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Workplace-based e-Assessment Technology for Competency-based Higher Multi-professional Education

Continuing education at the workplace has seen increasing demand as a crucial means of acquiring the requisite professional knowledge and skills. Electronic Portfolios (e-portfolios) for workplace training provide a global view of each trainee’s progress but offer no dynamic feedback to exploit the rich learning assessment data that could be analysed to support responsive adaptation for more efficient and rewarding training.

WATCHME effectively deploys Learning Analytics (LA) tools to deliver personalised learning; supporting learner empowerment, enhanced Quality-of-Experience, flexibility and mobility plus efficiency gains through workplace-based feedback and assessment. This is achieved by developing, implementing and evaluating a mobile, electronic portfolio-based system that utilises LA and student models to provide data-driven and model-based tailored feedback via a visualisation dashboard. The multi-sourced integrated deployment of authentic workplace data including self-reporting, narratives, qualitative and quantitative data e.g. videos and serious educational games enables the WATCHME trainees to exercise and thereby sharpen their learnt skills by responding to realistically situated judgment calls in a motivational and safe environment.

A Multi-entity Bayesian Network will be used for the student models, enabling an aggregation of data and tailored Just-in-Time feedback, visualised via intuitive interfaces. The close cooperation of educational researchers and ICT developers will deliver a tool to map critical professional tasks linked to their requisite competencies and markers for feedback and assessment in the workplace integrated with an easy access electronic portfolio system for data collection and LA-driven tools to inform trainees, teachers and supervisors about the trainee’s progress and deliver personalised Just-in-Time feedback with intuitive visualisation tools.

The WATCHME platform will be empirically validated for its quality and contribution to trainees’ learning. The overall system shall be evaluated formatively and summatively in three professional environments (human medicine, veterinary medicine and teacher training) including benchmarking against control sets.

Project Details

Project funded by: EU
Project Duration: 03/14 - 02/17
Project Partners: Utrecht University (NL), Jayway (DK), Mateum (NL), NetRom (RO), Szent Istvan University (HU), University of Tartu (EE), Universitätsmedizin Charité Berlin (DE), Maastricht University (NL), University Medical Centre Utrecht (NL), University of Reading (UK), University of California San Francisco (USA) [Associate Partner]
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Integrated Cognitive Assistive Domotic Companion Robotic System for Ability & Security

There are widely acknowledged imperatives for helping the elderly live at home (semi)-independently for as long as possible. Without cognitive stimulation support the elderly dementia and depression sufferers can deteriorate rapidly and the carers will face a more demanding task. Both groups are increasingly at the risk of social exclusion.

CompanionAble will provide the synergy of Robotics and Ambient Intelligence technologies and their semantic integration to provide for a care-giver's assistive environment. This will support the cognitive stimulation and therapy management of the care-recipient. This is mediated by a robotic companion (mobile facilitation) working collaboratively with a smart home environment (stationary facilitation).

The distinguishing advantages of the CompanionAble Framework Architecture arise from the objective of graceful, scalable and cost-effective integration. Thus CompanionAble addresses the issues of social inclusion and homecare of persons suffering from chronic cognitive disabilities prevalent among the increasing European older population. A participative and inclusive co-design and scenario validation approach will drive the RTD efforts in CompanionAble; involving care recipients and their close carers as well as the wider stakeholders. This is to ensure end-to-end systemic viability, flexibility, modularity and affordability as well as a focus on overall care support governance and integration with quality of experience issues such as dignity-privacy-security preserving responsibilities fully considered.

CompanionAble will be evaluated at a number of testbeds representing a diverse European user-base as the proving ground for its socio-technical-ethical validation. The collaboration of leading gerontologists, specialist elderly care institutions, industrial and academic RTD Partners, including a strong cognitive robotics and smart-house capability makes for an excellent confluence of expertise for this innovative project.


Project Details

Project funded by: EU
Project Duration: 01/08 - 06/12
Project Partners: The University of Reading (GB), Technical University of Ilmenau (D), Assistance Publique Hopitaux de Paris (F), Groupe des Ecoles des Telecommunications (F), Fundacion Tecnalia (E), AIT Austrian Institute of Technology GmbH (A), Legrand France SA (F), AKG Acoustics GmbH (A), Chambre de Commerce et d'Industrie de Paris CCIP (F), AG ESIGETEL (F), Universite d'Evry-Val d'Essonne (F), Metralabs GmbH Neue Technologien und Systeme (D), Stichting Smart Homes (NL), Center for Usability Research and Engineering (A), Universidad da Coruna (E), Innovation Centre in Housing for Adapted Movement (B), Fundacion Instituto Gerontologico Matia - Ingema (E), Verklizan B.V. (NL)
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Network Embedded Middleware for Heterogeneous Physical Devices in a Distributed Architecture

Hydra is a middleware for building secure, fault-tolerant Networked Embedded Systems where diverse heterogeneous devices co-operate to achieve a given goal. It aims to research, develop, and validate middleware for networked embedded systems that allows developers to develop cost-effective, high-performance ambient intelligence applications for heterogeneous physical devices. The main aim is to hide the complexity of the underlying infrastructure while providing open interfaces to third parties for application development.

Specific projects objectives include:

  • Research and development of a middleware for networked embedded systems that allows developers to develop cost-effective, high-performance ambient intelligence applications for heterogeneous physical devices.
  • Development of a Software Development Kit (SDK) that can be used by developers to develop innovative Model-Driven applications.
  • Research and development of a business modelling framework for analysing the business sustainability of the developed applications.

Project Details

Project funded by:


Project Duration:

07/06 - 06/10

Project Partners:

CNET SVENSKA AB (S), Fraunhofer Gesellschaft zur Förderung der angewandten Forschung e.V. (D), In-JET APS (DK), Priway APS (DK), T-Connect S.R.L. (I), Telefonica Investigacion y Desarrollo SA Unipersonal (E), Aarhus Universitet (DK), Innova S.P.A. (I), The University of Reading (GB), Mesh-Technologies A/S (DK), Siemens IT Solutions and Services GmbH & Co. OHG (D), Technicka Univerzita V Kosiciach (SK)

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