Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - WEKIT (Wearable Experience for Knowledge Intensive Training)

Teaser

Possibilities for widespread automation in the 2020s, brought forward by advances in robotics and artificial intelligence, have started disrupting the job market at scale, also the linked training-and-updating market, and the emerging market for performance...

Summary

Possibilities for widespread automation in the 2020s, brought forward by advances in robotics and artificial intelligence, have started disrupting the job market at scale, also the linked training-and-updating market, and the emerging market for performance support/augmentation. A worryingly-large professional skills gap exists and is predicted to widen between tasks and job profiles in ample supply today (eg as routine-isable blue or white collar jobs) but at risk through full- or partial-automation, and tomorrow’s work tasks and job profiles that are in high demand through and beyond automation (eg high-experience, high-flexibility, high-knowledge and performance-focused jobs).

WEKIT, short for Wearable Experience for Knowledge Intensive Training, tries to tackle this professional skills gap using innovative real-time learning methodology and training technology to support professional development in ways that speed the diffusion of new bodies of knowledge (eg from pioneers and inventors, to early adopters and \'Industry 4.0\'), helping to make knowledge-intensive jobs more fulfilling, ergonomic, efficient, and effective, specifically targeting industrial training on-the-job. Funded under the Horizon 2020 programme for three years from December 2015 to November 2018, WEKIT developed and tested a wearable hard- and software solution to this knowledge-diffusion problem. The solution combines recording human expertise live and in situ from skilled experts, to then map and provide extracted instruction to novice learners or to remind infrequent performers, using the same wearable solution (or scaled-down versions thereof), all along the way supported by analytics providing feedback on actual levels of performance.

Using Augmented Reality and Smart Glasses, WEKIT effectively brings textbooks to life using digital audio-visual data overlaid on the physical environment, for example in the form of animations. The WEKIT.one soft- and hardware system shows the trainee what to do through the eyes of the expert, allowing the trainee to learn by experience rather than simply reading about it or watching a video tutorial. It also allows an expert to create instructions easily for themselves (as an aide memoire) or for others - by capturing performance using the wearable sensor framework.

WEKIT brings together 13 partner organisations representing academia and industry from six countries in Europe to build a ground-breaking, industrial-strength learning technology platform and unique methodology for capturing expert experience and sharing it with trainees in the process of enabling immersive, in-situ, and intuitive learning.

WEKIT mobilises its community of stakeholders – WEKIT.club – to roadmap pathways for the use of Technology-Enhanced Learning in changing industrial landscapes. The technology platform developed in the project – WEKIT.one – based on a thorough analysis of industrial needs and validated through user tests will enhance human abilities to acquire procedural knowledge by providing a smart system that directs attention to where it is most needed. Thanks to WEKIT, new smarter products and services will significantly improve workflows, enhancing (re)training of workers whose skill sets need upgrading after ‘Industry 4.0’.

The project objectives are:
•to develop an open technology platform for Augmented Reality experience based on open standards and licenses
•to research how we identify, acquire and exploit skills valued by industry and based on that research, to develop and evaluate a conceptual framework for capturing workplace experience, combining it with technical documentation
•to augment training in situ with live expert guidance, a tacit learning experience and a re-enactment of the expert
•to create a roadmap for Augmented Reality experience-based learning together with the community ensuring high take-up by early adopters in the industry

Work performed

The project work is segmented into four phases: A brief \'leading requirements engineering\' phase (M1-6) is followed by the first \'development and evaluation\' cycle (M7-18). The project continues with a second iteration of \'development and evaluation\' (M19-33), to finally culminate in a short phase focusing on \'introduction and wrap-up of work\' (M34-36, extended to M39 to allow inclusion of additional final-phase industry trials).

This overview reports on the status as of the final review of the project (covering M1-36 and a 3-month extension to M39) and thus provides insights on achievements with respect to the framework and industrial learning methodology, and its implementation in the prototypes, as well as results from the evaluation cycles. From a user point of view, the first prototype allowed testing of the first MVP Minimum Viable Product facilities for capturing experience (authoring side, aka ‘The Recorder’), the sensor platform and sensor processing unit (observation side, aka ‘SPU’), and facilities for re-enacting experience (learner side, aka ‘The Player’). That MVP testing was complemented by an online community platform that was then linked with the fuller version of the repository further developed in the second phase of the project. The final review period included all of the validation trials conducted in and with the three pilot partner companies, results of which were made available in phases (by M18 and by M36 respectively). From a technical point of view, this period reported covers the initial and final versions of the modular architecture, the specification of a standard for interoperability of augmented reality learning experiences (and a series of steps in its standardisation in the IEEE standard association), the initial and final versions of hardware selection and integration in the sensor framework, the visualisation and workplace integration framework and methodology. Moreover, it documents achievements in community building and dissemination, as well as steps undertaken towards exploitation and sustainability of the project’s assets beyond the runtime of the project.

Final results

WEKIT successfully achieved the expected M36 milestones for impact (eg regarding peer-reviewed publications and invited sessions at key conferences) and for the visibility of our new paradigms for AR and wearable experience and associated standards for TEL, which were necessary steps in reaching the impact measures promised in the DoA (section 2.1 Expected Impacts).
Noteworthy challenges we addressed throughout the project concern how to work in concert with other Horizon 2020 TEL projects and the EC-sponsored network of excellence EC-TEL, to jointly increase the EU\'s visibility in, and impact upon, US-dominated ecosystems for technology-enhanced learning, TEL. As an example, through actions such as its leadership in standards and specifications in AR and in wider TEL (advances in methodologies for content creation and localisation; insights relevant to personalisation to learner needs), WEKIT has won the attention and support of global players in interoperability in knowledge-intensive domains of training and education (eg IEEE). This is raising the historically low level of visibility of EU TEL to companies and investors in TEL, with considerable implications for the EU TEL community in reducing barriers to multi-country exploitation of products and services based on EU-originated TEL research.

Website & more info

More info: https://wekit.eu/.