D2.2 Learning Experience Content Model (draft)

This deliverable proposes a draft specification for the WEKIT content model for learning experiences. The proposed content model consists of an activity modelling language and a workplace modelling language, both together able to express how users of the WEKIT.one AR soft- and wearable hardware solution can interact with media and the environment in pursuit of developing new (or upgrading existing) knowledge, skills, and other abilities.


The core of this deliverable comes in a different format: The specification is a formal submission for the

P1589 working group of the IEEE standards association. The new working group p1589 for ‘Augmented Reality Learning Experience Models’ (AR-LEM) was approved by the New Standards Committee (NesCom) of the IEEE standards association on February 16, 2015. The working group was granted until December 2019 and it is under the sponsorship of the learning technologies standards committee and its chair Avron Barr.
The spec draws wide input from the stakeholder community of WEKIT, with contributions formally honoured in the section ‘participants’ in the spec. While the kick off meeting of the working group took place virtually on June 3, 2015, the WP2 work on the content model was organised alongside in the ARLEM working group meetings that took place mostly on a monthly basis. The website for the standards outreach is http://arlem.cct.brookes.ac.uk.

Following this submission, a first ballot will take place, requiring two prior readings in the p1589 working group meetings to establish voting membership. Subsequently, a phase of outreach events shall assist especially technology providers in implementation and validation of their support of the interchange format. The final first version of the standard is planned in for the end of 2017.
The ARLEM specification serves as the interchange format, providing the representation needed to collate recording and sensor data into consumable learning activities and workplace models needed for the re-enactment system for performance augmentation.

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