Social Ability in Online Groups Representing the Quality of Interactions in Social Computing Environments Sean P. Goggins Drexel University outdoors@acm.org James Laffey & Krista Galyen University of Missouri – Columbia laffeyj@missouri.edu / kgalyen@gmail.com Abstract— We propose Social Ability as a construct that will contribute to the development of social computing models. Completely online group experiences vary according to the composition of tools, tasks and individuals. This conditionality creates challenges for social computing researchers who seek to model social behavior online. We use social ability as a frame to describe how members of completely online groups (COGs) experience the social nature of their interaction and how the nature of their social computing changes over time. We show how social ability measures for COG participants change during collaboration and describe how two social ability factors – Social Presence and Perceived Written Communication Skills – are related to participation and contribution in online group activities. The findings from this mixed methods study show that members who participate in online groups experience increases in perceived written communication skills and peer social presence, suggesting that completely online group work influences social ability. I. INTRODUCTION Social computing is more than the identification of multi- dimensional clusters from usage logs. Parson [16] popularly described the importance of the normative aspects of social organization. Lockwood [15] in turn critiqued this focus on normative social structure, arguing that it is the non-normative or, to use the vernacular of the day, deviant behavior through which systems of social organization evolve. Social computing systems evolve more rapidly than the systems Parsons or Lockwood studied. Social computing represents a form of social experience and a range of new computing capabilities that enable, sustain and constrain social experiences. The phenomenon of rapid change to social structure in social computing contexts calls for the development of new constructs to explicate the nexus of person, task and tools in social computing. Laffey, Lin & Lin [12] developed an instrument to measure social ability: a way of representing students’ experience and perception of social interaction in online learning settings. Social ability is defined as a person’s capacity to associate with fellows and to use shared resources, including members, online tools, and learning resources, to accomplish something of value. Social ability is not a characteristic of an individual, but rather of the relationship of the individual to the context formed by task and tools. For example, someone may feel quite content in managing a face to face meeting or writing an email to a colleague, but overwhelmed by new syntax and multiple inputs in instant messaging. This report uses social ability as a frame to explicate how members of completely online groups (COGs) experience the social nature of their interaction and how the nature of their social computing changes over time. Wang, Zeng, Carley & Mao [23] identify the representation of social context, individual characteristics and group norms in agent-based computational models as one of three vital social computing research issues. Social ability is a construct that will help build models to explain behavior and outcomes in social computing systems. The first step in building such models is decomposing the systems to bring progressively more detailed representations of system behavior into view [25]. Representing system behavior in social computing research requires consideration of the individual characteristics of participants, the technological characteristics of the tools they use to interact and the locales that emerge from this interaction [3,6]. Social computing experiences can be instantiated through a wide mix of technology, tasks and tools. For example, Facebook friends usually have some prior relationship with one another in a face-to-face setting [13] and often interact daily for purposes varying from dating to basic socialization. In this way, Facebook serves to maintain existing social relationships. In other cases, such as completely online graduate student courses, participants may know each other only through the tools used to communicate, coordinate and complete course work. Social ability has the potential to represent important aspects of the online social experiences of members and provide input to the development of models of online social behavior. Social ability is a construct that is proving useful in the study of information and communication technologies designed for computer supported collaborative learning (CSCL). CSCL systems enable new social computing phenomena, including groups who come together online without ever meeting face-to- face. In such settings, people from diverse backgrounds typically come together for some period of time, usually consistent with an academic quarter or semester, to perform group activities, often using only online course management systems like Blackboard, Sakai or Moodle. Completely Online Groups (COGs) are sometimes conflated with studies of free and open source software (FOSS) and Wikipedia groups. Like these other types of technology-centered groups, COGs exchange information and maintain awareness primarily through shared artifacts and asynchronous communication. However, COGs differ from FOSS and Wikipedia groups in two significant ways. First, members of COGs have a common organizational affiliation, similar to work groups or student groups in face-to-face settings. Second, COG members are often assigned to their groups by an organizational leader or instructor. This report uses social ability as a frame to explicate how members of completely online groups (COGs) experience the social nature of their interaction and how the nature of their 2009 International Conference on Computational Science and Engineering 978-0-7695-3823-5/09 $26.00 © 2009 IEEE DOI 10.1109/CSE.2009.339 667 2009 International Conference on Computational Science and Engineering 978-0-7695-3823-5/09 $26.00 © 2009 IEEE DOI 10.1109/CSE.2009.339 667