The role of social networks in students��� learning experiences Ilaria Liccardi School of Electronics and Computer Science B32 University Road University of Southampton Hampshire, UK SO171BJ il05r@ecs.soton.ac.uk Asma Ounnas School of Electronics and Computer Science B32 University Road University of Southampton Hampshire, UK SO171BJ ao05r@ecs.soton.ac.uk Reena Pau School of Electronics and Computer Science B32 University Road University of Southampton Hampshire, UK SO171BJ rp05r@ecs.soton.ac.uk Elizabeth Massey Faculty of Technology Brayford Pool University of Lincoln Lincolnshire, UK LN6 7TS bmassey@lincoln.ac.uk P��ivi Kinnunen Department of Computer Science and Engineering Helsinki University of Technology Helsinki, 02015, Finland Paivi.Kinnunen@cs.hut.fi Sarah Lewthwaite Learning Science Research Institute School of Education University of Nottingham Nottingham, NG7 2RD, UK ttxsem@nottingham.ac.uk Marie-Anne Midy School of EECS Oregon State University 1147 Kelley Engr. Ctr Corvallis, OR 97330, USA midym@onid.orst.edu Chandan Sarkar School of EECS Oregon State University 1147 Kelley Engr. Ctr Corvallis, OR 97330, USA sarkar@eecs.oregonstate.edu Abstract The aim of this research is to investigate the role of social networks in computer science education. The Internet shows great potential for enhancing collaboration between people and the role of social software has become increasingly rele- vant in recent years. This research focuses on analyzing the role that social networks play in students��� learning experi- ences. The construction of students��� social networks, the evolution of these networks, and their effects on the stu- dents��� learning experience in a university environment are examined. Categories and Subject Descriptors K.3.2 [Computer and Education]: Computer and Infor- mation Science Education - Computer science education General Terms Human Factors, Theory Keywords Social network, computer science education, student experi- ence, higher education, learning process 1. INTRODUCTION Identifying the right people to effectively resolve a prob- lem or collaborate with others is a challenging task. There are clear advantages to getting this right, as it may involve people with varying levels of expertise working together col- lectively to resolve problems. A vast array of systems exist which employ users��� stored profile data, identifying matches for collaboration. Social interaction within an online frame- work can help university students share experiences and col- laborate on relevant topics. As such, social networks can act as a pedagogical agent, for example, with problem-based learning. This paper is a literature review of social networks in educa- tion including both technical and social aspects of computer- supported collaborative learning. The aim of this review is to highlight the complexity of the field of social learning and to bring forward some central aspects that need more investigation. This paper is a snapshot of an ongoing larger study. Based on this literature review, we will later gather empirical data to further uncover how social networks are formed and what makes them work efficiently. As various possibilities for web-based education are inves- tigated, researchers and universities are trying to provide effective web-based courses to students within the univer- sity, and as a mode of delivery for distance learners. This paper focuses on pedagogy from a student perspective, concentrating on the computer science culture. Initially, the paper gives an overview of existing social software appli- cations falling under the ���Web 2.0��� category, and discusses the potential for employing these applications in education. Particular attention will then be given to the perception of social networks and their current influence on the computer science students��� learning experience. The paper also dis- cusses the gap between the fast developing social software and its use for education. Because the paper is an effort by 224

PhD students, educators can benefit from realizing the im- portance and influence of social networks on the students��� academic lives, and their learning experience in particular, from a student perspective. To understand the impact social networks have on the learn- ing experience, it is worth a bit of discussion on how so- cial networks are formed, how universities group students, and how students go about grouping themselves. Issues such as diversity and perceived value of social networks to students are also considered in this context. Examples of how the study of social networks can assist educators with their teaching - such as detecting plagiarism, forming groups for collaborative learning, enhancing distance learning, and building strong communities of experts - are given in differ- ent sections of the paper. Considerable resources have been dedicated to establishing effective methods for locating people suitable for working groups. In higher education, universities frequently group students together to improve student performance. Some success has been attained in the use of web-based courses using shared spaces and annotation of web-pages, and adap- tive desktops for accessing their evolving contents. Weblogs, wikis, logs and online documentation are also gaining popu- larity and pedagogic credence as part of the learning process, as is the evolution of associated collaborative communities. Section 2 introduces the concept of social networks, present- ing the ways in which networks can be formed, along with other types of group in which people can be aggregated. Section 3 describes current theories about how people learn. In section 4, the social aspects of collaborative learning are examined. Section 5 analyses the different social networks present in education, how they are formed, the influence of universities and diversity of this formation, their effect on the learning experience and communication within a social network. Section 6 gives an overview of computer-supported social network applications. Finally, Section 7 discusses the conclusions of this review. 2. SOCIAL NETWORKS The study of social networks has received significant inter- est from researchers in various domains such as psychology, philosophy, education, and lately computer science - par- ticularly in the field of artificial intelligence. This section defines what we mean by social networks, the way in which these networks form and evolve in our daily lives, and their relations to other types of group. 2.1 Definition of Social Network Social networks are a social structure of nodes that represent individuals (or organizations) and the relationships between them within a certain domain. Therefore, social networks are usually built based on the strength of relationships and trust between the members (nodes). Scrutiny of the ways in which these nodes are connected has resulted in the identifi- cation of varying types of ties between nodes. In [2] and [33], the authors discuss the notion of describing connections in terms of strong and weak ties, or formal and informal rela- tionships, respectively. In this context, a strong tie is one established directly between two people in the same network, whereas a weak tie is a relationship between two people con- nected through another person (two levels of separation). 2.2 Algorithms Forming connections is a natural human process. Current research outlines the algorithms that model the resulting networks. Examples of these algorithms are investigated in graph theory [38] and have highlighted the social values and evolution of trust that occurs among the members of the network. Constructing networks: The way in which people meet and form social networks in everyday life has caught the attention of many computer science researchers. The fact that we relate to and depend on our social network for such things as friendship, support, special interests and knowl- edge sharing has inspired algorithm developers to analyze these facets in a more abstract way. In [35] the authors de- scribe the Neighboring Matchmaker methodology thus: two individuals who do not know each other are introduced by a mediator who is a friend of both and who can facilitate the creating of a new relationship. A similar method of cre- ating or enlarging a network follows the Friend of a Friend concept, where the associations are inferred through mutual friends. However, with methods such as Friend of a Friend, trust and privacy issues become questionable due to the de- batable measurement and inference of trust. Since social networks can serve as a rich resource of new knowledge and as a filter for identifying the information most relevant to our specific needs, a second naturally occurring networking method is Word of Mouth [37]. Here individuals obtain re- views, share knowledge and expertise, find experience and ask for advice or assistance from the neighboring individuals in their social network. Searching networks: On searching for specific criteria within a social network, Zhang and Ackerman [101] stud- ied the social characteristics of various searching algorithms that can be useful in finding individual features such as ex- pertise, in order to understand the tradeoffs involved in the design of social network-based searching engines. The use of searching algorithms to navigate social networks can be highly beneficial in looking for a special individual and then identifying the people connected to her. Network dynamics: People have been forming themselves into groups without the gratuitous nature of the internet or social software. Online communities are not new. So what is new about the interaction of people within online social networks? According to [53], what may be different is un- derstanding the role social networks play in forming com- munities. Wellman views the difference between networks and groups: ���Although people view the world in terms of groups they function in networks. In networked societies, boundaries are permeable, interactions are with diverse oth- ers, connections switch between networks, and hierarchies can be flatter and recursive.��� [91]. Due to the transparent and loosely-knit nature of social networks, members move in and out of communities without formalism. Indeed, ac- cording to [91], ���Rather than fitting into the same group as those around them, each person has his/her own personal community.��� 225