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2nd Learning Analytics Summer Institute in the Netherlands (#LASI-NL)

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2nd Learning Analytics Summer Institute (#LASI-NL)

in conjunction with the Computer Assisted Learning Conference CAA2014 (http://caaconference.co.uk/)

30.06. – 01.07.2014, near Utrecht at Woudschoten in Zeist, Netherlands

Jointly organised by SURF SIG LA the https://www.surfspace.nl/sig/18-learning-analytics/ and the EU FP7 project LACE http://www.laceproject.eu

Workshop website: http://lasiutrecht.wordpress.com

Sign up here (Participation is free of costs):

http://www.surf.nl/agenda/2014/06/learning-analytics-summer-institute-lasi-2014/index.html

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Dear Learning Analytics enthusiasts,

On the 30th of June until 1th of July, the 2nd Learning Analytics Summer Institute in the Netherlands (#LASI-NL) will be organised in conjunction with the Computer Assisted Learning Conference CAA2014 (http://caaconference.co.uk/).

After a very successful LASI-Amsterdam in 2013, we wish to foster the Dutch Learning Analytics community and their research efforts with this local event. The event is part of a global network of LASI events (http://www.solaresearch.org/events/lasi-2/lasi2014/) that will be hold at that time in different locations over in the world.

Several key researchers from the European projects such as the FP7 Projects LACE (www.laceproject.eu) and WatchMe (http://www.project-watchme.eu) as well as the Open Source community Apereo Foundation (http://www.apereo.org/) will present their approach and research agenda towards Learning Analytics. Furthermore, we will have some collaboration between the CAA conference and the local LASI event through a Special Track of Learning Analytics in e-Assessment and a panel discuss on the future of e-assessment in times of Learning Analytics.

We expressly invite people that are new to the field to engage with the Dutch research community around Learning Analytics. LASI-NL tries to bring researchers together in a two-day summer school to foster synergies between national and international research efforts in the field. You are invited to join and exchange your expertise and experiences and contribute constructively to the Learning Analytics community.

The two days will be split into two different topics:

1. Practitioner day (30th of June). This track is looking at barriers to adoption, stakeholder requirements, instructional design and methods.

2. Data Wrangler day (1st of July) is focused on the pragmatic issues for practitioners in the field such as insight over tooling, what are the standards needed to build infrastructure within a University and a workshop on getting data out of your LMS (e.g.: BlackBoard) and using.

The event will last two full days, is completely free and will be partly in Dutch and in English. Lunch is included. The event is being held near Utrecht at Woudschoten (http://www.woudschoten.nl/) in Zeist.

Sign up here

http://www.surf.nl/agenda/2014/06/learning-analytics-summer-institute-lasi-2014/index.html

DETAILED SCHEDULE

MONDAY, 30.06.2014

Requirements track

10:00 KEYNOTE by Dr. Stefan Mol & Dr. Gabor Kismihok, Universiteit van Amsterdam, ‘Barriers to adoption for Learning Analytics at a Dutch University’

10:45 Discussion with keynote speakers

11:00 Coffee break

11:30 Stakeholder Requirements (EU FP7 LACE project), Dr. Hendrik Drachsler

12:00 Lunch break

Practitioner track

13:00 Learning Analytics supported Instructional Design (EU FP7 WatchME project), Dr. Jeroen Donkers

15:00 Coffee break

15:30 Learning Analytics & Assessment Methods (Joint paper session wit CAA)

17:00 Panel discussion between LASI NL and CAA

TUESDAY, 01.07.2014

Data wrangler track

10:00 KEYNOTE by Prof. Dr. Ulrich Hoppe, University Essen-Duisburg, Germany. ‘Beyond the obvious – advanced analytics tools and applications in educational contexts’

10:45 Discussion with the Keynote speakers

11:00 Coffee break

11:15 The Caliper and XApi frameworks what are they and why they are important

11:45 Apereo Foundation & LACE – Learning Analytics Initiative and working in an International community

12:00 Lunch break

Technology track

13:00 How to get your hands on the data of your LMS (e.g. Blackboard) Session 1, Alan Berg, Hendrik Drachsler

14:30 Coffee break

15:00 How to get your hands on the data of your LMS (e.g. Blackboard) Session 2, Alan Berg, Hendrik Drachsler

16:30 Closing & Drinks

Using linked data in Learning Analytics

Learning Analytics has a lot to do with data, and the way to make sense of raw data in terms of the learner’s experience, behaviour and knowledge. In this article, we argue about the need for a closer relationship between the field of Learning Analytics and the one of Linked Data, which in our view constitutes an ideal data management layer for Learning Analytics. Based on our experience with organising the “Using Linked Data in Learning Analytics” tutorial at the Learning Analytics and Knowledge conference, we discuss the existing trends in the use of linked data and semantic web technologies, in general in education and in Learning Analytics specifically. We find that the emerging connections between the two fields are still, at the time of writing, much less prominent than one would expect considering the complementary nature of the considered technologies and practices. We therefore argue that specific efforts, somehow materialised through the tutorial and the work in the LinkedUp support action, are needed to ensure the realisation of the potential cross-benefits that combining Learning Analytics and Linked” Data research could bring.

http://portal.ou.nl/documents/363049/8074517e-da6d-47f2-9296-8911e7fb4d51

http://creativecommons.org/licenses/by-sa/3.0/

d’Aquin, M., Dietze, S., Herder, E., Drachsler, H. (2014). Using linked data in learning analytics. eLearning Papers. Nr. 36/2. ISSN: 1887-1542. http://www.openeducationeuropa.eu/en/article/Using-linked-data-in-Learning-Analytics?paper=134810

The storify story of the #LAKdata14 data competition, LAK14, Indianapolis, Indiana, USA

LAK14 data challenge (#LAKdata14)

On 25ht of March 2014 the 2nd  workshop at the Learning Analytics & Knowledge Conference 2014, Indianapolis, Indiana, USA took place.

Again we wanted to know what analytics on learning analytics tell us? How can we make sense of this emerging field’s historical roots, current state, and future trends, based on how its members report and debate their research?

The aim of #lakdata14 have been:

  • Analysis & assessment of the emerging LAK community in terms of topics, people, citations or connections with other fields
  • Innovative applications to explore, navigate and visualize the dataset (and/or its correlation with other datasets)
  • Usage of the dataset as part of recommender systems
  • Analysis of the evolution of LAK discipline
  • Improvement or enrichment of the LAK Dataset

This time we had four high quality submissions that provided new insights into the LAK & EDM dataset.

Introduction slides to the LAK14 data challenge by providing a retrospective of the LAK13 data challenge papers.

 

Dietze, S., Herder, E., d’Aquin, M., Taibi D., & Drachsler H. (2014). The LAK data challenge, Learning Analytic and Knowledge (LAK14) Indianapolis, Indiana, USA.

The winners were:

FIRST PRIZE: Deconstruct and Reconstruct, Mike Sharkey & Mohammed Ansari Deconstruct and Reconstruct provided some nice insights into the LAK 2014 dataset such as evidence of the merging of the LAK and EDM community, core research topics and their changes over years. The submission hit the core objective of the LAk14 challenge: What do analytics on learning analytics tell us? The various visualizations are meaningful and informative and extend knowledge we gained from the previous LAK data challenge: http://lak14.bluecanarydata.com/

SECOND PRIZE: A linked-data-driven web portal, Yingjie Hu et al.
The linked-data-driven web portal is really very powerful, provides nice visualizations on various objects such as authors, co-authors networks etc., and connects a large amount of datasets. Unfortunately, the level of reported insights by this powerful tool in the paper have been limited: http://stko-exp.geog.ucsb.edu/lak/

Demo:

THIRD PRIZE: Spiral me to the core, Maren Scheffel et al.
A nice visualization, the focus on core concepts make sense and help to explore the LAK key concept in a meaning full manner: http://mitarbeiter.fit.fraunhofer.de/~scheffel/LAKchallenge2014/

FOURTH PRIZE: RecLAK, Giseli Lopes et al.
RecLAK shows analysis of the metadata and recommendations of related datasets. The app demonstrates nicely how the LAK dataset can be extended and connected to other LD sources. A thorough investigation on which data sets can best be used for interlinking with LAK.

The data challenge has been very well appreciated their are plans to extend he current workshop challenge also with a twitter feed analysis of the LAK2011, 2012, 2013 and 2015. A couple of new people indicated their interest to participate in the #lakdata15 next year. The driving idea is to invite all previous submission on an early stage and ask them to present their insights accruing to some Focus Tasks.

Agenda of the 2nd LAK Data Challenge at LAK14, Indianapolis, USA

Agenda of the 2nd LAK Data Challenge #lakdata14 is out

http://portal.ou.nl/documents/363049/69bdc1dd-d162-4f89-bc88-a981d26c8387

http://creativecommons.org/licenses/by-sa/3.0/

Learning Analytics & Knowledge (LAK) DATA CHALLENGE 2014

*** LAK DATA CHALLENGE 2014 ***

*** http://lak.linkededucation.org ***

*** collocated with Learning Analytics & Knowledge 2014 ***

The LAK Dataset (http://lak.linkededucation.org/) provides access to

structured metadata from research publications in the field of learning

analytics. Beyond merely publishing the data, we are actively

encouraging its innovative use and exploitation as part of a public LAK

Data Challenge sponsored by the European Project LinkedUp

(http://linkedup-project.eu), co-located with the Learning Analytics &

Knowledge Conference 2014 conference in Indianapolis, Indiana (US) in

March 2014.

IMPORTANT DATES

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- 20th January, 2014: submission deadline

- 3rd February, 2014: notification deadline

- 24-28 March, 2014: LAK2014 Conference.

CHALLENGE OBJECTIVE

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What do analytics on learning analytics tell us? How can we make sense

of this emerging fieldís historical roots, current state, and future

trends, based on how its members report and debate their research?

Challenge submissions should exploit the LAK Dataset for a meaningful

purpose. This may include submissions which cover one or more of the

following, non-exclusive list of topics:

- Analysis & assessment of the emerging LAK community in terms of

topics, people, citations or connections with other fields

- Innovative applications to explore, navigate and visualise the dataset

(and/or its correlation with other datasets)

- Usage of the dataset as part of recommender systems

- Analysis of the evolution of the LAK discipline

- Improvement and enrichment of the LAK Dataset

SUBMISSION FORMAT

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Each submission should be accompanied by a 2-4 page paper (ACM format,

see http://www.acm.org/sigs/publications/proceedings-templates) that

contains at least:

- an abstract of the submission

- motivation: which purposes does your system or dataset serve?

- description of your dataset (e.g. if the LAK data is combined with

other datasets), system or demo

- a link to your dataset and/or system or demo

Please use the EasyChair submission form

(https://www.easychair.org/conferences/?conf=lakdatachallenge2014) for

all submissions.

EVALUATION

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There will be a light review by members of the challenge committee to

pre-select submissions for presentation. During the LAK conference and

based on the presentations, the challenge winner(s) will be identified

based on votes by the audience and the committee.

PUBLICATION, PRESENTATION & AWARDS

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Accepted submissions will be published in online proceedings and

presented during an interactive LAK Data workshop collocated with the

LAK 2014 conference in Indianapolis, Indiana (US). The three best papers

of each workshop will be invited to a Special Issue in the Journal for

Learning Analytics. In addition, there will be awards for the winning

submissions with very cool prizes (further details to be announced)!

CHALLENGE COMMITTEE

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- Mathieu D’Aquin (The Open University, United Kingdom)

- Stefan Dietze (L3S Research Center, Germany)

- Hendrik Drachsler (Open Universiteit Nederland, Netherlands)

- Eelco Herder (L3S Research Center, Germany)

- Davide Taibi (Institute for Educational Technologies CNR, Italy)

CONTACT

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lakdatachallenge2014@easychair.org

TEL4Health – Mobile Tools for patient safety

The Presentation given at the blended learning platform of the Netherlands Organisation for Hospitals (Nederlandse Vereniging van Ziekenhuizen) , Utrecht, Netherlands.

http://portal.ou.nl/documents/363049/2409d5a7-fc6e-453e-845e-afd9b1dfc0ef

http://creativecommons.org/licenses/by-nc-sa/3.0/

Drachsler, H., Kalz, M., Specht, M. (2013). TEL4Health – Mobile Tools for patient safety. The Presentation given at the blended learning platform of the Netherlands Organisation for Hospitals (Nederlandse Vereniging van Ziekenhuizen) , Utrecht, Netherlands.

R&D activites on Learning Analytics

The presentation provides an overview of the R&D activities of the Learning Analytics topic at the Open Universiteit in October 2013.

http://portal.ou.nl/documents/363049/789b3323-d55c-4e3e-93ba-a716ade14463

http://creativecommons.org/licenses/by-nc-sa/3.0/

Drachsler, H., Specht, M. (2013).

Hoe ziet de toekomst van Learning Analytics er uit?

Presentation given in the Dutch Masterclass: ‘Hoe ziet de toekomst van Learning Analytics er uit?’

http://portal.ou.nl/documents/363049/1adc41e5-52f5-4b08-8b98-bf19b635931a

http://creativecommons.org/licenses/by-nc-sa/3.0/

Drachsler, H., (September, 2013). Hoe ziet de toekomst van Learning Analytics er uit? Open Universiteit, CELSTEC, Heerlen, The Netherlands.

Group Concept Mapping on Learning Analytics

Presentation given at Learning Analytics Summer School Institute (LASI) to kickoff the national GCM study on LA, Amsterdam, The Netherlands.

http://portal.ou.nl/documents/363049/3430aeb1-2450-4587-8f26-e56efd7b80c4

http://creativecommons.org/licenses/by-nc-sa/3.0/

Stoyanov, S., Drachsler, H. (2013). Group Concept Mapping on Learning Analytics. Presentation given at Learning Analytics Summer School Institute (LASI) to kickoff the national GCM study on LA, Amsterdam, The Netherlands.