de zes dimensies van learning analytics
TRANSCRIPT
```
Dr. Hendrik Drachsler, UHD, Pre-Con. #OWD2015 09.11.20151
Learning Analytics
http://www.flickr.com/photos/traftery/4773457853Picture Pic. by Tom Raftery:
```
3
• Hendrik DrachslerAssociate Professor Learning Technologies
• Research topics:Personalization, Recommender Systems, Learning Analytics, Mobile devices
• Application domains: Schools, HEI, Medical education
WhoAmI
2006 - 2009
@HDrachsler
```
3
Research activitesSURF
```
@HDrachsler, #LASI_NL, Zeist, NetherlandsSlide 4 / 29 June 2014
1. Why LA2. LA Framework
Lecture structure
3. Conclusions
```
More ICT = More DATA
Deze data zijn waardevol en informatief.
```
The Big Data Economy Voorbeeld:
The Google Flue trendtechnology …
… kun nu ook voor onderwijs toegepast worden.
Learning Analytics = Data Science voor educatie
```
New MIT study
```
Onderwerp via >Beeld >Koptekst en voettekstPagina 9
```
DATA vanLearning Profiles
DATA vanLMS en MOOCs
DATA vanLearning Resources (Apps, Games,..)
DATA vanassessments
Wat zijn educatief data?
De eerste keer dat wij de leerling in het leerproces kunnen volgen.
- On Demand Learning Measures -
```
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
```
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.
```
17Graph 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
LearningActivities
Studytime in days
```
17Graph 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
LearningActivities
Studytime in days
```
@HDrachsler, #LASI_NL, Zeist, NetherlandsSlide 16 / 29 June 2014
1. Why LA 2. LA Framework
3. Conclusions
Lecture structure
```
```
18
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.
```
19
Stakeholdersdata 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
```
20
Stakeholders
Verbert, K., Duval, E., Klerkx, J., Govaerts, S., & Santos, J. L. (2013). Learning analytics dashboard applications. American Behavioral Scientist.
```
22
ObjectivesReflection Prediction
```
24
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
```
25
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
```
26
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.
```
Data Standards
```
34
TechnologiesPrediction
Manouselis, N., Drachsler, H., Verbert, K., and Duval, E. (2012). Recommender Systems for Learning. Berlin:Springer
```
35
TechnologiesReflection
```
36
Constraints
1.Data security
2.Ethics & Privacy
3.Transparency
4.Ownership
```
37
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
```
38
Constraints
```
40
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_analytics_190515_v1.pdf
```
41
Constraints
Learning analytics onder de Wet bescherming persoonsgegevens
```
42
Competences
1.E-literacy
2.Interpretation skills
3.Agency
4.Privacy understanding
```
43
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.
```
@HDrachsler, #LASI_NL, Zeist, NetherlandsSlide 44 / 29 June 2014
1. Why LA2. LA Framework
3. Conclusions
Lecture structure
```
45
LA driven instructional Design
```
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
```
@HDrachsler, #LASI_NL, Zeist, NetherlandsSlide 50 / 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
```
Join us: www.laceproject.eu
```
116