Data Sets as Facilitator for new Products and Services for Universities

Dr. Hendrik DrachslerCentre for Learning Sciences and Technology@ Open University of the Netherlands

Data Sets as Facilitator for new Products and Services for Universities

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29.11.2010 VOR-ICT Bijeenkomst, Utrecht, The Netherlands

• Assistant Professor at the Learning Networks ProgramOUNL / CELSTEC

• Research topics:Learning Networks, Technology Enhanced Learning, Recommender Systems, Personalisation, Mash-Ups and widget technology, Health2.0

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Whoami

We live in a decade of industrial change

Change picture

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“The biggest challenge businesses face today is unlearning what was successful in the industrial age and learning how to prosper in the network era.”

The challenge

Jay Cross (2006)

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Graphic by Alex Guerten, 2008

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GLOBALISATION

LO C A L I S AT I O N


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G LO C A L I S AT I O N


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C O N S U M E R S

PRODUCERS



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P R O S U M E R SGraphic by Alex Guerten, 2008

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http://flickr.com/photos/zoharma/97214235/sizes/l/by Zohar Manor-Abel

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The Glocalisation / Prosumers world

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Example Networks

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Example Networks

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Example Networks

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Example Networks

v

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http://blog.core-ed.net/derek/2006/11/more_on_mles_and_ples.html

life symbiotic...

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Data & Recommender Systems

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Data emerge

Johnson, S. (2001)

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Data emerge

Johnson, S. (2001)

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Data emerge

Johnson, S. (2001)

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Data emerge

Johnson, S. (2001)

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Data emerge

Johnson, S. (2001)

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Data emerge

Johnson, S. (2001)

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Data emerge

“We are leaving the age of information and entering the age of recommendation”

Chris Anderson (2004)

Johnson, S. (2001)

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Recommender Systems

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Recommender Systems

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Recommender SystemsPeople who bought the sameproduct also bought product B or C …

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The Long Tail

13Graphic Wilkins, D., (2009); Long tail concept Anderson, C. (2004)

The Long Tail

13Graphic Wilkins, D., (2009); Long tail concept Anderson, C. (2004)

The Long Tail of Learning

TEL recommender are a bit like this...

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TEL recommender are a bit like this...

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We need to select for each application an appropriate recommender that fits its needs.

But...

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Kaptain Koboldhttp://www.flickr.com/photos/kaptainkobold/3203311346/

“The performance results of different research efforts in recommender systems are hardly comparable.”

(Manouselis et al., 2010)

But...

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Kaptain Koboldhttp://www.flickr.com/photos/kaptainkobold/3203311346/

“The performance results of different research efforts in recommender systems are hardly comparable.”

(Manouselis et al., 2010)

The TEL recommender experiments lack transparency. They need to be repeatable to test:

• Validity• Verification• Compare results

How others compare their their recommender systems

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How others compare their their recommender systems

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Although the TEL domain stores plenty of data everyday in e-learning environments (LMS, PLEs) it typically lacks shareable and publicly available data sets.

Data Products & Science

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Promises of Open Data

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Unexploited potentials:


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• The evaluation of learning theories and learning technology


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• More transparent, mutually comparable, trusted and repeatable experiments that lead to evidence-driven knowledge


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• More transparent, mutually comparable, trusted and repeatable experiments that lead to evidence-driven knowledge

• Development of new educational data products that combine different data sources in data mashups

New Science Paradigms

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• Thousand years ago science was empirical (Describing natural phenomena)

• Last few hundred years science: theoretical branch (Using models, generalizations)

• Last few decades: computational branch (Simulating complex phenomena)

• Nowadays: data science(Unify theory, experiment, and simulation, data captured by instruments and processed by software)

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Data Products

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Data Products

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Data Products

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Data Products

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Data Products

Educational Data Products• Drop-out Analyzer• Group Formation Recommender • Question-Answering Tool• Awareness Tools

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Data Products

Educational Data Products• Drop-out Analyzer• Group Formation Recommender • Question-Answering Tool• Awareness Tools

Future Activities

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Beyond

O P E N DATA

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Beyond

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Beyond the

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Beyond

O P E N DATAO P E N DATA

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Beyond the

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Beyond

O P E N I N N O VAT I O NO P E N I N N O VAT I O N

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Beyond the

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Beyond

VISUALIZATION OF DATAVISUALIZATION OF DATA

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Beyond the

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Beyond

M A S H U P T E C H N O L O G YM A S H U P T E C H N O L O G Y

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Beyond the

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Beyond

R E C O M M E N D E R S Y S T E M SR E C O M M E N D E R S Y S T E M S

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Beyond the

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Beyond

P ROT E C T I O N R I G H T SP ROT E C T I O N R I G H T S

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Beyond the

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Open Data

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Open Data

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Open Data

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Open Data

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Open Data

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Open Data

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Open Data

Data Visualization

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Data Visualization

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Data Visualization

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Open Innovation

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Open Innovation

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R&D -> C&D

Open Innovation

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R&D -> C&D

Open Innovation

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R&D -> C&D

Mashups and Widgets

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Mashups and Widgets

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Recommender Systems

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Recommender Systems

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Recommender Systems

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Protection Rights

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Protection Rights

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Protection Rights

O V E R S H A R I N G

3 Take away messages

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Plan(t)ing for the future

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Plan(t)ing for the future 1. Use digital ecosystem services for student projects (Google API, Yahoo pipes, Twitter, Reuters Open Calais ...)

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2. Apply and create open data for research (Become part of the ecosystem, open innovation, science2.0 -> pre-processing, privacy protection)

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2. Apply and create open data for research (Become part of the ecosystem, open innovation, science2.0 -> pre-processing, privacy protection)

3. Empower your users to adjust and remix your contributions to the web (Open API’s, protocols, standards -> interoperability)

This silde is available at:http://www.slideshare.com/Drachsler

Email: [email protected]

Skype: celstec-hendrik.drachsler

Blogging at: http://www.drachsler.de

Twittering at: http://twitter.com/HDrachsler

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Questions and ideas now or later...

References

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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.