information sharing and interaction in the online learning communities
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Information Sharing and Interaction in the Online Learning Communities
János Ollé
Eötvös Loránd University Faculty of Pedagogy and Psychology
Department of Education Information Society Teaching and Researching Group
June 5, 2014 ELTE PPK Takács Etel Room (KAZY 407)
#1 Educational background
educational environments• contact-based, offline
• network (internet) supported
• blended
• distance education
• virtual education
learning environments
• personal (PLE)
• social interactivity-based (web2)
• personal activity-based (MOOC)
• instructional (LMS, LCMS)
current trends
• growth of information sharing space
• permanent possibility of the interaction
• the efficiency depends of the environment
#2 Social Network Analysis
SNA theoretical background
online information sharing network
we calculate, we use, it's important for us:
• directed matrix
• whole network
• realized connection
• edge weight
• timeline of connections
• information type
• information quality
what's not important:
• personal (offline) friendship
• (other) social network relationship
• offline information sharing
• sharing to the group
#3 Analyzed groups
nickname content sem level type method N social network analyse
konnekt2012 information society
2012 spring MSc
offline lecture
+seminarconnectivism 59 facebook OK
tav2012 distance education
2012 spring MSc
offline lecture,
virtual 3Dhybrid environment 65 facebook,
3D SecondLife OK
bevikt2013 ICT, web2, online social
2013 autumn BSc offline
seminar offline interactivity 14 facebook OK
tav2013 distance education
2013 spring MSc offline
lectureoffline classroom,
“MOOC” 53 facebook few interaction
infotud2013 information society
2013 spring MSc offline
lectureoffline classroom,
“MOOC” 21 facebook OK
bevikt2012 ICT, web2, online social
2012 autumn BSc offline
seminar offline interactivity 44 facebook few interaction
ossz2013all of above+research
methodology
2013 autumn
BSc MSc PhD
lecture, seminar “one big group” 117 google plus few interaction
sportinf2012 ICT, web2, online social
2012 autumn BSc offline
seminar offline interactivity 52 facebook few interaction
#4 Descriptive graphs
Inf2013 group (MSc, offline classroom, "MOOC" N=21, E=39)
Tav2012 group (MSc, hybrid environment, N=42, E=147)
konnekt2012 group 108 days, 6743 action in the group (mean = 62,44)
konnekt2012 group (MSc, connectivism, N=43, E=429, T=6743)
konnekt2012 group
quality interactions N=32, E= 215
social media noise N=40, E= 318
#5 curve estimation, function analysis
number of edge (realized information connections)
#6 learners, groups -
differences
frequent statistic measures:• degree centrality
• shortest path
• betweenness centrality
• closeness centrality
• diameter (longest shortest path)
• eigenvector centrality!
• local clustering coefficient
• graph density
(Abraham-Hassanien-Snasel, ed. 2010)
"Eigenvector centrality is a measure of the importance of a node in a network."
"A player’s degree of “popularity” within the network, i.e., they represent centers of large
cliques in the graph. A node with more connections to higher scoring nodes is considered as being more important."
content sharing
res-ponse
inter-action
relevant content
mixed content
irrelevant content
other content
eigen-vector r!p
0,1650,079
0,0700,462
0,036!0,707
-0,137!0,146
0,0980,298
0,0430,648
0,2600,005
• the "importance in the network" does not correlate with relevant content sharing activity
• It correlates with other content sharing activity (for example: social noise, pretence activity)
• is social media really useful in educational communication?!
• hopefully: there are differences between different methodology used groups
eigenvector - content sharing activity
sum inter-
actionsposts com-
mentcontent sharing
res-ponse
inter-action
relevant content
mixed content
irrelevant content
other content
eigen-vector
r!p
0,0390,677
0,1670,075
0,0640,502
0,1650,079
0,0700,462
0,036!0,707
-0,137!0,146
0,0980,298
0,0430,648
0,260!0,005
konnekt2012 0,034!0,815
0,010!0,946
0,023!0,875
0,004!0,976
0,028!0,974
0,005!0,974
-0,190!0,186
-0,043!0,767
0,070!0,631
0,126!0,382
tav2012 -0,040!0,801
-0,106!0,502
-0,066!0,676
-0,114!0,472
-0,067!0,672
-0,036!0,819
-0,070!0,662
-0,120!0,451
-0,026!0,872
-0,109!0,493
infotud2013 0,664!0,001
0,592!0,005
0,669!0,001
0,593!0,005
0,652!0,001
0,564!0,008
0,392!0,079
0,577!0,006
0,501!0,021
0,592!0,005
• the "importance in the network" does not correlate with relevant content sharing activity - any groups
• the online activity are useful only in the open, regular course group ("little MOOC")
• there are the social media noise significance as well
eigenvector - content sharing activity
conclusions of correlation matrix• small groups, small networks - small conclusions :)
• #1 online communities (social networks) can be very spectacular but are not useful for educational process
• they can help the communication, but there are a big irrelevant social noise
• there are differences between groups
• #2 connectivism in small groups can develop "social market", but connected knowledge is unsure
• #3 hybrid environment (offline, online, 3D) obviate the bridge role in the information network
• #4 in an open online course the activity can be better quality than other groups
Thank you, for the attention and for your patience!
János Ollé
Eötvös Loránd University Faculty of Pedagogy and Psychology
Department of Education Information Society Teaching and Researching Group
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