary goals have been proposed as also having value[1]. In particular, it has been suggested that brainstorming helps build organizational memory in terms of design decisions and creates a ‘status auction’. To address these limitations and secondary goals, we have created an online collaborative mind-mapping tool called COBRAS (Collaborative Online Brainstorming by Roman And Saket). Mind-maps are visual representations of ideas and how they are connected to each other[2]. They are usually laid out like a tree which makes it easy to identify relationships and has been proven to help transfer memory into long-term memory and increase recall[2].

References
Robert I. Sutton and Andrew Hargadon. Brainstorming Groups in Context: Effectiveness in a Product Design Firm. Administrative Science Quarterly, Volume 41, Pages 685-718, 1996
Tony Buzan. The Mind Map Book. New York: Penguin, 1991

Interdisciplinary collaboration is an important component of academic research. It serves as a means to pool physical and intellectual resources, gain social status and knowledge, and bridge ideas from different areas. However, it is difficult to find such collaborators because many researchers do not know what others are working on, nor how their interests might overlap. This problem is paramounted by the fact that office spaces usually consist of people with homogenous sets of interests. In this work, we attempt to support collaboration amongst the various subfields within the computer science department at the Univerity of Maryland (UMD). To this end, we introduce UMDRecorder, a Firefox browser plugin that captures user web activity on “educational” domains. We attempt to use web activity to automatically generate user profile pages which summarize user interests, and match users to other similar users based on these interests. We also employ data mining techniques on top of this data to structure the data into relevant “topics”. Our tool was used by 9 graduate students at UMD for 6 weeks. The results of our evaluation study suggest that web activity is a useful indicator of a user’s research interests, but more sophisticated data mining techniques are required to filter and organize the information in a meaningful way.

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