Learning Analyticsam Beispiel des Mathetrainers

Martin Ebner

http://wp.nmc.org/horizon2011/

Horizon Report (2007 - 2012)

Educational Data Mining

Educationa data mining (EDM) is a field that exploits statistical, machine-learning,

and data-mining (DM) algorithms over the different types of educational data. Its main objective is to analyze these types of data in order to resolve educational

research issues.

Romero, C. (2010) Educational Data Mining: A Review of the State of the Art - in: Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 40, p. 601 - 618

... there are 11 fields

• Analysis and Visualization of Data, • Providing Feedback for Supporting Instructors• Recommendations for Students• Predicting Student’s Performance• Student Modeling• Detecting Undesirable Student Behaviors• Grouping Students• Social Network Analysis• Developing Concept Maps• Constructing Courseware• Planning and Scheduling

Romero, C. (2010) Educational Data Mining: A Review of the State of the Art - in: Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 40, p. 601 - 618

Learning Analytics

Learning Analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on

learning.

George Siemens (2010) http://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics

Learning Analytics

Learning Analytics is about collecting traces that learners leave behind and

using those traces to improve learning.

Erik Duval (2012) http://www.slideshare.net/erik.duval/learning-analytics-13050389

It‘s all about

http://www.flickr.com/photos/neeravbhatt/6995946039

Potenzial ist heute noch schwer abschätzbar, da mit zunehmender

Datenmenge gänzlich neue Sichtweisen gewonnen werden können.

Martin Ebner & Martin Schön (2012)

ABER ...

Peter Purgathofer (2010), Gesellschaftliche Aspekte der Informationstechnologie

Peter Purgathofer (2010), Gesellschaftliche Aspekte der Informationstechnologie

Informationhttp://www.flickr.com/photos/auuep/3357824170

Interpretation

Beispiel

... ein scheinbar simples Problem ...

Beispiel

... das kleine EinmalEins für Volksschulkinder ...

http://youtu.be/P9qVWtVWYQI

http://mathe.tugraz.at

http://mathe.tugraz.at

Lernfortschrittsanzeige

Funktionsweise des Algorithmus

!

http://einmaleins.tugraz.at

Analyse

!

• Beobachtungs zeitraum: 1,5 Monate• n = 230• > 750 Sessions• > 28.000 generierte Beispiele• > 6 Minuten / Session im Schnitt

http://einmaleins.tugraz.at

Analyse

! !

http://einmaleins.tugraz.at

Analyse - Alle BenutzerInnen

!

http://einmaleins.tugraz.at

!

Analyse - Alle BenutzerInnen

http://einmaleins.tugraz.at

http://mathe.tugraz.at

Detailanalyse

! !

... Lernfortschritt

... Lernrate

http://einmaleins.tugraz.at

http://einmaleins.tugraz.at http://einmaleins.tugraz.at

http://einmaleins.tugraz.at http://einmaleins.tugraz.athttp://einmaleins.tugraz.at

http://mathe.tugraz.at

http://multitrainer.tugraz.at

http://multitrainer.tugraz.at

http://multitrainer.tugraz.at

http://multitrainer.tugraz.at

Learning Analytics / PLE (TU Graz)

http://my.tugraz.at

Learning Analytics ist die Interpretation von lernerspezifischen Daten um den individuellen Lernprozess gezielt zu

verbessern.

Martin Ebner & Martin Schön (2012)

1x1 Trainer in Zahlen (9 Monate)

> 1000 Kinder

> 60.000 Rechnungen

> 60 Rechnungen / Kind

http://mathe.tugraz.at

Freie Bildungs-materialien

http://www.flickr.com/photos/ell-r-brown/3912248265http://www.bims.com

http://mathe.tugraz.at

Graz University of Technology

SOCIAL LEARNINGComputer and Information Services

Graz University of Technology

Martin Ebner

http://elearning.tugraz.atmartin.ebner@tugraz.at

Slides available at: http://elearningblog.tugraz.at

mebner