COORDINATION AND COLLABORATION ACTIVITIES IN COOPERATIVE INFORMATION SYSTEMS

2004 ◽  
Vol 13 (01) ◽  
pp. 1-7 ◽  
Author(s):  
ANDREA OMICINI ◽  
SASCHA OSSOWSKI

The notions of coordination, collaboration and cooperation have originated a number of heterogeneous research lines in diverse scientific areas, both inside and outside Computer Science — along with a number of different acceptations for the terms as well. The basic and almost obvious correlation between these terms, however, has not yet led to a satisfactory scientific overall picture that could put them in the right perspective, emphasizing their commonalities and distinctions. Still, there is a great potential for cross-fertilization between the different strands of work. In particular, if the mutual relationship between these terms was understood and commonly accepted, it would be much easier to adapt and apply many innovative ideas developed by the different communities to the field of cooperative information systems. In this article, we outline a possible unified conceptual framework, by suitably re-interpreting findings from Activity Theory. There, a clear definition for both coordination and cooperation as collaborative activities can be found and used as a reference, which is centred around the notion of (coordination) artifact. Then, we gladly introduce four contributions, selected from the best papers of the 18th ACM Symposium on Applied Computing and suitably revised for the International Journal on Cooperative Information Systems, that show how some of the most recent results of the research on coordination can be fruitfully exploited and applied to the field of cooperative information systems.

Examples of the value that can be created and captured through crowdsourcing go back to at least 1714, when the UK used crowdsourcing to solve the Longitude Problem, obtaining a solution that would enable the UK to become the dominant maritime force of its time. Today, Wikipedia uses crowds to provide entries for the world’s largest and free encyclopedia. Partly fueled by the value that can be created and captured through crowdsourcing, interest in researching the phenomenon has been remarkable. For example, the Best Paper Awards in 2012 for a record-setting three journals—the Academy of Management Review, Journal of Product Innovation Management, and Academy of Management Perspectives—were about crowdsourcing. In spite of the interest in crowdsourcing—or perhaps because of it—research on the phenomenon has been conducted in different research silos within the fields of management (from strategy to finance to operations to information systems), biology, communications, computer science, economics, political science, among others. In these silos, crowdsourcing takes names such as broadcast search, innovation tournaments, crowdfunding, community innovation, distributed innovation, collective intelligence, open source, crowdpower, and even open innovation. The book aims to assemble papers from as many of these silos as possible since the ultimate potential of crowdsourcing research is likely to be attained only by bridging them. The papers provide a systematic overview of the research on crowdsourcing from different fields based on a more encompassing definition of the concept, its difference for innovation, and its value for both the private and public sectors.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Meir Meshulam ◽  
Liat Hasenfratz ◽  
Hanna Hillman ◽  
Yun-Fei Liu ◽  
Mai Nguyen ◽  
...  

AbstractDespite major advances in measuring human brain activity during and after educational experiences, it is unclear how learners internalize new content, especially in real-life and online settings. In this work, we introduce a neural approach to predicting and assessing learning outcomes in a real-life setting. Our approach hinges on the idea that successful learning involves forming the right set of neural representations, which are captured in canonical activity patterns shared across individuals. Specifically, we hypothesized that learning is mirrored in neural alignment: the degree to which an individual learner’s neural representations match those of experts, as well as those of other learners. We tested this hypothesis in a longitudinal functional MRI study that regularly scanned college students enrolled in an introduction to computer science course. We additionally scanned graduate student experts in computer science. We show that alignment among students successfully predicts overall performance in a final exam. Furthermore, within individual students, we find better learning outcomes for concepts that evoke better alignment with experts and with other students, revealing neural patterns associated with specific learned concepts in individuals.


1997 ◽  
Vol 25 (4) ◽  
pp. 38-47 ◽  
Author(s):  
Mary J. Granger ◽  
Elizabeth S. Adams ◽  
Christina Björkman ◽  
Don Gotterbarn ◽  
Diana D. Juettner ◽  
...  

2012 ◽  
Vol 27 (2) ◽  
pp. 96-99 ◽  
Author(s):  
Salvatore T. March ◽  
Fred Niederman

We must look ahead at today's radical changes in technology, not just as forecasters but as actors charged with designing and bringing about a sustainable and acceptable world. New knowledge gives us power for change: for good or ill, for knowledge is neutral. The problems we face go well beyond technology: problems of living in harmony with nature, and most important, living in harmony with each other. Information technology, so closely tied to the properties of the human mind, can give us, if we ask the right questions, the special insights we need to advance these goals. Herbert A. Simon (2000)


2021 ◽  
Vol 50 (2) ◽  
pp. 30-32
Author(s):  
Patrick Valduriez

I have been working on research in data management for the last 40 years. I like my job and my research institution (Inria, the French national research institute for computer science), which have offered me great opportunities to learn a lot, do good work, get to know smart and nice people and overall feel useful. However, since the early days of my mid-career, the research environment, including academia and industry, has certainly become more complex, making the move from junior (or pre-tenure) researcher to senior researcher quite challenging. Based on my experience, I review some of the main questions and challenges and give some hints on how to deal with them. I'll sometimes use stories and anecdotes to illustrate the point.


Author(s):  
Ewa Andrejczuk ◽  
Rita Berger ◽  
Juan A. Rodriguez-Aguilar ◽  
Carles Sierra ◽  
Víctor Marín-Puchades

AbstractNowadays the composition and formation of effective teams is highly important for both companies to assure their competitiveness and for a wide range of emerging applications exploiting multiagent collaboration (e.g. crowdsourcing, human-agent collaborations). The aim of this article is to provide an integrative perspective on team composition, team formation, and their relationship with team performance. Thus, we review the contributions in both the computer science literature and the organizational psychology literature dealing with these topics. Our purpose is twofold. First, we aim at identifying the strengths and weaknesses of the contributions made by these two diverse bodies of research. Second, we aim at identifying cross-fertilization opportunities that help both disciplines benefit from one another. Given the volume of existing literature, our review is not intended to be exhaustive. Instead, we have preferred to focus on the most significant contributions in both fields together with recent contributions that break new ground to spur innovative research.


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