Visualizing Informal Learning Behavior from Conference Participants Twitter Data presented by Heli Aramo-Immonen at TEEM 2014 conference

1. Visualizing Informal Learning Behavior from Conference Participants Twitter Data
Heli Aramo-Immonen1, Jari Jussila2, Jukka Huhtamäki3,
Tampere University of Technology,
1 Industrial Management in Pori Unit
2 Department of Information Management and Logistics
3 Intelligent Information Systems Laboratory (IISLab)
This paper was introduced in
TEEM2014 International ACM-conference in Salamanca, Spain

2. Overview of the study
•The aim of this research was to explore the informal learning behavior in project context especially by analyzing and visualizing informal learning behavior from conference participants Twitter data
•Case study
–Project of organizing the CMAD2014 (Community Manager Appreciation Day) conference held during 27 January 2014 in Hämeenlinna, Finland
–Tweets from the registered participants two weeks before the conference
–225 people participated in CMAD2014 during the day
Aramo-Immonen et al. (2014)
2
cmad.fi

3. Community of Practice
•A community of practice is a collection of people who engage on an ongoing basis in some common endeavor. (Eckert, 2006)
•Organizations are made up of communities of practice
•If organizational learning is to take place, then Informal learning in communities needs to be stimulated. (Ropes, 2010)
2.10.2014
Aramo-Immonen et al. (2014)
3

4. Theoretical discussion
•Concepts of informal and formal learning,
•Activity theory based informal expansive learning,
•Internal and external memory aids,
•Motivation to learn
•Context of communities of practice as informal learning environments
2.10.2014
Aramo-Immonen et al. (2014)
4

5. Informal Learning
•Icinformal learners usually set their own learning objectives.
•They learn when they feel a need to know.
•The proof of their learning is their ability to do something they could not do before.
•Informal learning is often a pastiche of small chunks of observing how others do things, asking questions, trial and error, sharing stories with others, and casual conversation.
2.10.2014
Aramo-Immonen et al. (2014)
5
According to García-Peñalvo, Colomo-Palacios and Lytras (2012),

6. Activity theory
•According to the socio-cultural historical activity theory, there has to be a triggering action, such as a conflictual questioning of the existing standard practice in the organization in order to generate expansive learning
•Expansive learning produces culturally new patterns of activity.
Engeström, Y, (2000)
2.10.2014
Aramo-Immonen et al. (2014)
6

7. Expansive Learning
•In Twitter communities is the freedom to be critical concerning contemporary ways of doing things.
•In other words, individuals do tend to criticize and express their feelings more easily in social media than in face-to-face contact.
•This could be trigger for a change in organization.
2.10.2014
Aramo-Immonen et al. (2014)
7

8. Motivation to Learn
•An individual moves through a number of stages in the process of becoming learning- oriented (Bucler, 1996; Koskinen & Aramo-Immonen 2008)
1.Ignorance
2.Awareness
3.Understanding
4.Commitment
5.Enactment
6.Reflection
2.10.2014
Aramo-Immonen et al. (2014)
8

9. Assessment of how does learning motivation stages differ in online and face-to-face informal learning environments. Based on our observation during this study. (online/face to face is marked in the table X=exists and - =does not exist)
Motivation stages
Before conference
During conference
After conference
Ignorance
x / -
- / -
x / -
Awareness
x / -
x / x
x / x
Understanding
- / -
x / x
- / x
Commitment
x / x
x / x
- / x
Enactment
- / -
- / -
- / x
Reflection
- / -
- / -
x / x
2.10.2014
Aramo-Immonen et al. (2014)
9

10. Top 5 hashtags that CMAD2014 participants used during two weeks before the conference day. Interactive version is available: http://bit.ly/chashtags
2.10.2014
Aramo-Immonen et al. (2014)
10

11. Hashtag metrics of people tweeting during two weeks before the CMAD2014 conference day. Interactive visualization available: http://bit.ly/hcmatrix
2.10.2014
Aramo-Immonen et al. (2014)
11

12. Hashtag metrics
•In the matrix the discussions are clustered based on the choice of sorting parameter: volume, partition and total number of co- occuring tweets.
•From the co-occurrence of hashtags matrix, and sorting by partitions, we identified 7 larger different partitions, representing 7 different subgroups of discussions inside the community of community managers.
2.10.2014
Aramo-Immonen et al. (2014)
12

13. 2.10.2014
Aramo-Immonen et al. (2014)
13
Figure 3. Interactive visualization of people tweeting and their hashtags during two weeks before the conference day. Interactive visualizations is available: http://bit.ly/cnetwork

14. Interactive Visualization
•The figure 3 can be used by people to find people with similar interest, to network with and share knowledge even before the conference.
•For the organizers the figure 3 gives clues which people should be e.g. seated at same tables at lunch to generate fruitful further discussions
2.10.2014
Aramo-Immonen et al. (2014)
14

15. Aramo-Immonen et al. (2014)
15
•Proposition 1: Discussions in social media network can perform as virtual informal collaborative learning environments.
•Proposition 2: Physical informal learning environments can be build based on information gained from interactive visualization of people’s behaviour in social network before and during the event.
•Proposition 3: Before event virtual discussions can increase the motivation to learn informally during the conference.
Propositions

16. CONTACT
Heli Aramo-Immonen, heli.aramo-immonen@tut.fi
Twitter: @AramoHeli, LinkedIn, Facebook
Blogi: http://heliaramoimmonen.wordpress.com/
Jari J. Jussila, jari.j.jussila@tut.fi
Twitter: @jjussila
Jukka Huhtamäki jukka.huhtamaki@tut.fi
Twitter: @jnkka
2.10.2014
16

17. 2.10.2014
17
ACKNOWLEDGMENTS
This research is sponsored by Tekes – the Finnish Funding Agency for Technology and Innovation (Projects “Soila”; Innovative Value Creation and Business Models of Social Media in B2B Networks, and “Reino”; Relational Capital for Innovative Growth Companies).