This document outlines the author's previous experience and current research interests related to social semantic infrastructures, learning analytics, and workplace learning. It then discusses the envisioned research work for the CEITER project, including developing a learning analytics data infrastructure for Estonia that incorporates stakeholders, integrates datasets from various sources, and scales nationally while ensuring privacy and promoting educational innovation. The infrastructure would be evaluated through design-based research and promote the use of learning analytics at institutional and policy levels.

1. A Learning Analytics infrastructure to promote
educational innovation in Estonia
Adolfo Ruiz-Calleja
31st, May 2016

2. Index
 Previous experience
 Current research work and interests
 Envision research work in CEITER project
 Conclusions
2

3. Index
 Previous experience
 Current research work and interests
 Envision research work in CEITER project
 Conclusions
3

4. Short CV
 2007: Telecommunications Engineer
 2007 – 2008: Master in Logic and Philosophy of
Science
 2008 – 2013: PhD student at Universidad de
Valladolid
 Sept 2013 – March 2014: Freelance
 April 2014 – now : Researcher at Tallinn University
4

5. 5
TECHNOLOGY
METHODOLOGY
& CONTEXT
LEARNING

6. 2008 – 2009: Euricles project
 Ontology-based catalogue of services and
infrastructure elements for a telecommunication
company
 Followed business standards: Shared Information/Data
Model (Brenner, Schaaf & Scherrer, 2009)
6
Ontology
engineering
Private
companies

7. Offer
tools
Marie
77
Google
Docs
MediaWiki
Hot
potatoes
Group
Scribbles
Learning situation
Educational
ICT tool pool
SELECT...tool...write
... collaboration...
peer review...
1.- Google Docs
2.- MediaWiki
Activities
People
Google
Docs
??
I need a tool for my
students to write a
document
collaboratively in a peer
review activity
Query: write,
collaboration,
peer review
Results
Educational ICT tool search system
(semantic or keyword-based)
Registry of
educational ICT tools
(semantic or not)
2010 – 2013: PhD work
Teacher
Educational
tool provides

8. 2010 – 2013: PhD work
8
 Consumption of Linked Open Data (Heath & Bizer,
2011)
 Ontology mapping (Choi, Son & Han, 2006)
 Understanding teachers needs
 Participatory design
Linked Data
Ontology
mapping
Participatory
design
Teachers
needs

9. 2010 – 2013: PhD work
9
Social-semantic
infrastructure
Web
technologies
Teacher
community

10. 2010 – 2013: PhD work
10
 Design and development of educational
applications
 Interface design
 Mixed methods evaluation (Tashakkori & Teddlie,
2010)
Interface design
Mixed methods
Multidisciplinary
research
Teacher
community

11. 2013 – 2014: Coin catalogue
11
Legacy data SMEs

12. Index
 Previous experience
 Current research work and interests
 Envision research work in CEITER project
 Conclusions
12

13. 2014 – 2016: Learning Layers
13
 Observe learning at the workplace (Eraut, 2004)
 Allow peer collaboration (Schmidt et al., 2009)
 Scaffolding for meaningful learning (Ley et al., 2010)
 Scale-up to regional clusters (Ley et al., 2013)
Scale up technology
Estonian context
European projects
Design-based research
Learners
Informal/Formal learning
Scale up learning
Three learning metaphors

14. 2014 – 2016: Social Semantic Server
14
Micro-service
Architecture
Actor-Artifact
Network
Design-based
research
Workplace
Learning
Analytics

15. 15
Ontology engineering
Linked Data
Web technologies
Social-semantic infrastructures
Legacy data
Scale up technology
Actor-Artifact Network
Micro-Service architecture
Participatory design
Design-based research
Estonian context
European projects
Working with companies
Multidisciplinary research
Focus on teachers
Focus on learners
Scale up learning
Formal/Informal learning
Three learning metaphors
Workplace Learning Analytics

16. Index
 Previous experience
 Current research work and interests
 Envision research work in CEITER project
 Conclusions
16

17. Social Semantic Server
 Collaboration with Graz University of Technology
 Workplace Learning Analytics
 Explore the potential of the SSS for the industry
 Collaboration with Karlsruhe University of Applied
Science
 Maturity indicators
17
"Pilots and Business Models for Training in Industry
using Social Semantic and Ubiquitous Technologies"

18. SHEILA
 Offer a general policy development framework for
LA to guide higher education institutions
 Conduct case studies that follow the framework
 Promotion of cross-institutional cooperation on
sharing experiences
18

19. SHEILA
Opportunity to work with highest-level
researchers
Understand LA initiatives at TLU
Get advice for initiatives that Estonia is a little
bit behind
 Ethics committee
Understand how to implement LA in the
institutional level
19

20. The CEITER project
CEITER project as a research infrastructure
Goals:
 Research contributions in the TEL field
 Increase chances of getting research funding for
TLU
 Practical impact on Estonian education
Contextualized in Estonia and TLU
 Small and technical-advanced country
 Big effort in Life-Long learning
 Easy access to policy makers 20

21. The CEITER project
21
ekool Stadium EHIS IASÕIS LMSs
CEITER INFRASTRUCTURE
Companies Universitie
s
Schools Ministry of education
Data Infrastructure
API
Data
model
Learning Analytics service DashboardPolicy support Best practices

22. A data infrastructure for CEITER
22
Data Infrastructure
API
Data
model
How to structure the data to promote the
dataset integration for Learning
Analytics?
Definition of an extensible information model
Data model based on Ontologies
Ontology
engineering
Participatory
design

23. A data infrastructure for CEITER
23
Data Infrastructure
API
Data
model
How to involve stakeholders into the
data management cycle?
Social technologies
Learning metaphors
Reuse/Propose vocabularies (RIHA project)
Three learning
metaphors
Social
technologies
Design-based
research
Formal/Informal
learning

24. A data infrastructure for CEITER
24
Data Infrastructure
API
Data
model
How to actually integrate datasets?
Software architecture to process data, including:
– Vocabulary mapping
– Identity resolution
– Anonymization
– Quality evaluation
Service Oriented
Architecture
Ontology
mapping
Legacy data

25. A data infrastructure for CEITER
25
Data Infrastructure
API
Data
model
How to offer the data?
Use of open standards, such as xAPI (Whitaker, 2012) or
Caliper (IMS Global, 2015)
Linked Data for Learning Analytics (d’Anquin & Jay, 2013
Legal and ethical issues (Slade & Prinsloo, 2013)
Linked Data
Ontology
engineering
Focus on
learners and
teachers
Workplace
Learning
Analytics

26. A data infrastructure for CEITER
26
Data Infrastructure
API
Data
model
How to scale it up to national level?
Pay-as-you-go principle (Madhavan et al., 2007)
(Micro-)Service architecture
Micro-Service
Architecture
Scale-up
technology
Scale-up
learning
Web
technologies

27. A data infrastructure for CEITER
27
Data Infrastructure
API
Data
model
How to promote the infrastructure to analyze
and enhance educational innovation in
Estonia?
Question-driven approach (Gasevic, Dawson and
Siemens, 2015)
Maybe new data sources are required (sensors?)
Design-based
research
Estonian
context
Multidisciplinary
research
Focus on
learners and
teachers

28. A data infrastructure for CEITER
28
Data Infrastructure
API
Data
model
How to guarantee privacy and security?
Potential collaboration with CYBERNETICA
(Cybernetica, 2016)
Working with
companies

29. A data infrastructure for CEITER
29
Data Infrastructure
API
Data
model
How to promote the use of the
infrastructure from the policy level?
SHEILA project

30. Relationships and other projects
European networks
 Workplace Learning Analytics working group
 COST Action Proposal “Learning Analytics in
Digital Learning Ecosystems: Frameworks,
Methods and Policies”
 LACE project
 Estonian chapter of SOLAR
Potential project calls
 Swafs-11-2017: Science education outside the
classroom. DL: August 2017
 MSCA-ITN-2017: Innovative Training Networks. DL:
January 2017
30
European
projects

31. Index
 Previous experience
 Current research work and interests
 Envision research work in CEITER project
 Conclusions
31

32. Conclusions
My role at CEITER as a continuation of my
current work at TLU
Social-semantic infrastructures
Workplace Learning Analytics
32
CEITER Learning Analytics infrastructure
Goes beyond a technical infrastructure
Research while having a practical impact
Integrate other projects into CEITER
SHEILA
Social-Semantic Server
New proposals

33. A Social-Semantic Infrastructure to support
Learning Analytics at Tallinn University
Adolfo Ruiz-Calleja
31st, May 2016

34. Baeza-Yates, R. and Ribeiro-Neto, B. (1999). “Modern information retrieval” (1st edition). Vol. 463. New
York: ACM press.
Buckingham, S. (2012) "Policy Brief: Learning Analytics". UNESCO Institute for Information Technologies
in Education. http://iite.unesco.org/publications/3214711/, last visit May 2016.
Brenner, M., Schaaf, T. and Scherer, A. (2009) "Towards an information model for ITIL and ISO/IEC 20000
processes". In: Proceedings of the IFIP/IEEE International Symposium on Integrated Network
Management, IEEE, pp. 113-116.
Choi, N., Song, I.Y. and Han, H. (2006) "A survey on ontology mapping." ACM Sigmod Record 35(3): 34-
41
Cybernetica (2016) “Sharemind. Analyze confidencial data without compromising security – Practical
secure computation for companies and goberments”. http://cyber.ee/uploads/2016/03/Sharemind-
2016-web.pdf last visit May 2016.
d'Aquin, M. and Jay, N. (2013). ”Interpreting data mining results with linked data for learning analytics:
motivation, case study and directions”. In: Proceedings of the Third International Conference on
Learning Analytics and Knowledge (pp. 155-164). ACM.
Duval, E. (2011): ”Attention please: Learning Analytics for visualization and recommendation”. In:
Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK), ACM,
pp 9-17.
Eraut, M. (2004) ”Informal learning in the workplace”. Studies in continuing education, 26(2):247-273.
Gašević, D., Dawson, S. and Siemens, G. (2015). ”Let’s not forget: Learning analytics are about learning”.
TechTrends, 59(1):64-71.
References
34

35. Gómez-Pérez, A., Fernández-López, M. and Corcho, O. (2006) ”Ontological Engineering: with examples
from the areas of Knowledge Management, e-Commerce and the Semantic Web” (1st edition).
Springer Science & Business Media.
Heath, T. and Bizer, C. (2011) ”Linked Data: Evolving the Web into a Global Data Space” (1st edition).
Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool.
IMS Global (2015). “Caliper Analytics™ Background”. https://www.imsglobal.org/activity/caliperram last
visit May 2015.
Ley, T., Kump, B. and Gerdenitsch, C. (2010). ”Scaffolding self-directed learning with personalized
learning goal recommendations”. In: User modeling, adaptation, and personalization (pp. 75-86).
Springer Berlin Heidelberg.
Ley, T., Cook, J., Dennerlein, S., Kravcik, M., Kunzmann, C., Pata, K., Purma, J., Sandars, J., Santos, P.,
Schmidt, A. and Al‐Smadi, M. (2014) "Scaling informal learning at the workplace: A model and four
designs from a large‐scale design‐based research effort" British Journal of Educational Technology
45(6): 1036-1048.
Madhavan, J., Jeffery, S., Cohen, S., Dong, X., Ko, D., Yu, C. and Halevy, A. (2007). “Web-scale data
integration: You can only afford to pay as you go”. In: Proceedings of 6th
Conference on Innovative
Data Systems Research (pp. 342-350).
Malcolm, J., Hodkinson, P. and Colley, H. (2003). "The interrelationships between informal and formal
learning". Journal of workplace learning 15(7/8):313-318.
Mikroyannidis, A. (2007) "Toward a social semantic web” Computer 40(11):113-115.
Newman, S. (2005) “Building Micro-services. Designing Fine-Grained Systems”. O’Relly Media.
Paavola, S. and Hakkarainen, K. (2005). “The knowledge creation metaphor, an emergent epistemological
approach to learning”. Science & Education. 14(6):535-557.
References
35

36. Schmidt, J. P., Geith, C., Håklev, S. and Thierstein, J. (2009) ”Peer-to-peer recognition of learning in open
education”. The International Review of Research in Open and Distributed Learning, 10(5):1-16.
Siemens, G. (2011). ”Learning and Academic Analytics”. 5 August 2011
http://www.learninganalytics.net/?p=131, last visit May 2016
Slade, S. and Prinsloo, P. (2013). ”Learning analytics ethical issues and dilemmas”. American Behavioral
Scientist, 57(10):1510-1529.
Tashakkori, A. and Teddlie, C. (2010) ”Sage handbook of mixed methods in social & behavioral research”
(2nd edition). Los Angeles, USA:Sage.
Wang, F. and Hannafin, M. J. (2005). ”Design-based research and technology-enhanced learning
environments”. Educational technology research and development, 53(4):5-23.
Whitaker, A. (2012). "An Introduction to the Tin Can API". The Training Business. 19 July 2012
http://www.thetrainingbusiness.com/softwaretools/tin-can-api/, last visit May 2016
References
36