Participant Observation in Online Multiplayer Communities

This chapter discusses participant observation as a method of data collection for studying social interaction in online multiplayer games and the communities within them. Participant observation has its roots in the social sciences, and especially in the field of anthropology. True to a natural inquiry approach, studies utilizing participant observation try to understand the actual habitat or “lifeworld” of those participating in the study. This chapter looks at various practical issues connected to conducting participant observation in online multiplayer communities. Examples of data collection are presented, including saving log files, capturing images and video, and writing field notes. Participant observation seems well suited for studying online communities since it can respond well to the challenges of the ever-changing technology and social situations, the need to take into account multiple channels of communication, and the complex and sometimes hidden nature of computer-mediated social interaction.

Methods for the Measurement and Visualization of Social Networks in Multi-User Virtual Worlds

Virtual communities that allow many users to interact in a virtual world, often called multi-user virtual worlds (MUVWs), allow users to explore and navigate the virtual world as well as interact with other users. The communicative interaction within these virtual worlds is often text-based using Internet relay chat (IRC) and related systems. IRC has posed a difficulty for researchers looking to evaluate the interaction by analyzing and interpreting the communication since data is stored in the form of chatlogs. The current chapter explicates methodological procedures for the measurement and visualization of chat-based communicative interaction in MUVWs as social networks. A case study on an educational MUVW, the SciCentr programs sponsored by Cornell University, is used to elaborate methods and related findings.

Participant-Observation as a Method for Analyzing Avatar Design in User-Generated Virtual Worlds

This chapter explores the epistemological, and ethical boundaries of the application of a participant-observer methodology for analyzing avatar design in user-generated virtual worlds. We describe why Second Life was selected as the preferred platform for studying the fundamental design properties of avatars in a situated manner. We will situate the specific case study within the broader context of ethnographic qualitative research methodologies, particularly focusing on what it means to live – and role-play - within the context that one is studying, or to facilitate prolonged engagement in order to have the research results accepted as trustworthy or credible (Lincoln & Guba, 1985). This chapter describes a case study where researchers can extract methods and techniques for studying “in-world” workshops and focus groups. Our speculations and research questions drawn from a close analysis of this case study will illuminate the possible limitations of applying similar hybrid iterations of participation-observation tactics and translations of disciplinary frameworks into the study of user-generated content for future virtual world communities. Finally, we will review the broader epistemological and ethical issues related to the role of the participant-observation researcher in the study of virtual worlds.

Intelligent LMS with an Agent that Learns from Log Data in a Virtual Community

This study describes an agent that acquires domain knowledge related to the content from a learning history log database in a learning community and automatically generates motivational messages for the learner. The unique features of this system are as follows: The agent builds a learner model automatically by applying the decision tree model. The agent predicts a learner’s final status (Failed; Abandon; Successful; or Excellent) using the learner model and his/her current learning history log data. The constructed learner model becomes more exact as the amount of data accumulated in the database increases. Furthermore, the agent compares a learner’s learning processes with “Excellent” status learners’ learning processes stored in the database, diagnoses the learner’s learning processes, and generates adaptive instructional messages for the learner. A comparison between a class of students that used the system and one that did not demonstrates the effectiveness of the system.

Virtual Communities as Tools to Support Teaching Practicum

The impact of Web 2.0 and social networking tools such as virtual communities, on education has been much commented on. The challenge for teachers is to embrace these new social networking tools and apply them to new educational contexts. The increasingly digitally-abled student cohorts and the need for educational applications of Web 2.0 are challenges that overwhelm many educators. This chapter will make three important contributions. Firstly it will explore the characteristics and behaviours of digitally-abled students enrolled in higher education. An innovation of this chapter will be the application of Bourdieu’s notions of capital, particularly social, cultural and digital capital to understand these characteristics. Secondly, it will present a possible use of a commonly used virtual community, Facebook©. Finally it will offer some advice for educators who are interested in using popular social networking communities, similar to Facebook©, in their teaching and learning.

Making the Virtual Real

The emerging critical global collaboration paradigm and the use of virtual learning communities can form structured domains that require complementary methods for educational research. The purpose of this chapter is to illustrate how the social nature of virtual worlds can be used to teach technical writing and the academic research process. A yearlong, mixed methodology, research study is used to demonstrate the effect of this blended learning pedagogical approach on writing apprehension in advanced technical writing courses. Students wrote manuals collaboratively for an audience of their peers. Second Life, the online 3D virtual world created entirely by its residents, was both their subject of study and a mode of meaningful communication.

Semantic Social Network Analysis

In this chapter we present our approach to analyzing such semantic social networks and capturing collective intelligence from collaborative interactions to challenge requirements of Enterprise 2.0. Our tools and models have been tested on an anonymized dataset from Ipernity.com, one of the biggest French social web sites centered on multimedia sharing. This dataset contains over 60,000 users, around half a million declared relationships of three types, and millions of interactions (messages, comments on resources, etc.). We show that the enriched semantic web framework is particularly well-suited for representing online social networks, for identifying their key features and for predicting their evolution. Organizing huge quantity of socially produced information is necessary for a future acceptance of social applications in corporate contexts.

The Sense of e-Learning Community Index (SeLCI) for Computer Supported Collaborative e-Learning (CSCeL)

The aim of this research is to shed light in collaborative e-learning communities in order to observe, analyse and support the e-learning participants. The research context is the Greek teachers’ e-learning community, started in 2003 as part of a project for online teachers’ training and aimed at enabling teachers to acquire new competencies. However, these aims were not met because of passive participation; therefore this study aimed to enhance the Greek teachers’ social engagement to achieve the new skills acquisition. Therefore, the initial sense of community identification was based on empathy; however, because it was inadequate to fully describe the context,, a Sense of E-Learning Community Index (SeLCI) was developed. The new SeLCI attributes were: community evolution; sense of belonging; empathy; trust; intensity characterised by e-learners’ levels of participation and persistence on posting; collaborative e-learning quality measured by the quality in Computer Supported Collaborative eLearning (CSCeL) dialogical sequences, participants’ reflections on own learning; and social network analysis based on: global cohesion anchored in density, reciprocity, cliques and structural equivalence, global centrality derived from in- and out-degree centrality and closeness; and local nodes and centrality in real time. Forty Greek teachers participated in the study for 30 days using Moodle and enhanced Moodle with to measure participation, local Social network Analysis and critical thinking levels in CSCeL. Quantitative, qualitative, Social Network Analysis and measurements produced by the tools were used for data analysis. The findings indicated that each of the SeLCI is essential to enhance participation, collaboration, internalisation and externalisation of knowledge to ensure the e-learning quality and new skills acquisition. Affective factors in CSCeL (sense of belonging, empathy and trust) were also essential to increase reciprocity and promote active participation. Community management, e-learning activities and lastly, the technology appear to affect CSCeL.

Challenges of Analyzing Informal Virtual Communities

Drawing from previous research, this chapter presents major challenges associated with the analysis of interaction patterns in informal virtual communities. Using social network as well as content analysis to understand the structure and nature of interaction in such virtual communities, the goal was understand the physical structure of the community as well as the nature of the themes discussed by community members in an attempt to build a theoretical model of interactions.

Researching Community in Distributed Environments

In this chapter we examine how a variety of research approaches can be applied to the study of cross-blog interactions. Cross-blog interactions can be challenging to study because of they often require the researcher to reconsider traditional notions of temporality, discourse space, and conversation. Further, in many instances they are neither static nor well defined; defining the beginning and end of a discussion as well as locating all components of the discussion can be difficult. For this reason, we advocate a blend of six approaches (social network analysis, content analysis, discourse analysis, conversation analysis, narrative analysis, and ethnography). For each, we discuss strengths and limitations and provide examples of how the approach may be used to help fully capture the complexity of these interactions. Additionally we discuss web-based tools that are helpful when engaged in this type of research.