TeLLNet Learning Analytics in a Teachers’ Social Network Manh Cuong Pham, Yiwei Cao, Zinayida Petrushyna, and Ralf Klamma RWTH Aachen University Advanced Community Information Systems (ACIS) email@example.comLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
TeLLNet Advanced Community Information Systems (ACIS) Responsive Web Engineering Community Web Analytics Open Visualization Community and Information Simulation Systems Community Community Support AnalyticsLehrstuhl Informatik 5 Requirements(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-2 Engineering
TeLLNet Agenda Introduction to social capital Social network analysis for social capital Case study: social capital in eTwinning network Conclusions and future workLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-3
TeLLNet Introduction Human capital vs. social capital [Burt, 1992] – Human capital: the personal ability to perform tasks (e.g. talent, education, etc.) – Social capital: the social environment surrounding individuals Social capital as a property of – Individuals: positions in social network that are more efficient in performing tasks (i.e. local structure) – Groups: structure of members’ network that makes the group functions more efficient (i.e. structure of a sub-network) In our research, we study social capital in teachers’ network – By SNA metrics and a development model – The performance of teachers and projects: recognized by Quality Labels – Network structure of projects and position of teachers: identified via networks created by several communication mechanisms (e.g. message, projectLehrstuhl Informatik 5(Information Systems) collaboration, blog) Prof. Dr. M. Jarke I5-PCPK-0412-4
TeLLNet Social Capital: Structural Hole vs. Closure Structural holes [Burt, 1992] - Nodes are positioned at the interface between groups (gatekeepers, e.g. node B) - Informational advantages: access to information from different parts of networks - Form novel ideas by combining information from different groups - Control the communication between groups Closure - Nodes are embedded in tightly-knit groups (e.g. node A) - More trust and security within coherent communities Social capital [Coleman, 1990] - Individuals and groups deriving benefits from social relationshipsLehrstuhl Informatik 5(Information Systems) - Network structural property: either structural hole or closure Prof. Dr. M. Jarke I5-PCPK-0412-5
TeLLNet Identification of Individual Social Capital Given the network G=(V,E), where V is the set of nodes and E is the set of edges Structural holes: nodes with high betweenness u (i, j ) B(u ) u i j (i, j ) where: u (i, j ): number of shortest paths between nodes i and j that pass through node u (i, j ): total number of shortest paths between nodes i and j Closures: nodes with high local clustering coefficient v, w N(u) : (v, w) E C(u) N(u) N (u ) 1 / 2Lehrstuhl Informatik 5 where: N (u ) is the set of neighbors of node u(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-6
TeLLNet Identification of Group Social Capital A community development model [Pham et al., 2011]Lehrstuhl Informatik 5 In which stage is the members’ network of a given group?(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-7 How does it relate to the performance of the group?
TeLLNet Qualify the Stage of Group Member Network Density: fraction of actual edges in the network v, w V : (v, w) E , n is the number of nodes D n 2 Global clustering coefficient 3 number of triangles D number of connected triples Maximum betweenness: highest betweenness of nodes Largest connected component: fraction of nodes in largest connected component For large member networksLehrstuhl Informatik 5 - Diameter: the longest shortest path between any pair of nodes(Information Systems) Prof. Dr. M. Jarke - Average shortest path length I5-PCPK-0412-8
TeLLNet Case Study: eTwinning Community Data #data entries Description Project 23641 Schools from at least two schools from at least two different European countries create a project and use ICT to carry out their work. Contact 769578 Teachers are able to explore other teachers profiles and add them into their own contact list. It is suggested to use forum and other media to contact the other teachers before taking them as a contact. Project diary 20963 Blog for project reports Project diary post 49604 Each blog entry in project diary Project diary 7184 Comments added to blog entries in project diary comment My journal 38496 Message posted on teachers wall which is part of teachers profile message Teacher 146105 Registered teachers working in European schools and, namely "eTwinner" Quality label 8042 Awarded first to projects. Then the project-involved schools and teachers are awarded accordingly. They are assigned by each country or on the European level: National Quality Label and European Quality Label Prize 1384 eTwinning Prizes are awarded to schools. They are of European level and are called European eTwinning Prizes Institution 91077 Various European schools: pre-school, primary, secondary and upper schoolsLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke Statistics on eTwinning data (as of 11.11.2011) I5-PCPK-0412-9
TeLLNet eTwinning Network Network #nodes #edges Description Project 37907 804856 Nodes are teachers (eTwinners) and there is a connection (edge) between two (26%) (0.11%) teachers if they collaborated in at least one project. Edges in the network are undirected and weighted by the number of projects in which the two teachers collaborate. Contact 109321 573602 Nodes are teachers and there is an edge between two teachers if at least one (75%) (0.01%) teacher is in the contact list of the other. Edges are undirected and unweighted. Project diary 3264 3436 Nodes are teachers and there is an edge between two teachers if one teacher has (2.2%) (0.06%) commented on at least one blog post created by the other. Edges are directed and weighted by the number of comments. My journal 23919 30048 Nodes are teachers and there is an edge between two teachers if one teacher has (16%) (0.01%) posted or commented on the wall of the other. Edges are directed and weighted by the number of messages. Teacher networks statistics (as of 11.11.2011) Data is processed, transformed and loaded into Oracle data warehouse Networks are aged for time series analysis Network parameters are computed using Oracle store proceduresLehrstuhl Informatik 5(Information Systems) Projects are considered as groups to study group social capital Prof. Dr. M. Jarke I5-PCPK-0412-10
TeLLNet Properties of Teacher Networks: The Power Law Degree Distribution Project network degree distribution Contact network degree distribution 4 6 Raw data Raw data 1.455 1.933 2 y=28.209x 4 y=327.630x 2 Cumulative Frequency Cumulative Frequency 0 0 2 2 4 4 6 6 8 8 10 10 0 2 4 6 8 0 2 4 6 8 10 Degree Degree Project diary network degree distribution My journal network degree distribution 6 6 Raw data Raw data 1.625 1.750 4 y=14.904x 4 y=38.875x Cumulative Frequency Cumulative Frequency 2 2 0 0 2 2 4 4 6 6 8 8 0 1 2 3 4 5 6 0 1 2 3 4 5 6 7 Degree DegreeLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke Degree distribution of eTwinning networks follow the power law with the formula y ax I5-PCPK-0412-11
TeLLNet Social Capital of Teachers (a) Quality labels and number of projects/posts/contacts/wall posts (b) Quality labels and degree 1 1 Project diary Project diary 0.9 0.9 Contact Contact 0.8 Project 0.8 Project My journal My journal 0.7 0.7 0.6 0.6 Frequency Degree 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Number of quality labels Number of quality labels (c) Quality labels and betweenness (d) Quality labels and clustering 1 1 Project diary Project diary 0.9 Contact 0.9 Contact Project Project 0.8 0.8 My journal My journal 0.7 0.7 Betweenness 0.6 0.6 Clustering 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70Lehrstuhl Informatik 5 Number of quality labels Number of quality labels(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-12 Structural hole as a form of social capital in eTwinning networks
TeLLNet Projects Achievement and Non-structural Properties Quality label of projects and their properties Quality label of projects and their properties 1 0.9 Country Teacher 0.9 Language 0.8 Institution Fraction of received quality label projects Fraction of received quality label projects Subject 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0 0 5 10 15 20 25 30 35 40 0 10 20 30 40 50 60 70 80 Number of countries involved, languages used and subjects Number of teachers and institution involved Number of countries and languages used somehow correlate to the quality Number of teachers and institutions: effect on small projects (less than 30 members)Lehrstuhl Informatik 5(Information Systems) Subject has no effect Prof. Dr. M. Jarke I5-PCPK-0412-13
TeLLNet Projects Achievement and Structural Properties Quality label of projects and their members network parameters 0.5 Density Clustering coefficient Maximum betweenness 0.45 Largest component Fraction of received quality label projects 0.4 0.35 0.3 0.25 0.2 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Network parameters Project member networks: created using the previous project collaboration and wall messaging, reflect the early communication of project members High quality projects prefer the Bonding stage: consists of seperated densely connected groupsLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke Form of social capital: structural hole I5-PCPK-0412-14
TeLLNet Conclusions and Future Work Social capital in eTwinning Network – Both teachers and projects follow structural hole – The informational diversity is the key success factor Applications: recommendation tools – Help teachers find projects, contacts, etc. – Help project organizers find, select and invite project partners Future works – Tracking the development pattern of teacher networks – Tracking the development pattern of teachers for competence management – Developing tools – Recommendation tools – Dynamic visualization of local and global teacher networks as well as network parametersLehrstuhl Informatik 5(Information Systems) Prof. Dr. M. Jarke I5-PCPK-0412-15