Bett 2016 - Implementing learning analytics in your school

Implementing Learning Analytics in Your School

Wietse van Bruggen, Project Manager, Kennisnet [email protected]

Jan Hylén, Researcher, Skolverket SE

[email protected]

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What is Learning Analytics?

• The measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs – First International Conference on Learning Analytics And

Knowledge (LAK11), Banff, Alberta, Feb 27-Mar 1, 2011

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What is Learning Analytics?

• “Collecting traces that learners leave behind and using those traces to improve learning”

– Erik Duval http://erikduval.wordpress.com/2012/01/30/learning-analytics-and-educational-data-mining/

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LACE Evidence Hub

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LACE School Blog

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Tool selection

• Learning materials are becoming increasingly digital.

• With the move to digital materials, products will most likely all have some form of learning analytics as a feature, even if not explicitly sold as learning analytics.

• Whether a certain tool fits your schools needs depends on your vision on personalized learning / education.

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Tool selection

• Learning materials are becoming increasingly digital.

• With the move to digital materials, products will most likely all have some form of learning analytics as a feature, even if not explicitly sold as learning analytics.

• Whether a certain tool fits your schools needs depends on your vision on personalized learning / education.

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Tool selection

• Vision on learning– Teacher-driven learning

• Learners are organized in groups depending on their age and level.

• Learning materials are matched to the level of the group

• Teacher directs the learning process of the group.

– Autonomous learning• Learning materials are aimed at the needs of the individual learner (pace,

level, order)

• Learning is organized to work towards a pre-set goal.

• Teacher directs the learning process of the individual.

– Self-organized learning• Learner itself directs the learning process (with assistance and coaching)

• Learner is responsible for their own learning process.

• Learner learns on their own level, their own pace, in their own style, from their interests.

10Source: Four in Balance monitor 2013, Kennisnet

Tool selection

• Survey of tools in the Netherlands.

• All contain some form or learning analytics functionality, dashboards, adaptivity etc.

• Most tools fit into the teacher-driven vision.

• Some tools fit into the autonomous learning model or would not require extensive modification to be able to support it.

• Self-organized learning is the least supported model.

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Example: The School in Zandvoort

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Example: The School in Zandvoort

• School is open all year.

• Learning is organized for each individual and not in fixed groups.

• Each individual learner has their own program, their own timesheet.

• “We have to look carefully at digital learning tools and whether they support our views on learning. Creators of digital learning tools often say that their tool supports personalized learning, but in the design of their tool they often work with the idea of groups or learners or classes, and not the individual. A lot of products therefor are not useful for us or can be hard to work with because they don’t fully support our way or working.”

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Privacy

• Privacy agreement on national level.

• Privacy agreement en model contract created in collaboration with school representatives and major suppliers of digital learning materials, tools and systems.

• Have agreed to adhere and implement these agreements.

• Agreements on how personal data should be handled when using digital learning tools/materials and digital testing.

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Privacy

• Model contract that can be used by schools and suppliers.

• For example:– Limits the use of personal data to the goals for

which a school has given authorization.

– Supplier has to provide an overview of the categories of personal data it will use and process.

– Personal data obtained by suppliers cannot be supplied to third parties unless explicitly allowed by an educational institution.

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Questions

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Data teams: Schildkamp, Handelzalts, & Poortman

Swedish pilot studyin two schools

An analytic team in the school

• 6-8 participants

• a coach as support

• a chair person

• the school manager

• mixed competences in the team

• meetings for 1,5 hour every 4th week

• ”Why are our pupils performing less well in Math than the pupils in the neighbouring school”?

Conclusions from pilot study

• From gut feeling to data driven qualityimprovements

• Key factors for successEnough timeGroup size importantStick to the modelThe group ”owns” the processThe coach has a key rolePrepare yourself before starting

Questions

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www.laceproject.euLearning Analytics Community Exchange (FP7)

• Coordination and Support

• Evidence Hub

• Events

• Publications, briefings, webinars

Wietse van Bruggen, Kennisnet NL

Jan Hylén, Skolverket SE

This work was undertaken as part of the LACE Project, supported by the European Commission Seventh Framework Programme, grant 619424.

These slides are provided under the Creative Commons Attribution Licence: http://creativecommons.org/licenses/by/4.0/. Some images used may have different licence terms.

www.laceproject.eu@laceproject

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