Title: Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups
Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data. more »« less
Morgan, Jonathan H.; Zhao, Jun; Sedlacek, Andrea; Chen, Lena; Piper, Hayley; Beck, Yliana; Rogers, Kimberly B.; Hoey, Jesse; Schröder, Tobias
(, Advances in Social Simulation)
null; null
(Ed.)
We review Affect Control Theory (ACT), a mathematically formalized theory that integrates sociological insights about the symbolic construction of the social order with psychological knowledge about cognitive-affective mechanisms, as a basis for equipping computational agents in social simulations with a sense of sociality. After explaining theoretical foundations and describing previous applications of ACT at the dyadic and group level, we describe a case study from an ongoing research project aimed at understanding self-organized online collaboration in software development with ACT-based social simulations.
Pe-Than, Ei Pa; Dabbish, Laura; Herbsleb, James D.
(, Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing)
Social coding platforms such as GitHub are increasingly becoming a digital workspace for the production of non-software digital artifacts. Since GitHub offers unique features that are different from traditional ways of collaborative writing, it is interesting to investigate how GitHub features are used for writing. In this paper, we present the preliminary findings of a mixed-methods, case study of collaboration practices in a GitHub book project. We found that the use of GitHub depended on task interdependence and audience participation. GitHub's direct push method was used to coordinate both loosely- and tightly-coupled work, with the latter requiring collaborators to follow socially-accepted conventions. The pull-based method was adopted once the project was released to the public. While face-to-face and online meetings were prominent in the early phases, GitHub's issues became instrumental for communication and project management in later phases. Our findings have implications for the design of collaborative writing tools.
Morrison-Smith, Sarah; Boucher, Christina; Sarcevic, Aleksandra; Noyes, Noelle; O’Brien, Catherine; Cuadros, Nazaret; Ruiz, Jaime
(, Humanities and Social Sciences Communications)
Abstract Biological and biomedical research is increasingly conducted in large, interdisciplinary collaborations to address problems with significant societal impact, such as reducing antibiotic resistance, identifying disease sub-types, and identifying genes that control for drought tolerance in plants. Many of these projects are data driven and involve the collection and analysis of biological data at a large-scale. As a result, life-science projects, which are frequently diverse, large and geographically dispersed, have created unique challenges for collaboration and training. We examine the communication and collaboration challenges in multidisciplinary research through an interview study with 20 life-science researchers. Our results show that both the inclusion of multiple disciplines and differences in work culture influence collaboration in life science. Using these results, we discuss opportunities and implications for designing solutions to better support collaborative tasks and workflows of life scientists. In particular, we show that life science research is increasingly conducted in large, multi-institutional collaborations, and these large groups rely on “mutual respect” and collaboration. However, we found that the interdisciplinary nature of these projects cause technical language barriers and differences in methodology affect trust. We use these findings to guide our recommendations for technology to support life science. We also present recommendations for life science research training programs and note the necessity for incorporating training in project management, multiple language, and discipline culture.
Gillen, Andrew L.; Grohs, Jacob R.; Matusovich, Holly M.; Kirk, Gary R.
(, Journal of Engineering Education)
Abstract BackgroundCalls to improve learning in science, technology, engineering, and mathematics (STEM), and particularly engineering, present significant challenges for school systems. Partnerships among engineering industry, universities, and school systems to support learning appear promising, but current work is limited in its conclusions because it lacks a strong connection to theoretical work in interorganizational collaboration. Purpose/HypothesisThis study aims to reflect more critically on the process of how organizations build relationships to address the following research question: In a public–private partnership to integrate engineering into middle school science curriculum, how do stakeholder characterizations of the collaborative process align with existing frameworks of interorganizational collaboration? Design/MethodThis qualitative, embedded multiple case study considered in‐depth pre‐ and post‐year interviews with teachers, administrators, industry, and university personnel during the first year of the Partnering with Educators and Engineers in Rural Schools (PEERS) program. Transcripts were analyzed using a framework of interorganizational collaboration operationalized for our context. ResultsResults provide insights into stakeholder perceptions of collaborative processes in the first year of the PEERS program across dimensions of collaboration. These dimensions mapped to three central discussion points with relevance for school–university–industry partnerships: school collaboration as an emergent and negotiated process, tension in collaborating across organizations, and fair share in collaborating toward a social goal. ConclusionsTaking a macro‐level look at the collaborative processes involved enabled us to develop implications for collaborative stakeholders to be intentional about designing for future success. By systematically applying a framework of collaboration and capitalizing on the rich situational findings possible through a qualitative approach, we shift our understanding of collaborative processes in school–university–industry partnerships for engineering education and contribute to the development of collaboration theory.
Sankaranarayanan, Sreecharan; Kandimalla, Siddharth Reddy; Cao, Mengxin; Maronna, Ignacio; An, Haokang; Bogart, Chris; Murray, R. Charles; Hilton, Michael; Sakr, Majd; Penstein Rosé, Carolyn
(, Information and Learning Sciences)
Purpose In response to the evolving COVID-19 pandemic, many universities have transitioned to online instruction. With learning promising to be online, at least in part, for the near future, instructors may be thinking of providing online collaborative learning opportunities to their students who are increasingly isolated from their peers because of social distancing guidelines. This paper aims to provide design recommendations for online collaborative project-based learning exercises based on this research in a software engineering course at the university level. Design/methodology/approach Through joint work between learning scientists, course instructors and software engineering practitioners, instructional design best practices of alignment between the context of the learners, the learning objectives, the task and the assessment are actualized in the design of collaborative programming projects for supporting learning. The design, first segments a short real-time collaborative exercise into tasks, each with a problem-solving phase where students participate in collaborative programming, and a reflection phase for reflecting on what they learned in the task. Within these phases, a role-assignment paradigm scaffolds collaboration by assigning groups of four students to four complementary roles that rotate after each task. Findings By aligning each task with granular learning objectives, significant pre- to post-test learning from the exercise as well as each task is observed. Originality/value The roles used in the paradigm discourage divide-and-conquer tendencies often associated with collaborative projects. By requiring students to discuss conflicting ideas to arrive at a consensus implementation, their ideas are made explicit, thus providing opportunities for clarifying misconceptions through discussion and learning from the collaboration.
Jesse Hoey, Meiyappan Nagappan. Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups. Retrieved from https://par.nsf.gov/biblio/10296729. SocArXiv .
Jesse Hoey, Meiyappan Nagappan. Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups. SocArXiv, (). Retrieved from https://par.nsf.gov/biblio/10296729.
Jesse Hoey, Meiyappan Nagappan.
"Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups". SocArXiv (). Country unknown/Code not available. https://par.nsf.gov/biblio/10296729.
@article{osti_10296729,
place = {Country unknown/Code not available},
title = {Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups},
url = {https://par.nsf.gov/biblio/10296729},
abstractNote = {Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.},
journal = {SocArXiv},
author = {Jesse Hoey, Meiyappan Nagappan},
editor = {null}
}
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