Public lecture given at Tallinn University

1. From L e a r n i n g N e t wo r k s
to Digital Ecosystems
03.09.2010 Tallinn University, Estonia
Dr. Hendrik Drachsler
Centre for Learning Sciences and Technology
@ Open University of the Netherlands
1

2. Centre for Learning Sciences
and Technologies (CELSTEC)
2

3. Centre for Learning Sciences
and Technologies (CELSTEC)
2

4. Centre for Learning Sciences
and Technologies (CELSTEC)
2

5. Centre for Learning Sciences
and Technologies (CELSTEC)
• 100 employees (R. Koper)
• 3 R&D program’s
• Learning and Cognition (P. Kirschner)
• Learning Media (M. Specht, & W. Westera)
• Learning Networks (P. Sloep)
• Master Active Learning (E. Boshuisen)
2

6. Whoami
• Assistant Professor at the
Learning Networks Program
• Research topics:
Learning Networks,
Technology Enhanced
Learning, Recommender
Systems, Personalisation,
Mash-Ups and widget
technology, e-health
3

7. Learning Network Projects
4

8. Learning Network Projects
SC4L
4

9. Overview
• Introduction to Learning Networks
• Introduction to Digital Ecosystems
• Differences between Learning Networks
and Digital Ecosystems
• A Future Research Agenda
5

10. Overview
• Introduction to Learning Networks
• Introduction to Digital Ecosystems
• Differences between Learning Networks
and Digital Ecosystems
• A Future Research Agenda
5

11. Overview
But before we start...
• Introduction to Learning Networks
• Introduction to Digital Ecosystems
• Differences between Learning Networks
and Digital Ecosystems
• A Future Research Agenda
5

12. Twitter
Ecosystem nt
Are there any
Twitter users?
6

13. Twitter
Ecosystem nt
Please use the
Are there any
following hashtag for
Twitter users?
the backchannel.
You can post your
remarks and questions
during the presentation
and we get back to
them later on.
6

14. Twitter
Ecosystem nt
Please use the
following hashtag for
the backchannel.
You can post your
remarks and questions
during the presentation
and we get back to
them later on.
6

15. Twitter
Ecosystem nt
Hashtag: #LNDE
Please use the
following hashtag for
the backchannel.
You can post your
remarks and questions
during the presentation
and we get back to
them later on.
6

16. Twitter
Ecosystem nt
Hashtag: #LNDE
Please use the
If you are not a twitter
users surf hashtag for
following to:
the backchannel.
http://backnoise.com/?LNDE
You can post your
You just have questions
remarks and to enter
during the presentation
a user name and can
and we get back to
contribute and discuss
in the later on.
them backchannel.
6

17. Learning Networks
7

18. We live in a decade of
industrial change
Change picture
8

19. The challenge
“The biggest challenge businesses face
today is unlearning what was successful in
the industrial age and learning how to
prosper in the network era.”
Jay Cross (2006)
9

20. Graphic by Alex Guerten, 2008
10

21. G
L O C A L I S AT I O N
O
B
A
L
I
S
A
T Graphic by Alex Guerten, 2008
I
O
N 10

22. G L O C A L I S AT I O N
Graphic by Alex Guerten, 2008
10

23. G L O C A L I S AT I O N
P
R
O
D
U
C
Graphic by Alex Guerten, 2008
E
CONSUMERS
S
10

24. G L O C A L I S AT I O N
Graphic by Alex Guerten, 2008
PROSUMERS
10

25. The Glocalisation / Prosumers world
by Zohar Manor-Abel http://flickr.com/photos/zoharma/97214235/sizes/l/
11

26. Learning Networks
• Explicitly address informal
learning
• Users can publish, share, rate,
tag and adjust knowledge
resources in Learning
Networks
• Open Corpus that emerges
form the bottom upwards (Koper & Sloep, 2002)
12

27. Learning Networks
• Explicitly address informal
learning
• Users can publish, share, rate,
tag and adjust knowledge
resources in Learning
Networks
• Open Corpus that emerges
form the bottom upwards (Koper & Sloep, 2002)
12

28. Use Cases for
Learning Networks
13

29. Julie, a medical doctor from Germany
Julie is a medical doctor at the Gannon University who wants
to become specialized as cardiologist.
She participates in the International Cardiology Qualification
Network and shares her experiences on the medical cases with
colleagues from hospitals world wide. She also gets informed
about new cases available in the network.
14

30. Julie, a medical doctor from Germany
Julie is a medical doctor at the Gannon University who wants
to become specialized as cardiologist.
She participates in the International Cardiology Qualification
Network and shares her experiences on the medical cases with
colleagues from hospitals world wide. She also gets informed
about new cases available in the network.
14

31. Limbourgs Public Library in the Netherlands
Limbourgs public library in
the Netherlands needs to
rethink its role in society
and retrain its personnel in
the process.
Therefore they want to
create an Innovation
Network with their
employees and their target
groups to innovate and
train their personnel
towards the network era.
15

32. Limbourgs Public Library in the Netherlands
Limbourgs public library in
the Netherlands needs to
rethink its role in society
and retrain its personnel in
the process.
Therefore they want to
create an Innovation
Network with their
employees and their target
groups to innovate and
train their personnel
towards the network era.
15

33. Technologies for
Learning Networks
16

34. Technologies for
Learning Networks
But before we Go on...
Let’s have a look at our
Twitter experiment
16

35. R&D for Learning Networks
• Mashups, Personal Environments
• Indicators on Learning Interactions
• Reflection Support on Social Learning
• Personalisation of Information
• Distributed Innovation
• Prior Knowledge Assessment
• Recommender Systems
• Network Analysis
17

36. Personal Environments
18

37. Personal Environments
18

38. 19

39. Personal Environments
19

40. Personal Environments
More
Blog Reader Information
Providers
Social
Bookmarking
Various
Communities
19

41. Personal Environments
Developing Widgets
20

42. Personal Environments
Developing Widgets
20

43. Personal Environments
Developing Widgets
20

44. Personal Environments
Developing Widgets
Scott Wilson
20

45. Personal Environments
Developing Widgets
20

46. Personal Environments
Interwidget communication
Developing Widgets
Julie
20

47. Emergence
Johnson, S. (2001)
21

48. Emergence
Johnson, S. (2001)
21

49. Emergence
Johnson, S. (2001)
21

50. Emergence
Johnson, S. (2001)
21

51. Emergence
Johnson, S. (2001)
21

52. Emergence
Johnson, S. (2001)
21

53. Emergence
“We are leaving the age of information and
entering the age of recommendation”
Chris Anderson (2004)
Johnson, S. (2001)
21

54. Recommender Systems
22

55. Recommender Systems
22

56. Recommender Systems
People who bought the same
product also bought product
B or C …
22

57. The Long Tail
Graphic Wilkins, D., (2009); Long23 concept Anderson, C. (2004)
tail

58. The Long Tail of Learning
Graphic Wilkins, D., (2009); Long23 concept Anderson, C. (2004)
tail

59. Emerging paths
24
© peterme.com, flickr 2009

60. Emerging paths
Main
Road
24
© peterme.com, flickr 2009

61. Emerging paths
Personalised
paths
Main
Road
24
© peterme.com, flickr 2009

62. Recommender Systems for
Learning Paths
25

63. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

64. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
2006
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

65. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

66. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
2007 Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

67. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

68. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
2008 Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

69. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

70. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
2009
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

71. Recommender System Research
Prototype:
Recommender
Practical
System for Learning
Networks
Study 3: Learning Networks
Simulation
Study 2: Psychology Experiment
Study 1: Theoretical Background
Theoretical
2006 2007 2008 2009
26

72. Try it your self ...
27

73. Try it your self ...
Sign up at
remashed.ou.nl
27

74. Try it your self ...
Sign up at
remashed.ou.nl
Enter your favorite
Web 2.0 potatoes.
27

75. Try it your self ...
Sign up at
remashed.ou.nl
Enter your favorite
Web 2.0 potatoes.
Join the
Community.
27

76. Try it your self ...
Sign up at Let ReMashed
remashed.ou.nl start mashing.
Enter your favorite
Web 2.0 potatoes.
Join the
Community.
27

77. Try it your self ...
Sign up at Let ReMashed
remashed.ou.nl start mashing.
Enter your favorite Taste your
Web 2.0 potatoes. personal
flavor of
Web 2.0.
Join the
Community.
27

78. Networks are dead! Long live
the Digital Ecosystems!
28

79. Learning Networks
“A Learning Network is an online, social network
designed to support and facilitate lifelong
learning (a learning ‘ecosystem’)”
(Peter Sloep, 2009)
29

80. Learning Networks
Learning Network = Digital
Ecosystem ?
29

81. Digital Ecosystems
30

82. Digital Ecosystems
But before we Go on...
Let’s have a look at our
Twitter experiment
30

83. What is an Ecosystem ?
“An ecosystem is
generally an area within
the natural environment
in which physical factors
of the environment, such
as rocks and soil, function
together along with
interdependent
organisms, such as plants
and animals, within the
same habitat.”
http://en.wikipedia.org/wiki/Ecosystem
31

84. What is a Digital
Ecosystem ?
“A Digital Ecosystem is
any distributed adaptive
open socio-technical
system, with properties
of self-organisation,
scalability and
sustainability, inspired by
natural ecosystems.”
http://en.wikipedia.org/wiki/Digital_ecosystem
32

85. What is a Digital
Ecosystem ?
“Digital Ecosystems were
made possible by the
emergence of three
networks: ICT networks,
social networks, and
knowledge networks.
Nachira, F., Dini, P., Nicolai, A. (2007)
33

86. What is a Digital
Ecosystem ?
Nachira, F., Dini, P., Nicolai, A. (2007)
34

87. What is a Digital
Ecosystem ?
Learning Ecosystems
Nachira, F., Dini, P., Nicolai, A. (2007)
34

88. Another Definition
“... often a group of applications complementing a specific
product or platform is considered to form a digital
ecosystem; the ICT companies form a “digital ecosystem
community.”
“But, in order to make sense in large scale concepts such as
the Information Society they [the digital ecosystems] need to
be useful to many facets of the economic life of the individual
economic player. “
Nachira, F., Dini, P., Nicolai, A. (2007)
35

89. Another Definition
Company Ecosystems
“... often a group of applications complementing a specific
product or platform is considered to form a digital
ecosystem; the ICT companies form a “digital ecosystem
community.”
Digital Ecosystems
“But, in order to make sense in large scale concepts such as
the Information Society they [the digital ecosystems] need to
be useful to many facets of the economic life of the individual
economic player. “
Nachira, F., Dini, P., Nicolai, A. (2007)
35

90. Examples of Digital
Ecosystems
36

91. iPOD Ecosystem
37

92. iPOD Ecosystem
37

93. Facebook Ecosystem
38

94. Facebook Ecosystem
38

95. Google Ecosystem
39

96. Google Ecosystem
39

97. Iyer, B. & Davenport, T. (2008)
40

98. life symbiotic...
41

99. life symbiotic...
41

100. Ergo
Peter Sloep is partly right ...
42

101. A Learning Network can become
a Digital Ecosystem when...
...it applies distributed tools, communities, or
services from different providers whereby
these sources interrelated in very specific
ways by open API’s and standards in order to
serve a greater overall purpose for its
community.
43

102. Extend tools
Biosphere Organisations
Create
Create Consume
Innovate Digital Ecosystem Extend
Mashup
Consume community Community
New services Innovators Content
Providers
f
Position Glocalisation ProSumers
Use
Target offers Contribute / Enrich
Alliance Consume
Advertise Search
Target Groups Validate
Emerge data

103. Future Research
Agenda
45

104. Future Research
Agenda
But before we Go on...
Let’s have a look at our
Twitter experiment
45

105. Beyond
46

106. Beyond
46

107. Beyond
46

108. Beyond
46

109. Beyond
O P E N D ATA
48
47

110. Beyondthe
Beyond
48
47

111. Beyondthe
Beyond
O P E N D ATA
48
47

112. Beyondthe
Beyond
O P E N I N N O V AT I O N
48
47

113. Beyondthe
Beyond
MASHUP TECHNOLOGY
48
47

114. Beyondthe
Beyond
RECOMMENDER SYSTEMS
48
47

115. Beyondthe
Beyond
P ROT E C T I O N R I G H T S
48
47

116. Free
the data
by Tom Raftery http://www.flickr.com/photos/traftery/4773457853/sizes/l
48

117. Why ?
by Tom Raftery http://www.flickr.com/photos/traftery/4773457853/sizes/l
48

118. Because we
will get new
insights
by Tom Raftery http://www.flickr.com/photos/traftery/4773457853/sizes/l
48

119. 49

120. 49

121. 49

122. 49

123. 49

124. 49

125. Open Innovation
50

126. Open Innovation
R&D -> C&D
50

127. Open Innovation
R&D -> C&D
50

128. Open Innovation
R&D -> C&D
50

129. Mashups and Widgets
51

130. Mashups and Widgets
51

131. Recommender Systems
52

132. Recommender Systems
52

133. Recommender Systems
52

134. Protection Rights
53

135. Protection Rights
53

136. Protection Rights
OVERSHARING
53

137. Application Areas
by Ivan Plata, flickr
48
54

138. Technology-
Enhanced
Application Areas
Learning
by Ivan Plata, flickr
48
54

139. Technology-
Enhanced
Application Areas Science 2.0
Learning
by Ivan Plata, flickr
48
54

140. Technology-
Enhanced
Application Areas Science 2.0
Learning
by Ivan Plata, flickr
48
54 e-health

141. Technology-
Enhanced
Application Areas Science 2.0
Learning
e-democracy /
e-participation by Ivan Plata, flickr
48
54 e-health

142. Grow new niche services
55

143. Grow new niche services
Consequently use services from the biosphere and
intertwine student projects with these services
• Google ecosystem (forms, database, Google API)
• Yahoo ecosystem (Yahoo pipes, and web services)
• Reuters Open Calais and Semantic Enrichment
• Open data from twitter and other ecosystems
• Open API’s, Protocols, Standards -> Interoperability
• Empower the users to connect, enrich and combine
55

144. Many Thanks for your
interests
56

145. Many Thanks for your
interests
Your questions are welcome
and what is happening in
the #LNDE backchannel?
56

146. References
Anderson, C. 2004. “The long tail.” Wired Magazine 12 (10). Available: http://www.wired.com/wired/archive/12.10/tail.html
Cross, J., (2006) Informal learning: Rediscovering the natural pathways that inspire innovation and performance. Pfeifer
Drachsler, H., Hummel, H., & Koper, R. (2008a). Personal recommender systems for learners in lifelong learning: requirements,
techniques and model. International Journal of Learning Technology 3(4), 404 - 423.
Drachsler, H., Hummel, H., & Koper, R. (2008b). Using Simulations to Evaluate the Effects of Recommender Systems for Learners in
Informal Learning Networks. Paper presented at the EC-TEL conference, 2nd Workshop on Social Information Retrieval in
Technology Enhanced Learning (SIRTEL08). September, 16-19, 2008, Maastricht, The Netherlands: CEUR Workshop
Proceedings
Drachsler, H., Hummel, H., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for
Formal and Informal Learning. Journal of Digital Information.
Drachsler, H., Hummel, H., van den Berg, B., Eshuis, J., Berlanga, A., Nadolski, R., Waterink, W., Boers, N., & Koper, R. (accepted).
Effects of the ISIS Recommender System for navigation support in self-organised Learning Networks. Journal of Educational
Technology and Society.
Drachsler, H., Dries, E., Arts, T., Rutledge, L.,Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (submitted). ReMashed –
Recommendations for Mash-Up Personal Learning Environments. 4th European Conference on Technology Enhanced
Learning, EC-TEL 2009. Learning in the Synergy of Multiple Disciplines, September, 29, 2009, Nice, Italy
Iyer, B., & Davenport, T. H. (2008). Reverse engineering Google's innovation machine. Harvard Business Review.
Kalz, M.,Van Bruggen, J., Giesbers, B., & Koper, R. (2007). Prior Learning Assessment with Latent Semantic Analysis. In F. Wild,
M. Kalz, J.Van Bruggen & R. Koper (Eds.). Proceedings of the First European Workshop on Latent Semantic Analysis in
Technology Enhanced Learning (pp. 24-25). Heerlen, The Netherlands: Open University of the Netherlands.
Gahn, C., Specht, M., & Koper, R. (2007). Smart Indicators on Learning Interactions. In E. Duval, R. Klamma, & M. Wolpers
(Eds), Creating New Learning Experiences on a Global Scale: LNCS 4753. Second European Conference on Technology
Enhanced Learning, EC-TEL 2007 (pp. 56-70). Berlin, Heidelberg: Springer.
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147. This silde is available at:
http://www.slideshare.com/Drachsler
Email: hendrik.drachsler@ou.nl
Skype: celstec-hendrik.drachsler
Blogging at: http://www.drachsler.de
Twittering at: http://twitter.com/HDrachsler
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