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Dr. Hendrik Drachsler, UHD, Pre-Con. #OWD2015 09.11.2015
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Learning
Analytics
http://www.flickr.com/photos/traftery/4773457853Picture Pic. by Tom Raftery:
@HDrachsler
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• Hendrik Drachsler
Associate Professor
Learning Technologies
• Research topics:
Personalization,
Recommender Systems,
Learning Analytics,
Mobile devices
• Application domains:
Schools, HEI, Medical
education
WhoAmI
2006 - 2009
@HDrachsler
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3
Research activites
SURF
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@HDrachsler, #LASI_NL, Zeist, Netherlands
Slide 4 / 29 June 2014
1. Why LA
2. LA Framework
Lecture structure
3. Conclusions
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More ICT = More DATA
Deze data zijn waardevol en informatief.
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The Big Data Economy
Voorbeeld:
The Google Flue trend
technology …
… kun nu ook voor
onderwijs toegepast
worden.
Learning Analytics = Data Science voor educatie
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New MIT study
``
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Onderwerp via >Beeld >Koptekst en voettekst
Pagina 8
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DATA van
Learning Profiles
DATA van
LMS en MOOCs
DATA van
Learning Resources (Apps, Games,..)
DATA van
assessments
Wat zijn educatief data?
De eerste keer dat wij de leerling in het
leerproces kunnen volgen.
- On Demand Learning Measures -
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17
Reinhardt, W., Meier, C., Drachsler, H., & Sloep, P. B. (2011). Analyzing 5 years of EC-TEL
proceedings. In C. D. Kloos, D. Gillet, R. M. Crespo García, F. Wild, & M. Wolpers (Eds.),
Towards Ubiquitous Learning: 6th European Conference of Technology Enhanced Learning, EC-
TEL 2011 (pp. 531-536). September, 20-23, 2011, Palermo, Italy. LNCS 6964; Heidelberg,
Berlin: Springer.
Nieuwe inzichten
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17
Nieuwe inzichten
Dawson, S., Bakharia, A., & Heathcote, E. (2010, May). SNAPP: Realising the
affordances of real-time SNA within networked learning environments. In
Proceedings of the 7th International Conference on Networked Learning (pp. 125-133).
Denmark, Aalborg.
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17
Graph by Rob Koper. Data science voor de realisatie van online activerend onderwijs.
Presentation given at Dag van het Onderwijs (5 November 2015). Heerlen. The Netherlands
Nieuwe inzichten
Learning
Activities
Studytime
in days
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`
17
Graph by Rob Koper. Data science voor de realisatie van online activerend onderwijs.
Presentation given at Dag van het Onderwijs (5 November 2015). Heerlen. The Netherlands
Nieuwe inzichten
Learning
Activities
Studytime
in days
``
`
@HDrachsler, #LASI_NL, Zeist, Netherlands
Slide 14 / 29 June 2014
1. Why LA
2. LA Framework
3. Conclusions
Lecture structure
``
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``
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16
Greller, W. & Drachsler, H. (2012). Turning Learning into Numbers. Toward a Generic
Framework for Learning Analytics. Journal of Educational Technology & Society.
http://ifets.info/journals/15_3/4.pdf
Visualiz.
``
`
17
Stakeholders
data
subjects
data
clients
Greller, W. & Drachsler, H. (2012). Turning Learning into Numbers. Toward a Generic
Framework for Learning Analytics. Journal of Educational Technology & Society.
http://ifets.info/journals/15_3/4.pdf
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18
Stakeholders
Verbert, K., Duval, E., Klerkx, J., Govaerts, S., & Santos, J. L. (2013). Learning
analytics dashboard applications. American Behavioral Scientist.
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19
Objectives
Reflection Prediction
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20
Educational Data
Drachsler, H., et al. (2010). Issues and Considerations regarding Sharable Data Sets for
Recommender Systems in Technology Enhanced Learning. 1st Workshop Recommnder
Systems in Technology Enhanced Learning (RecSysTEL@EC-TEL 2010) September, 28,
2010, Barcelona, Spain.
Verbert, K., Manouselis, N., Drachsler, H., and Duval, E. (2012). Dataset-driven Research
to Support Learning and Knowledge Analytics. Journal of Educational Technology &
Society. www.ifets.info/journals/15_3/10.pdf
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`
21
Edu. Data Storage
Berg, A., Scheffel, M., Ternier, S., Drachsler, H., and Specht, M. (submitted). Dutch
cooking with xAPI recipes and the flavour of various Learning Record Stores.
Learning Analytics and Knowledge conference 2016, Edinburgh, UK.
•  Various heterogonous
data sources
•  No metadata standards
•  No proper description of
data fields
•  No unique user ID in the
different systems
•  Not intended for
evaluation and educational
interventions
•  No comparison of effective
methods
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22
Edu. Data Storage
Berg, A., Scheffel, M., Ternier, S., Drachsler, H., and Specht, M. (submitted). Dutch
cooking with xAPI recipes and the flavour of various Learning Record Stores.
Learning Analytics and Knowledge conference 2016, Edinburgh, UK.
``
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Data Standards
``
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24
Technologies
Prediction
Manouselis, N., Drachsler, H., Verbert, K., and Duval, E. (2012).
Recommender Systems for Learning. Berlin:Springer
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25
Technologies
Reflection
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26
Constraints
1. Data security
2. Ethics & Privacy
3. Transparency
4. Ownership
``
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27
Constraints
•  $100 million investment
•  Aim: Personalized learning in public schools, through data &
technology standards
•  9 US states participated, In 2013 data about millions of children
have been stored
``
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28
Constraints
``
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29
Constraints
http://www.open.ac.uk/students/
charter/essential-documents/
ethical-use-student-data-learning-
analytics-policy#
https://www.jisc.ac.uk/sites/default/files/
jd0040_code_of_practice_for_learning_a
nalytics_190515_v1.pdf
``
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30
Constraints
Engelfriet, A., Jeunink, E., Manderveld,
J. (2015). Learning analytics onder de
Wet bescherming persoonsgegevens
https://www.surf.nl/kennis-en-innovatie/
kennisbank/2015/learning-analytics-
onder-de-wet-bescherming-
persoonsgegevens.html
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31
Competences
1. E-literacy
2. Interpretation skills
3. Agency
4. Privacy understanding
``
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32
Competences
Drachsler, H., Stoyanov, S., d'Aquin, M., Herder, E., Dietze, S., & Guy, M. (2014, 16-19
September). An Evaluation Framework for Data Competitions in TEL. 9th European
Conference on Technology-Enhanced Learning (EC-TEL 2014), Graz, Austria.
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@HDrachsler, #LASI_NL, Zeist, Netherlands
Slide 33 / 29 June 2014
1. Why LA
2. LA Framework
3. Conclusions
Lecture structure
``
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34
LA driven instructional Design
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Sophistican model
Siemens, G., Dawson, S., & Lynch, G. (2014). Improving the Quality and Productivity of
the Higher Education Sector – Policy and Strategy for Systems-Level Deployment of
Learning Analytics. Canberra, Australia: Office of Learning and Teaching, Australian
Government. Retrieved from http://solaresearch.org/Policy_Strategy_Analytics.pdf
LA Sophistication Model
``
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@HDrachsler, #LASI_NL, Zeist, Netherlands
Slide 36 / 29 June 2014
Creative data
sourcing,
necessary IT
support
Question-
driven, not
data or IT
driven
Participatory design
of analytics tools
One–size-fits-all does not work in LA
and is no innovation
Suggestions to do own LA
``
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Join us:
www.laceproject.eu
``
`
38
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
Many thanks for your attention!

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